ElevenLabs

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations provide only idempotentHint=true and readOnlyHint=false. The description adds valuable behavioral context: the distinction between permanent config token and session token, and that no args returns a link. It could further detail state changes or side effects, but it is fairly transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a few sentences, front-loaded with the main purpose, and includes necessary details without significant fluff. Slightly dense but well-organized and readable.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple tool with one optional parameter and no output schema, the description covers the purpose, parameter semantics, invocation patterns, and persistence implications. It doesn't mention response format or failure handling, but overall is sufficiently complete for the tool's simplicity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 1 parameter with no description (0% coverage). Description fully compensates by explaining that the token is a JWT, is optional, and that omitting it yields a login link. This is essential usage information beyond the bare schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the tool's function: authenticate MCP.AI for IDE agents by logging in and obtaining/copying an access token. It distinguishes usage modes (permanent config vs session-only) and specifies the parameter behavior, making the purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit instructions for two usage scenarios: permanent config header vs session-only token, and how to call with or without the token. Does not explicitly contrast with sibling tools or state exclusions, but the guidance is practical and clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, idempotent, and non-destructive, so the description adds no contradiction. It goes beyond annotations by detailing the return values in both states (authenticated:true and empty pending[] vs. connect_url and per-install URLs), which is valuable context. No behavioral traits contradict the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences and front-loads the core purpose. Every clause adds meaning: the first gives the general behavior, the second covers the conditional outcomes. No redundancy or fluff—exemplary conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (no params, no output schema), the description covers the main states comprehensively. It explains the all-connected case and the missing-credentials case, though the partial-state (some providers missing) is not explicit. Still, it provides enough for an agent to decide calling it. The description is adequate for this low-complexity tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With zero parameters, the description has nothing to define about parameters. The baseline for 0-parameter tools is 4, and the description is not required to add parameter info. It does not mislead or omit anything since no parameters exist.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Returns' and the resource 'connection status and URLs', making the purpose specific. It distinguishes from siblings by focusing on status retrieval rather than connection creation (e.g., authenticate). The conditional details further clarify behavior.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use this tool by outlining the two response scenarios (all connected vs. missing credentials), which tells the caller they can use it to check if authentication is needed. It does not explicitly mention alternatives or exclusions, but the context is sufficient for common use.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate this is a mutating operation (readOnlyHint=false). The description adds useful context about creation modes (blank or from URL) and bulk execution, but does not disclose side effects, authentication needs, or behavior when from_url is null. This is adequate but not rich.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and front-loaded with the core purpose. The 'Bulk support' line adds useful information without waste. Minor redundancy exists in 'Create Chapter' followed by 'Creates a new chapter,' but overall it is efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 5 parameters, 0% schema coverage, no output schema, and sparse annotations, the description leaves notable gaps: it does not explain account, the relationship between project_id and project_ids, or expected return behavior. It covers the primary use case but is incomplete for a tool with this complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It explains from_url and project_ids, but leaves name, project_id, and especially account undefined. The parameter names are partially self-explanatory, but account is ambiguous and no additional meaning is provided.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'Creates a new chapter either as blank or from a URL.' This is a specific verb+resource pairing that distinguishes it from sibling tools like elevenlabs_edit_chapter and elevenlabs_delete_chapter_endpoint by emphasizing 'new' chapter creation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use the tool: when creating a chapter, with the option to create blank or from a URL. It also mentions bulk support via project_ids. However, it does not explicitly state when not to use it or name alternatives like edit_chapter.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations are all false, so no safety information is provided. The description only says 'creates' without disclosing side effects, idempotency, required permissions, or what happens to existing data. It doesn't mention that it's a write operation or any other behavioral traits, leaving the agent without crucial operational context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely brief (two sentences) but under-specified rather than concise. It lacks essential details about parameters, use cases, and behavior, making it too minimal to be helpful. Front-loading is irrelevant when almost no content exists.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 5 parameters, a complex nested rules array, no output schema, and sparse annotations, the description is entirely inadequate. It fails to explain the structure of rules, the purpose of the dictionary, or how this tool fits into the broader workflow. It provides no context for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description only mentions 'rules' without explaining the two possible rule types (alias vs phoneme), required fields, or the meaning of other parameters like name, account, description, and workspace_access. It adds negligible value beyond the schema structure itself.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states it creates a new pronunciation dictionary from provided rules, which is a clear verb+resource. However, it doesn't differentiate from sibling tools like elevenlabs_add_rules, elevenlabs_set_rules, or elevenlabs_update_pronunciation_dictionaries, which could also involve rules and dictionaries.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is given on when to use this tool versus alternatives. It doesn't mention whether it's for initialization only, or how it relates to updating or patching existing dictionaries. The description implies it's for creating new dictionaries, but no explicit context or exclusions are provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate this is a mutating operation (readOnlyHint=false) and not destructive. The description adds the permission requirement and bulk support, which are not covered by annotations. But it does not disclose side effects like what happens if the member already exists in the group, or any rollback/reversibility. Since annotations provide a baseline, the extra permission info justifies a 3.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely efficient: two sentences that convey the core action, permission, and an optional bulk feature. No filler or redundancy. Perfectly front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple mutation tool with no output schema, the description covers the main action and permission, plus bulk capability. However, it lacks details on return values, edge cases (duplicate members), and any potential side effects. Given the simplicity, it's minimally adequate but not rich.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It only explicitly explains 'group_ids' for bulk execution. The required parameters 'email' and 'group_id' are implied but not defined, and 'account' is completely unexplained. This is insufficient for an agent to correctly construct parameters, so a low score is warranted.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action: 'Adds a member of your workspace to the specified group.' This is a specific verb and resource, and it distinguishes from sibling tools like elevenlabs_remove_member and elevenlabs_invite_user. The title 'Add Member To User Group' reinforces the purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains the permission required ('group_members_manage'), which gives a usage prerequisite. It implies this tool is for adding existing workspace members to groups, and the bulk support note clarifies an alternative usage. However, it does not explicitly contrast with other member-management tools (e.g., invite_user), so it earns a 4 rather than a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond annotations (which only indicate non-readOnly and non-destructive), the description discloses that existing rules with the same string_to_replace are replaced, a key behavioral trait. It also mentions bulk execution capability. This adds meaningful context not present in annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and front-loaded, but redundant: the first sentence repeats the tool name almost verbatim ('Add Rules To The Pronunciation Dictionary' vs 'Add rules to the pronunciation dictionary'). The bulk support note is clearly separated. Overall efficient but with minor redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has a complex input schema (nested rules array with two types) and no output schema. The description does not explain rule structure, required fields, or what happens on success/failure. It also lacks detail on permissions or side effects. Incomplete for a complex tool with zero annotation coverage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate but does not. It only mentions string_to_replace and pronunciation_dictionary_ids, giving minimal meaning to a couple of parameters. The rules array structure, the two rule types (alias vs phoneme), and other params like account remain unexplained.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool adds rules to a pronunciation dictionary and mentions replacement behavior for existing string_to_replace. However, it does not explicitly differentiate from sibling tools like set_rules or add_from_rules, relying on the name for distinction.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for adding pronunciation rules and mentions bulk support via pronunciation_dictionary_ids, but provides no explicit guidance on when to use this tool versus alternatives or any exclusions. It lacks contextual cues like 'use this instead of set_rules when...'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already communicate that this is a write operation and not destructive. The description adds some behavioral context by stating the voice is added to 'your collection' and mentioning batched execution via plural parameters, but it does not disclose naming-conflict behavior, permissions, or reversibility.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and front-loaded, with the core purpose in the first sentence and the bulk capability in the final sentence. The only minor issue is that 'Add Shared Voice' redundantly repeats the tool name, but overall it is efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 7 parameters, no output schema, and no parameter descriptions, this description is too sparse. It does not explain required versus optional usage, batch semantics in detail, account targeting, or expected outcomes, making it incomplete for reliable invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate, but it only mentions public_user_ids and voice_ids for bulk support. It fails to explain required fields like new_name, or optional ones like account and bookmarked, and does not clarify the relationship between singular and plural parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb and resource: 'Add a shared voice to your collection of voices.' This clearly distinguishes the action from sibling tools like elevenlabs_create_voice, which creates a new voice, while this tool imports an existing shared voice.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the usage context—adding shared voices to a personal collection—and notes bulk execution support. However, it gives no explicit guidance on when to prefer this tool over alternatives such as create_voice, nor any exclusions or prerequisites.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations provide only basic flags (readOnly false, destructive false). The description adds significant behavioral context: it states the tool queues content for conversion and auto-publishing, indicating a non-reversible side effect. It also implies mutation of an existing project. No contradictions with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single efficient sentence that front-loads the action and explains the workflow. It is appropriately sized, though the capitalization of 'From Url' is odd and could be cleaned up. No unnecessary words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the high-level workflow but omits key details: it doesn't explain the meaning of title, author, or account parameters, nor does it mention prerequisites, error conditions, or exactly what 'auto-publishing' entails. Given no output schema and sparse annotations, a more complete description would include parameter roles and potential side effects.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% for parameters, so the description must explain them. It only addresses 'url' implicitly as the matching key, but 'title', 'author', and 'account' are left unexplained. This is a significant gap for a 4-param tool. The description adds minimal value beyond what the parameter names alone suggest.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the purpose: 'Update Audio-Native Content From Url' and then elaborates on the process: finding a project by URL, extracting content, updating, and queueing for conversion and auto-publishing. This is specific and distinguishes it from sibling update tools by focusing on the URL-driven workflow.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

While no explicit exclusion or alternative tools are mentioned, the description provides a clear context of when to use this tool: when you have a URL and want to update an AudioNative project with content extracted from it. The workflow description implies its unique use case, but it doesn't explicitly contrast with alternatives like 'elevenlabs_edit_project'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations provide no safety hints (all false), so the description must explain behavior. It mentions generation and bulk execution but omits what the composition plan contains, whether it persists or is ephemeral, cost implications, or non-determinism. The description adds minimal context beyond what the tool name already implies.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short with only two sentences. It front-loads the purpose. However, the first sentence 'Generate Composition Plan' is redundant with the second sentence 'Generate a composition plan from a prompt', wasting a few words. Still, it is generally concise and readable.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

This tool has a large, complex input schema (nested source_composition_plan with sections/chunks), no output schema, and no annotations. The description gives almost no context about expected inputs, outputs, or workflow. It is severely incomplete for an agent to correctly select and invoke this tool, especially among many similar creation tools.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It only explains `prompt` (source of generation) and `model_ids` (batched execution), but leaves `source_composition_plan`, `music_length_ms`, `account`, and `model_id` unexplained. The complex nested source_composition_plan parameter is entirely undocumented in prose.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'Generate a composition plan from a prompt' which clearly identifies the verb (generate) and resource (composition plan). It is distinct from sound_generation or text_to_speech, though it doesn't explicitly name sibling alternatives. The addition of bulk support via model_ids adds specificity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives like elevenlabs_sound_generation or elevenlabs_generate. The only hint is 'Bulk support: accepts model_ids for batched execution', which implies it supports batched usage but doesn't clarify single vs batch selection or prerequisites.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description reveals that the tool 'starts' a conversion, implying an asynchronous operation, but it does not explain what the conversion produces, how to track its status, what side effects occur, or what the response contains. The annotations provide only generic flags, so the description carries most of the burden and falls short.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very short and front-loaded, with the key information in the second sentence. The first sentence 'Convert Chapter.' is largely redundant with the tool name, so not every word earns its place, but overall the description is appropriately sized.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a state-changing tool with no output schema and sparse annotations, the description leaves too much unspecified: no mention of conversion status/results, no polling guidance, no account/auth details, and no explanation of batch behavior beyond parameter names. The minimal description is insufficient for reliable invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description does add some meaning by distinguishing singular conversion ('a specific chapter') from bulk execution via 'project_ids, chapter_ids'. However, it does not clarify the relationship between the required singular fields and the batch arrays, nor does it explain the 'account' parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action: 'Starts conversion of a specific chapter', identifying the resource and operation. It also mentions bulk support, which adds scope. However, the opening line 'Convert Chapter.' largely repeats the tool name and it does not explicitly contrast with the sibling 'elevenlabs_convert_project_endpoint'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The bulk-support sentence gives useful context for when to use the array parameters, implying batching is supported. However, it does not explicitly say when to prefer this tool over convert_project_endpoint or what distinguishes single vs. bulk usage beyond parameter choice.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations indicate destructiveHint=false, which is helpful, but the description does not disclose any behavioral traits beyond starting a conversion. It doesn't explain what happens to existing converted content, whether it is asynchronous, required permissions, or potential side effects. With no annotations covering behavior (only hints), the description carries a partial burden and fails to provide meaningful transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and front-loaded with the main action, but the two-sentence structure is acceptable. However, it lacks crucial detail, so while concise, that conciseness is at the expense of completeness. The bulk support note is useful but could be integrated better.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given that there is no output schema and only 3 params with 0% coverage, the description is inadequate. It doesn't mention return values, async behavior, or what 'conversion' results in. For a tool that initiates a process, the lack of any post-condition description makes it incomplete. An agent would not know what to expect after calling it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, meaning the description must compensate for explaining parameters. The description only mentions 'project_ids' for bulk support, but does not explain 'project_id' or 'account' semantics beyond what the schema type provides. It adds minimal value, leaving the agent to infer the meaning of project_id and account. No details on format, constraints, or relationships.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'Convert Studio Project' and says it starts conversion of a project and its chapters, which is a specific verb+resource. However, it doesn't clearly distinguish from the sibling 'elevenlabs_convert_chapter_endpoint' except implicitly by resource. There's no explicit differentiation or mention of what conversion entails. The purpose is clear enough but lacks depth.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. There is no mention of prerequisites, context, or when not to use it. The sibling 'elevenlabs_convert_chapter_endpoint' is a direct alternative but not referenced. The 'Bulk support' note hints at a use case but doesn't provide decision guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations are present but only indicate the tool is not read-only, not idempotent, and not destructive. The description adds minimal behavioral context: it creates a new connection but does not disclose the impact on existing connections, authentication requirements, or handling of secrets. For a mutation tool, this is insufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is only two sentences, but they are nearly identical: 'Create Workspace Auth Connection' and 'Create a new OAuth2 auth connection for the workspace' repeat the same information. The redundancy makes it less concise than a single well-crafted sentence would be.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of the input schema (multiple OAuth2 variants), the absence of annotations, and no output schema, the two-sentence description is completely inadequate. It does not explain the purpose of the 'body' object, the meaning of fields like 'auth_type', or how the tool behaves across the different variants.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description must explain the parameters, but it does not mention 'body' or 'account' at all. The schema shows seven distinct OAuth2 variant shapes, but the description offers no guidance on which variant to select or what each field means, leaving the agent completely in the dark.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Create') and resource ('Workspace Auth Connection'), adding specificity with 'OAuth2'. However, it contains a redundant first sentence that merely rephrases the tool name, and it does not distinguish this from sibling tools like update or list auth connections.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description offers no guidance on when to use this tool versus alternatives such as elevenlabs_update_auth_connection or elevenlabs_delete_auth_connection. It also does not mention any prerequisites, when a new connection is needed, or how to choose among the various OAuth2 flows.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations only indicate not read-only, not idempotent, and not destructive, so the description adds valuable behavioral context: creation, auto-conversion, current and future pricing, and batch execution. It does not mention the response shape or whether conversion is synchronous/asynchronous, but the disclosed cost and bulk behavior go beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is relatively short and readable. 'Create Podcast' is somewhat redundant with the tool name, but the cost explanation and bulk-support note are useful and concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the large parameter surface, 0% schema description coverage, and no output schema, the description is not fully sufficient for correct invocation. It omits important guidance on mode variants, source structures, quality/duration enums, and the conversion lifecycle, though it does add cost and bulk context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate for the 15 parameters. It only explains model_ids for batched execution, leaving required parameters like model_id, mode, and source—and all other optional parameters—without semantic explanation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool creates and auto-converts a podcast project, distinguishing it from sibling creation tools like elevenlabs_create_voice or elevenlabs_create_speech_engine. The verb and resource are specific and unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear context for when to use the tool: to create and auto-convert a podcast project. It also provides useful operational guidance by noting bulk execution via model_ids and cost considerations. It does not explicitly state when not to use it, but the purpose is well scoped.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The phrase 'with metadata but no samples' is useful behavioral context and goes beyond the annotations, making clear that this call does not create or attach audio samples. However, the description does not disclose required permissions, whether the operation can be repeated safely, what the returned object contains, or how a created PVC voice fits into the overall sample-upload/training flow. Since annotations are generic, some behavioral burden remains unmet.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and the second sentence adds the key distinction 'with metadata but no samples.' However, the first sentence 'Create Pvc Voice.' is a tautological restatement of the tool name and adds no value. The description could be improved by removing that first sentence and adding a more useful workflow hint instead.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

This is a creation tool with no annotations that describe safety or lifecycle details, no output schema, and no parameter descriptions. The description only scratches the surface by saying no samples are created. It leaves out the deeper context needed to use it reliably in a multi-step PVC workflow, such as what happens after creation, which differentiates it from the many sibling PVC-related tools.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description does not explain any of the five parameters: name, labels, account, language, or description. It only says metadata is included, which does not clarify required values, formats, or meaning. The parameter semantics are essentially undocumented at the description level.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the core action clearly: 'Creates a new PVC voice with metadata but no samples.' This specifies the resource (PVC voice) and adds a useful scope distinction, which differentiates it from general voice-creation tools like elevenlabs_create_voice. The opening sentence 'Create Pvc Voice' is redundant, so it does not earn a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives no guidance on when to use this tool versus alternatives. It does not mention that this tool only initializes a voice and that samples must be added or training must be run later via sibling tools such as elevenlabs_edit_pvc_voice_sample or elevenlabs_run_pvc_voice_training. No exclusions, prerequisites, or recommended workflows are provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations provide generic flags, and the description aligns with them without contradiction. It adds useful quota context (20 default, 100 enterprise maximum), but it does not disclose permission requirements, duplicate-name behavior, idempotency implications, or what result the tool returns.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very short and front-loaded, but the first sentence 'Create Service Account' is redundant with the tool name and the second sentence repeats the same idea. Only the quota sentence adds genuinely new information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a creation tool with three undocumented parameters and no output schema, the description is incomplete. It gives the purpose and a quota constraint but lacks parameter details, usage guidance, and expected result information.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% and the description provides no meaning for the three parameters: name, account, and default_sharing_groups. The structured schema reveals some shape for default_sharing_groups, but the description itself adds nothing to parameter understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool creates a new service account in the workspace. It is specific enough to distinguish from the sibling API-key creation tool, though the first sentence merely repeats the tool name and no explicit alternative is mentioned.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not explain when to use this tool versus related service-account tools. It only mentions workspace quota limits, leaving usage timing and selection criteria to be inferred.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate this is not read-only, not idempotent, and not destructive. The description adds the bulk-execution behavior, which is useful context. It does not disclose auth requirements, rate limits, or side effects, but the annotation coverage lowers the burden somewhat.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short, but the first sentence ('Create Service Account Api Key') largely repeats the tool name and adds little value. The second sentence and bulk note are useful, so it is concise but not optimally structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 8 parameters, no output schema, and no parameter descriptions, the description is insufficient for an agent to confidently invoke the tool. It does not explain required permissions, the meaning of fields like allowed_ips or character_limit, or what the response contains.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description only adds meaning for one parameter (service_account_user_ids for bulk execution). The other seven parameters—including required ones like permissions and name—are left entirely to the schema, which lacks descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action: 'Create a new API key for a service account.' This distinguishes it from service-account creation and key deletion/editing, though it does not explicitly name sibling alternatives.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The bulk support note ('accepts service_account_user_ids for batched execution') provides some usage guidance for batched vs. single execution. However, there is no explicit guidance on when to prefer this tool over related tools like elevenlabs_edit_service_account_api_key or elevenlabs_delete_service_account_api_key.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations provide no explicit safety hints (all false), so the description carries the burden of disclosing behavioral traits. It only says 'Create', implying a mutation but adds no details about side effects, required permissions, response format, or failure modes. This is minimal and does not go beyond the obvious.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is terse (two short sentences) but contains redundancy ('Create Speech Engine' and 'Create a new Speech Engine resource' essentially repeat the same information). It is not structured to front-load key details and wastes a bit of space, but it is not overly verbose either.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (13 parameters, nested objects, no output schema), the description is drastically inadequate. It provides no explanation of what a Speech Engine is, what the required 'speech_engine' object entails, or what successful creation returns. The description does not help the agent understand the tool's role or usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, meaning the description adds no meaning to any of the 13 parameters. The schema itself is detailed, but the description does not compensate for the low coverage. There is no mention of required parameters, purpose of fields, or examples, making the parameters practically opaque to the agent.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool creates a new Speech Engine resource, using a specific verb ('Create') and resource ('Speech Engine'). It distinguishes from sibling tools like 'get_speech_engine' and 'update_speech_engine' by implying a creation operation. However, the redundancy 'Create Speech Engine. Create a new Speech Engine resource' slightly detracts but does not obscure purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives, nor any prerequisites or context. It merely states what the tool does without any exclusions or distinctions, leaving the agent without decision-making support.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations are all false (readOnly=false, idempotent=false, etc.), indicating a mutating create operation. The description adds the prerequisite context but does not disclose additional behaviors like whether it permanently stores the voice, any auth requirements, or error scenarios. It is not contradictory, but it does not go beyond the basic action.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is succinct, just two sentences, with the action stated first and the prerequisite second. No filler or redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of output schema and 0% schema coverage, the description only partially covers necessary context. It explains the main flow and prerequisite but omits details on other parameters, response structure, and potential side effects. More information would be needed for complete guidance, particularly for the non-required parameters and expected return value.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate for parameter meaning. It only explains generated_voice_id and how to obtain it. Other parameters like voice_name, voice_description, labels, account, and played_not_selected_voice_ids are left unexplained, leaving significant ambiguity for the agent.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb and resource: 'Create A New Voice From Voice Preview' and explains that it creates a voice from a previously generated preview. It distinguishes from other creation tools by specifying the prerequisite generated_voice_id and pointing to specific prior endpoints.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly states when to use this tool: after fetching a generated_voice_id via the specified endpoints. It also names the alternative endpoints (design and remix) which are the prerequisites, giving clear context. However, it does not explicitly state when not to use it, though the prerequisite implies that.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations broadly indicate this is not read-only but do not detail side effects. The description adds only that the webhook has a specified auth type, which is already reflected in the schema. It does not disclose behavior such as required permissions, URL validation, whether headers are optional, or what happens on duplicate webhook names—leaving the safety and effect profile underspecified.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and front-loaded, but the first sentence 'Create Workspace Webhook' merely repeats the tool name. The second sentence provides minimal value. It is concise but primarily because it contains so little information; it does not suffer from verbosity, but it also does not use the available space to earn each sentence.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has a nested settings object with several required fields, no output schema, and no property descriptions. The description does not adequately explain the domain context, how webhook_url should be formatted, what auth types are supported, or what account refers to. For a mutation with this complexity, far more context is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate for explaining parameters. It only mentions 'authentication type', which merely restates the auth_type field. It does not explain 'account', 'name', 'webhook_url', or 'request_headers', so the agent has little understanding of what values to supply or their purpose.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states this tool creates a new workspace webhook, using the specific resource 'webhook' and the action 'create'. It distinguishes itself from sibling tools like edit_workspace_webhook_route and delete_workspace_webhook_route by explicitly stating it creates a new webhook, though it doesn't elaborate on the 'route' aspect implied by the tool name.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives no explicit guidance on when to use this tool versus alternatives. There are sibling tools for editing, listing, and deleting workspace webhook routes, but the description only says 'create a new webhook' without mentioning when creation is appropriate, any prerequisites, or why to choose this over related tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Description states the tool deletes an item and associated media files, but annotations set destructiveHint=false, contradicting the description's explicit destructive behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is compact and front-loaded; the first sentence mostly restates the tool name, but the bulk-support sentence adds meaningful information without fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a deletion tool with no output schema, no parameter descriptions, and misleading annotations, the description omits return behavior, idempotency/irreversibility, and relationship to the required history_item_id field.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% and the description only explains history_item_ids for bulk use; it does not clarify history_item_id or account, leaving three parameters under-documented.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description uses specific verb 'deletes' and explicit resource 'audio isolation history item' plus 'associated media files', making the operation unambiguous and distinct from sibling delete tools such as elevenlabs_delete_speech_history_item.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The bulk support note ('accepts history_item_ids for batched execution') gives some usage context, but there is no explicit when-to-use guidance, prerequisites, or comparison to alternative delete endpoints.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description says 'Delete' which is a destructive action, but the annotation destructiveHint is false. This contradicts the annotation. Additionally, the description provides no behavioral details beyond the action itself, such as consequences, reversibility, or permissions, which is especially important given the sparse annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, consisting of two short sentences. However, the first sentence redundantly repeats 'Delete an auth connection' after 'Delete Workspace Auth Connection', wasting words. It is still appropriately front-loaded and no extraneous content appears.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple delete tool with three parameters and no output schema, the description provides the core action and bulk capability. However, it omits details about the 'account' parameter, lacks guidance on parameter choices, and fails to mention any side effects or prerequisites. While adequate for a minimal understanding, it is not fully complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It only mentions 'auth_connection_id' and 'auth_connection_ids' for bulk support, but does not clarify their relationship or explain the 'account' parameter at all. The meaning of parameters is largely inferred from names, and the description adds minimal semantic value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: deleting an auth connection from a workspace, with an explicit verb and resource. It distinguishes itself from sibling tools like elevenlabs_create_auth_connection, elevenlabs_update_auth_connection, and elevenlabs_list_auth_connections by explicitly naming the delete operation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage (when you need to delete an auth connection) but does not explicitly state when to use this tool versus alternatives. It mentions bulk support but does not clarify the distinction between single and batch deletion or provide any exclusionary guidance. No alternatives are named.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description says 'Deletes a chapter,' which is a destructive operation, while annotations declare destructiveHint=false. This is an annotation contradiction, and the description provides no additional behavioral context such as permanence, side effects, or permissions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very short, but the first two statements ('Delete Chapter' and 'Deletes a chapter') are redundant, wasting a sentence. The bulk-support sentence is useful and front-loaded, but the redundancy keeps this from being optimally concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a deletion tool with no output schema and sparse annotations, the description is too thin. It does not cover batch behavior details, singular vs. bulk parameter usage, expected responses, or failure modes. The bulk-support note is the only meaningful operational context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate for parameter meaning. It only clarifies that project_ids and chapter_ids enable batch execution, but does not explain the required project_id/chapter_id pair or the account parameter. This is insufficient for 5 parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool deletes a chapter, with a specific verb and resource. It distinguishes itself from sibling delete tools by the 'chapter' resource, though not explicitly naming alternatives. The bulk-support note adds useful scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied by the name and description: use this when deleting chapters. The bulk-support sentence gives some guidance for batched execution via project_ids and chapter_ids, but there is no explicit when-to-use versus alternatives or exclusionary guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotation contradiction: destructiveHint=false while the description says 'Deletes a dubbing project,' implying destructive behavior. The description also fails to disclose permanence, reversibility, or side effects beyond the stated action.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the main purpose, and the bulk support sentence adds useful information without redundancy. It is concise and readable, though sparse on details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a delete operation with conflicting annotations, a similarly named sibling, and an undocumented required parameter, the description is too thin. Missing permanence, alternative selection, and parameter relationship details.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It only explains dubbing_ids via 'bulk support,' leaving dubbing_id and account undefined, including whether dubbing_id is still required for bulk calls.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description states 'Deletes a dubbing project' with a specific verb and resource. However, it does not distinguish itself from the sibling 'elevenlabs_dubbing_project_delete', which appears to perform the same operation, preventing a top score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives like elevenlabs_dubbing_project_delete. The bulk support note hints at a use case but does not explain when to choose batch vs single deletion.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description says 'Delete a music finetune', which is a destructive operation, but the annotations declare destructiveHint=false. This is a direct contradiction, so behavioral transparency must be scored as 1.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and front-loaded, but it repeats the same idea twice: 'Delete Music Finetue' and 'Delete a music finetue'. The bulk hint is useful, but the redundancy means not every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a destructive, multi-parameter tool with no output schema, the description is too thin. It does not mention irreversibility, account context, what happens with missing/invalid IDs, or how finetune_id relates to finetune_ids, leaving material gaps for an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description needs to explain parameter meaning. It only adds context for finetune_ids ('batched execution'), but it does not explain finetune_id, account, or the relationship between single and bulk deletion.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Delete') and the resource ('music finetune'), so an agent can tell it deletes finetunes. It is distinguishable from sibling tools like elevenlabs_get_finetunes and elevenlabs_update_finetune, though the two opening sentences are largely redundant.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The bulk-support note provides some usage guidance: use finetune_ids for batched execution. However, it does not mention when to prefer this tool over get/update finetune tools, nor does it explain prerequisites or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description says 'Delete Existing Invitation' and 'Invalidates,' indicating a destructive mutation, while annotations declare destructiveHint=false. This is an annotation contradiction, so the transparency score is 1. The side-effect note about the invitation still appearing in the inbox is useful, but it cannot override the contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three terse sentences: direct action statement, key behavioral caveat, and permission constraint. No filler, redundancy, or wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the main effect and permission requirement but leaves the 'account' parameter ambiguous and does not mention response behavior or edge cases. Given no output schema and 0% schema coverage, it is adequate but not fully complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description only loosely maps to the email parameter via 'email invitation.' The 'account' parameter is entirely unexplained, and the description does not compensate for the lack of schema-level parameter descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description opens with 'Delete Existing Invitation' and clarifies 'Invalidates an existing email invitation,' giving a specific verb+resource. It clearly targets invitation deletion rather than member removal or other workspace management tools, distinguishing it from siblings like elevenlabs_remove_member.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The permission constraint is explicit: 'may only be called by workspace members with the WORKSPACE_MEMBERS_INVITE permission.' However, there is no explicit when-to-use vs alternatives guidance, and it does not mention related tools like elevenlabs_invite_user or elevenlabs_remove_member, so usage context is only implied.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The annotations declare destructiveHint: false, but the description explicitly says the tool 'Deletes a Studio project.' This is a direct contradiction. Additionally, the description does not mention irreversibility, cascading effects, required permissions, or response behavior, which a destructive operation should disclose.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and front-loaded, but the first two sentences are redundant: 'Delete Studio Project. Deletes a Studio project.' The bulk-support sentence adds value, but the repeated statement wastes space.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a destructive tool with no output schema and conflicting annotations, the description is underspecified. It omits important context such as deletion scope, reversibility, side effects on associated chapters or project data, and account handling. The bulk-support note is helpful but insufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must carry the parameter-semantics burden. It adds some meaning by noting that project_ids enables 'batched execution,' but it does not explain the relationship between project_id and project_ids, the role of account, or whether project_ids can substitute for the required project_id.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: 'Delete Studio Project. Deletes a Studio project.' This clearly distinguishes it from sibling delete tools that target other resources like dubbing, voice, or speech history.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided about when to use this tool versus alternatives such as elevenlabs_edit_project, elevenlabs_delete_dubbing_project, or other project-related operations. The only usage-related note is bulk support via project_ids, which is a capability statement, not a when-to-use guideline.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description explicitly says 'Delete a sample,' implying a destructive operation, yet the annotation destructiveHint is set to false. This is a direct contradiction. Additionally, there is no disclosure about irreversibility, permission requirements, or effects on the voice, which is critical for a deletion tool. The contradiction alone drops this to a 1.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact, front-loaded with the core action, and includes a brief note on bulk support. There is no redundant information, and every sentence adds value despite the contradictions. It is appropriately sized for the tool's simplicity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a deletion tool with no output schema and no helpful annotations (which are also contradictory), the description lacks crucial context: irreversible effects, prerequisites (e.g., ownership), or interaction with the voice's other samples. It also fails to clarify bulk execution semantics, such as whether both single and bulk parameters can be used together. This is insufficient for a potentially destructive operation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It only mentions voice_ids and sample_ids for bulk support, which is helpful but does not clarify the relationship with the required voice_id and sample_id parameters, nor whether they are alternatives or co-required. The description adds minimal value beyond the schema for these array parameters and ignores the single-field parameters entirely.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it deletes a sample from a PVC voice, which is specific and distinguishes it from generic delete_sample tools. It mentions bulk support via voice_ids and sample_ids, adding capability clarity. However, it doesn't explicitly contrast with sibling tools like elevenlabs_delete_sample, so it's not fully differentiated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description mentions bulk support using arrays, which gives some guidance on when to use bulk vs single execution. However, it doesn't explain when to use this tool over alternatives like elevenlabs_delete_sample or what distinguishes PVC voices, nor does it provide exclusions. The context is thin.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations indicate destructiveHint=false, but the description says 'Delete Sample' which implies destruction. This is a potential contradiction: the description suggests a destructive action while annotations say it's not destructive. Additionally, no details about irreversibility, permissions, or side effects are provided, and the description doesn't add context beyond the name.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise with two sentences, front-loading the core purpose. The bulk support note is useful and adds value without excessive length. It earns its place, though it could be slightly more structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 5 parameters, no output schema, and no annotations beyond basic hints, the description is incomplete. It doesn't explain return values, error conditions, or the exact semantics of bulk vs single deletion. The description is adequate for a simple delete but lacks depth for a tool with multiple parameters and bulk capabilities.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It mentions voice_id and sample_id implicitly via 'by its ID' and bulk support via voice_ids and sample_ids, but it doesn't explain the relationship between these parameters (e.g., whether voice_id is required for bulk, or if sample_id alone suffices). The description adds minimal value over the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool deletes a sample by its ID, which is a specific verb+resource. It distinguishes from siblings like elevenlabs_delete_voice or elevenlabs_delete_pvc_voice_sample by focusing on 'sample' and mentioning bulk support, though it doesn't explicitly differentiate from other delete tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for deleting samples and mentions bulk support, but it doesn't provide explicit when-to-use vs alternatives or exclusions. It doesn't clarify when to use this over elevenlabs_delete_pvc_voice_sample or other delete tools, leaving the agent to infer from the name.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotation Contradiction: the description says 'Delete', which is inherently destructive, while annotations declare destructiveHint=false. Additionally, the description does not disclose irreversibility, permission requirements, or side effects, leaving important behavioral details unaddressed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and front-loaded, with the main action stated immediately. The bulk support sentence adds valuable information without padding. The first sentence is somewhat redundant with the tool name, but overall it is appropriately concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 5 parameters, no output schema, and sparse annotations, yet the description only covers the core delete action and bulk support. It omits details about account scoping, required parameter relationships, irreversibility, and potential permission prerequisites, leaving significant contextual gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With schema description coverage at 0%, the description carries the burden of explaining parameters. It only clarifies that the plural fields service_account_user_ids and api_key_ids support bulk execution, but it leaves the required singular parameters and the 'account' field semantically unexplained.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Delete') and the resource ('an existing API key for a service account'), making the tool's purpose unambiguous. It also distinguishes itself from related sibling tools like create/edit/get service account API key tools by explicitly focusing on deletion.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description conveys when to use the tool via the deletion semantics and mentions bulk execution support, but it does not explicitly explain when not to use it or provide alternative tool recommendations. Usage context is implied rather than fully specified.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description states 'Delete Speech Engine' while annotations declare destructiveHint: false. This is a direct contradiction—deleting a resource is inherently destructive. The description also fails to disclose any side effects, irreversibility, or permission requirements beyond what the annotations (which are contradictory) imply. Per rules, a contradiction yields a score of 1.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise: two sentences effectively communicate the core action and bulk capability. No redundant information or filler. Every word earns its place, making it highly efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a delete operation with no output schema and no annotations, the description should disclose irreversible effects, required permissions, and the difference between single and bulk deletion. It only mentions bulk support without clarifying the single-ID path or any resulting side effects. The annotation contradiction further undermines completeness. This is insufficient for a mutation tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It explains that speech_engine_ids enables batched execution, adding meaning to that parameter. However, it does not clarify the relationship between speech_engine_id (required) and speech_engine_ids (optional) — e.g., whether both can be provided, or if speech_engine_ids overrides the single ID. The required parameter speech_engine_id is left unexplained. Given the low coverage and partial compensation, a score of 2 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Delete Speech Engine' — a specific verb and resource. It distinguishes itself from sibling delete tools like elevenlabs_delete_voice or elevenlabs_delete_project by naming the exact resource type. The additional mention of bulk support adds purpose nuance without ambiguity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description mentions bulk support via speech_engine_ids, implying a use case for batch deletion, but provides no guidance on when to use this tool versus alternatives (e.g., other delete endpoints). It does not state prerequisites, exclusions, or conditions under which single vs. batch should be used. Some context is present, but it lacks explicit when/when-not guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description states the tool deletes items, which is a destructive operation, but the annotations declare destructiveHint: false, creating a direct contradiction. Additionally, the description provides no extra behavioral context (e.g., permanence, permission requirements) beyond the delete action itself, and annotations are insufficient to clarify safety.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two short, focused sentences: one for the primary purpose and one for bulk support. No redundant wording or unnecessary detail, making it highly efficient and easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (3 params, 1 required, no output schema), the description covers the essentials but misses the account parameter and fails to address the contradiction with destructive annotations or any side effects. It is adequate for an agent but not fully complete due to these gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description carries the burden. It explains history_item_id as the ID to delete by and history_item_ids for bulk execution, which adds meaning. However, it omits the 'account' parameter and offers no guidance on formatting or relationships between parameters, leaving partial compensation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool deletes a history item by ID, and explicitly mentions bulk execution via history_item_ids, which distinguishes it from sibling delete tools like elevenlabs_delete_audio_isolation_history_item. It is not a tautology and provides specific resource and action.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use (when you have a history item ID to delete) but does not explicitly contrast with alternatives, such as noting that for audio isolation history one should use a different tool. It offers no exclusionary guidance or context beyond the core operation.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description explicitly says 'Delete' (a destructive action) while the annotations set destructiveHint to false. This is a direct contradiction, making the description untrustworthy for behavioral expectations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and front-loaded, but the first sentence 'Delete Transcript By Id' is redundant with the tool name. The second sentence adds value, and the bulk note is useful.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description lacks essential context for a delete operation: no mention of return value (since no output schema), no indication of permanence or permissions, and the 'account' parameter is unexplained.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description explains transcription_id and transcription_ids, but completely ignores the 'account' parameter. With 0% schema coverage, it should describe all parameters to compensate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool deletes a transcript by its ID and mentions bulk support via transcription_ids, distinguishing it from other delete tools that target different resources.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The context is clear: use this tool when you have a transcript ID to delete. No explicit alternatives or exclusions are needed given the specificity of the resource.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description discloses the bulk execution capability, which is a behavioral trait beyond the schema. However, it doesn't mention important behaviors like irreversibility of deletion, potential cascading effects on associated resources, or permission requirements. The annotations already indicate destructiveHint=false and readOnlyHint=false, so the description should provide more context on the destructive nature, but it only adds the bulk support note.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise: two short sentences. It front-loads the primary action and adds a key feature (bulk support). No wasted words, but it could benefit from more useful information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with zero schema description coverage and no output schema, the description is inadequate. It provides the basic purpose but fails to explain the parameters, prerequisites, effects on related resources, or expected behavior on failure. The tool is relatively simple but the description should at least clarify the difference between voice_id and voice_ids usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description does not explain any of the three parameters. It mentions 'voice_id' in the text but doesn't elaborate on the 'account' parameter or 'voice_ids' array semantics beyond the mention of bulk support. The description should compensate for the lack of schema descriptions by explaining parameters, but it does not.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action: 'Deletes a voice by its ID.' It identifies the resource (voice) and the operation (delete). It distinguishes from siblings by being specific to deleting a voice, though it could differentiate from other delete* tools that target different resources.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage in the context of voice management, but it doesn't provide explicit guidance on when to use this tool versus alternatives like elevenlabs_delete_sample or elevenlabs_delete_finetune. It mentions bulk support but doesn't elaborate on when batch deletion is appropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description says 'Delete', implying irreversible destructive behavior, but annotations declare destructiveHint=false. This is a direct contradiction. The description does not add any other behavioral context (e.g., irreversibility, permission requirements, side effects) that would compensate for the missing annotation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely short but repeats the same information twice ('Delete Workspace Webhook' and 'Delete the specified workspace webhook'). The bulk support note is useful but the duplication wastes space. It could be condensed to a single clear sentence.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

This is a delete operation with no output schema, no parameter explanations, and no behavioral warnings. It lacks critical context such as whether deletion is permanent, if any confirmation or cascade effects occur, or what the response contains. For a destructive operation, this is inadequate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description only mentions 'webhook_ids' for batch support but fails to explain the required 'webhook_id' parameter or the 'account' parameter. With 0% schema description coverage, the description does nothing to clarify parameter semantics beyond what the schema property names already imply. It adds no meaning about formats, defaults, or relationships.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action (delete) and resource (workspace webhook). It also mentions bulk support, which adds a distinguishing feature. However, the first two sentences are nearly identical ('Delete Workspace Webhook' vs 'Delete the specified workspace webhook'), which is slightly redundant but not confusing.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternative deletion tools (e.g., other elevenlabs_delete_* tools) or any prerequisites like required permissions or context. The only hint is the resource name, which implies usage for workspace webhooks, but there is no explicit when/when-not guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations include readOnlyHint=false and destructiveHint=false, but no idempotentHint (false). The description does not contradict these. It adds a critical behavioral note: 'Requires the query parameter api_key_name=self as an explicit confirmation', which implies a safeguard. However, it does not elaborate on consequences (e.g., irreversible? immediate effect? impact on existing requests?). Given annotations are sparse, description could do more to clarify what 'disable' entails.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, concise and to the point. No wasted words. The critical requirement is highlighted. Excellent structure.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is a mutating action (disable) with no output schema and incomplete parameter semantics. It does not explain what happens after disabling (e.g., response, further authentication needs, reversibility). The description does not mention any prerequisites (e.g., being authenticated) or edge cases. Given the complexity of API key management, this is under-specified.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so description must explain parameters. It only mentions the required parameter `api_key_name` and its specific value 'self', but does not explain the `account` parameter. The parameter semantics for `account` are entirely absent, leaving the agent guessing its purpose. For a 2-parameter tool with zero coverage, this is insufficient.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's action: 'Disable Api Key' with specific reference to the API key used for the request. It distinguishes from siblings (e.g., delete_service_account_api_key, edit_service_account_api_key) by indicating this disables rather than deletes or edits. However, it could be more explicit that this is a singular action on the current key.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives. It states a requirement ('Requires the query parameter api_key_name=self') but does not explain scenarios where disabling is appropriate, or alternatives like deletion or editing. Sibling tools with similar purposes are not mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations include readOnlyHint=false, destructiveHint=false, so they don't fully cover safety profile. Description adds that multiple items are zipped, which is helpful behavior. However, it doesn't disclose other behaviors like output format handling or potential limits, but no contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, front-loaded with purpose, and each sentence adds value: first states action, second and third explain behavior based on input. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a download tool with no output schema and 0% schema coverage, the description covers the main behavior but omits details about output format parameter, account parameter, and potential errors or size limits. However, the tool is relatively simple and the core behavior is well explained.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so description must compensate. The description explains 'history_item_ids' semantics (single vs. multiple => audio vs. zip). However, 'output_format' and 'account' parameters are not explained beyond schema type definitions. The description adds meaning for the primary parameter but leaves the other two undocumented.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states verb ('Download') and resource ('History Items'), and distinguishes between single vs. multiple items behavior. It is specific enough to differentiate from sibling tools like delete_speech_history_item or get_audio_full_from_speech_history_item.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use (when needing to download history items) and distinguishes between single vs. multiple item behavior. It doesn't explicitly mention alternatives or when not to use, but the distinction between single and multiple IDs provides useful context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations include readOnlyHint=false, destructiveHint=false, idempotentHint=false, openWorldHint=false. The description adds that the action is queued and starts once the project is ready, which is useful behavioral context beyond annotations. It also mentions bulk support. However, it doesn't disclose potential side effects, rate limits, or what happens on failure. Given annotations already indicate it's not read-only and not destructive, the description adds some value but not extensive transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very concise: two sentences. It front-loads the primary purpose and then adds the bulk support note. No wasted words. However, it could be slightly more structured by separating the bulk support into a clear note, but it's already quite efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 6 parameters, 0% schema description coverage, no output schema, and no enums, the description is insufficient. It doesn't explain what a 'language target' is, what 'translations' or 'voice_settings' do, or what the expected outcome is. The bulk support is mentioned but not detailed. The description is too sparse for the complexity of the tool, especially with no other structured information to rely on.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate for parameter meaning. The description only mentions project_ids for bulk support, but doesn't explain the meaning of project_id, target_language, translations, voice_settings, or account. The schema provides types but no descriptions. The description adds minimal value for parameters, leaving the agent to guess what 'translations' or 'voice_settings' mean in this context. This is a significant gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Create Dubbing Language Target' and 'Queue a language target for a project'. It identifies the resource (dubbing language target) and the action (create/queue). It distinguishes from siblings like elevenlabs_dubbing_language_delete/get/list by focusing on creation. However, it doesn't explicitly contrast with those siblings, so it's not a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description mentions 'starts once the project is ready', which gives some context on when the queued action takes effect. It also mentions bulk support via project_ids. However, it doesn't explicitly state when to use this tool vs alternatives, nor does it provide exclusions or prerequisites beyond the implicit 'project ready' condition. The guidance is implied but not fully explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description says 'Delete,' which implies a destructive action, but the annotations set destructiveHint to false, creating a direct contradiction. Additionally, the description does not disclose consequences like irreversibility, permission requirements, or side effects. Since the description contradicts the annotation, the score is 1.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences with no extraneous information. It front-loads the purpose and adds a concise note about bulk support. Every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a destructive operation with no annotations (except false hints) and no output schema, the description is too sparse. It omits crucial context such as irretrievability, permission prerequisites, or how batch mode differs from single mode. The lack of behavioral transparency and usage guidance makes it incomplete for safe invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds meaning to some parameters by mentioning bulk support with project_ids and language_ids for batched execution. This clarifies the purpose of the array parameters. However, it does not explain the account parameter or the relationship between project_id/language_id and their list counterparts. Given 0% schema coverage, it partially compensates but leaves gaps.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action: 'Delete Dubbing Language Target' and 'Delete a language target,' which is specific about the resource and operation. It distinguishes from siblings like dubbing_language_create or list, though it doesn't contrast with overlapping delete tools like dubbing_project_delete. The purpose is unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this tool versus alternatives such as delete_dubbing or dubbing_project_delete. The mention of bulk support is a parameter behavior hint, not a usage guideline. No prerequisites or context for when to choose batch vs single deletion are provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already mark the tool as readOnly, idempotent, and non-destructive. The description adds useful batch-support behavior and indicates 'full detail' output scope, but doesn't describe return shape, pagination, or any other operational caveats. No annotation contradiction is present.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two short, front-loaded sentences with zero filler. 'Bulk support' is a meaningful addition and the structure makes the core purpose immediately visible.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a five-parameter getter with no output schema, the description covers the core purpose and batch mode, and annotations handle the safety profile. It remains incomplete around the account parameter, singular-vs-array usage, and expected response shape.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description must compensate, and it does partially by explaining that project_ids and language_ids enable batched execution. However, it leaves the account parameter unexplained and doesn't clarify the relationship between singular project_id/language_id and their plural array counterparts.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Get Dubbing Language Target' and 'Full language-target detail', identifying a read operation for a specific dubbing language resource. It distinguishes itself from sibling list/create/delete tools through the verb and detail-level phrasing, though it doesn't explicitly name those alternatives.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear context: fetch full language-target detail, with optional bulk execution via project_ids and language_ids. It doesn't explicitly explain when not to use this tool or compare it with elevenlabs_dubbing_language_list, so it stops short of full when/when-not guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, covering safety. The description adds behavioral details beyond annotations: cursor-paginated results and bulk support via project_ids. This transparently discloses pagination and batching behavior, though it does not describe response structure or rate limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise: two sentences that immediately convey the primary purpose, pagination, and bulk capability. No fluff or redundant filler; it is appropriately sized for a list operation.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

While the description covers the core purpose and bulk/pagination, it lacks details about response contents (no output schema) and does not clarify optional parameters like status or account. Given the tool's moderate complexity (6 params, no schema descriptions), more context would be beneficial, but it is not entirely deficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It only explicitly mentions project_ids for bulk and implicitly references pagination via 'cursor-paginated'. Other parameters (cursor, status, account, page_size, project_id) are unexplained, leaving the agent to infer their purpose without guidance.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the operation: 'List Dubbing Language Targets' and refines it to 'List a project's language targets (cursor-paginated)'. It distinguishes from sibling tools like elevenlabs_dubbing_language_get (which presumably retrieves a single target) by emphasizing the list and pagination behavior.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description mentions 'Bulk support: accepts project_ids for batched execution', indicating when to use this tool for multiple projects, but it does not explicitly state when to use it over alternatives like twelve_labs_dubbing_language_get or create/delete. No explicit exclusions or alternative tool references are provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description discloses a meaningful behavioral trait (cascading deletion of language targets) and bulk support, which goes beyond the sparse annotations. However, annotations declare destructiveHint: false even though deletion is inherently destructive, and the description does not address irreversibility, permissions, or batch execution consequences. It adds some value but leaves ambiguity regarding destructive semantics.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and front-loaded with the main action, followed by a specific scope clarification and a bulk-support note. Every sentence earns its place, though the bulk support line could have included more parameter detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a delete operation with no output schema, no annotations beyond hints, and 0% schema coverage, the description should explain return behavior, error cases, and idempotency. It covers the core deletion and bulk aspect but is incomplete for an agent to confidently invoke it, especially given the destructive nature and sibling overlap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With schema description coverage at 0% and no parameter-level descriptions, the description must compensate, but it only mentions 'project_ids' for bulk support and implies 'project_id' via the delete action. The 'account' parameter is entirely unexplained, and the distinction between project_id and project_ids is not clarified beyond the bulk note.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('Delete') and resource ('Dubbing Project'), clarifying it deletes a project and its language targets. It partially distinguishes from siblings like elevenlabs_delete_project by focusing on dubbing projects, though it shares the same generic delete action with many siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use it—for deleting dubbing projects and their language targets—but does not explicitly contrast it with alternative delete tools like elevenlabs_delete_project or elevenlabs_delete_dubbing. The bulk support note adds a usage context, but no explicit when-not or alternative guidance is provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds useful behavioral context beyond annotations by promising full project detail including language target IDs and by noting bulk execution via project_ids. It does not cover response format details, but annotations lower the bar.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is brief and front-loaded: first the core purpose, then the key return details, then bulk behavior. Every sentence earns its place with no redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and a low-complexity 3-parameter tool, the description provides a workable overview but is incomplete. It omits the meaning of 'account' and does not clarify how project_ids interacts with project_id or what the bulk response shape looks like.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate for parameter meaning. It only clarifies that project_ids enables batched execution; it does not explain the 'account' parameter or the relationship/usage of project_id versus project_ids. This leaves significant semantic gaps.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb+resource pair ('Get Dubbing Project') and adds a clear scope ('Full project detail, including its language target ids'). It is distinct from sibling tools like list/delete operations, making the purpose immediately obvious.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The intended use is clear: retrieve a dubbing project's full details, with optional batch support via project_ids. It does not explicitly name alternatives or exclusions, but the context is sufficient for an agent to know when this getter is appropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description doesn't need to state safety. It adds the key behavioral trait of cursor-paginated listing, which is useful and not in annotations. However, it does not disclose any rate limiting or authentication requirements beyond what annotations imply.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise, consisting of two short sentences. It front-loads the core purpose and adds the pagination detail without any waste. Every word earns its place, and it is appropriately sized for a listing tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a listing tool with 5 params and no output schema, the description provides the basic scope and pagination hint but lacks parameter details and any mention of response format. Given that the schema is sparse (no descriptions), the description could do more to flesh out the params. It's adequate but not complete, especially since pagination is only hinted at.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description carries the burden. The description only mentions 'cursor-paginated', which explains the cursor parameter's role. Other parameters (status, account, page_size, sort_direction) are left undocumented. The description could enumerate these parameters and their meanings to compensate for the schema gap, but it doesn't.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that the tool lists the workspace's dubbing projects, with a specific verb ('List') and resource ('Dubbing Projects'). It is distinguished from siblings like 'elevenlabs_list_dubs' (which likely lists all dubs) and 'elevenlabs_dubbing_project_get' (which fetches a single project) by the explicit scope 'workspace's', though it could explicitly mention filtering by status or pagination.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies this is for listing dubbing projects, but it does not explicitly state when to use this over alternatives like 'elevenlabs_list_dubs' or 'elevenlabs_dubbing_project_get'. It lacks explicit exclusions or when-not-to-use guidance. Given the sibling names, some differentiation is implied by resource focus, but not explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds value by explaining bulk execution behavior and the content structure ('source segments with their translations'), which goes beyond the structured annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three short sentences with no filler. The main purpose is front-loaded, the resource is defined, and the bulk behavior is stated efficiently. Every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, but the description explains the return content ('source segments with their translations') and mentions batch support. It does not explicitly discuss pagination or response shape for batch calls, but for a read-only retrieval tool this is reasonably complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It adds meaning to `project_ids` and `language_ids` by identifying them as batch parameters, but it does not describe `account`, `project_id`, or `language_id` beyond what their names imply. This is partial compensation, not complete.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Get Dubbing Target Transcript' and defines the resource as 'A language target's transcript: source segments with their translations.' This distinguishes it from the sibling `elevenlabs_dubbing_transcript_get` by explicitly scoping to the target language transcript rather than the source transcript.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context: this tool is for retrieving a language target's transcript, and it explicitly notes bulk support via `project_ids` and `language_ids`. It does not explicitly name alternatives or exclusions, but the usage context is clear enough for an agent to select it appropriately.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description reveals billing implications ('charged like a generation') and conflict behavior ('Conflicts when the target has no edits to apply are ignored'). But annotations state destructiveHint=false while the description implies destructive replacement ('re-dub', 're-synthesizing') of the target dub, which is a contradiction in behavioral disclosure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is brief and front-loaded with the core purpose ('Regenerate Dubbing Target'), then adds caveats (enterprise-only, billing, conflicts). The two-paragraph structure is scannable and no fluff. Could be slightly more structured with explicit param headings.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (mutating, enterprise-only, billing repercussions, conflict errors, bulk support) and minimal schema descriptions, the description should be richer: it's missing required enterprise prerequisites, auth requirements, the exact failure modes beyond 'no edits', and the relationship to the underlying transcript edits. Merely noting enterprise-only and a conflict case is insufficient for safe and correct use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% (all 3 params undocumented). Description partially compensates by explaining that project_ids and language_ids support bulk executionags, but it never explains their individual meaning, types, or how single vs. bulk modes are determined, so agents lack critical parameter guidance.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action (

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides limited usage context: 'Enterprise only' and 'Bulk support' with project_ids/language_ids, plus a conflict condition (no edits → no dispatch/charge). However, it doesn't offer guidance on when to choose this over sibling tools such as update/delete/get transcript, or explain prerequisites for re-dubbing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations exist but all flags are false, providing minimal safety context. The description adds useful behavioral details beyond annotations: 'Enterprise only' indicates an access restriction, and 'Bulk support' reveals batched execution behavior. It does not disclose whether updates overwrite existing translations or any side effects of editing, but the added context is valuable.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two compact sentences. The first sentence front-loads the purpose and constraint ('Enterprise only'), the second adds the bulk execution detail. Every word earns its place with no redundancy or fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 8 parameters, no output schema, and complex bulk/single modes. The description does not explain parameter relationships, response format, error conditions, or how bulk mode interacts with required singular parameters. It also fails to differentiate from a near-identically named sibling, leaving critical gaps for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It names plural parameters (project_ids, language_ids, segment_ids) for bulk support but does not explain the singular required fields (project_id, language_id, segment_id), the 'translation' parameter's meaning, or the relationship between singular and plural forms. This leaves significant ambiguity for agents.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Update' and the resource 'Dubbing Target Transcript Segment', and elaborates with 'Edit a segment's translation for a language target.' This specifies the action and object. However, it does not differentiate between the similarly named sibling tool 'elevenlabs_dubbing_target_transcript_segmen_fa79db', so it lacks explicit sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage through 'Edit a segment's translation for a language target' and the 'Enterprise only' constraint. It mentions bulk support with plural arrays, suggesting when to use bulk execution. However, it offers no explicit guidance on when to use this tool versus alternatives like elevenlabs_dubbing_transcript_segment_update or the other target transcript segment tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations are minimal (readOnlyHint false, idempotentHint false, destructiveHint false). The description adds the behavior of an 'atomic request' and 'bulk support', which go beyond the annotations. However, it does not disclose whether edits overwrite or merge, what happens on partial failure, or other side effects. Given the sparse annotations, this is adequate but not rich.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and front-loaded with the primary purpose. It uses three short paragraphs: title, enterprise constraint, and bulk support note. No redundant or filler sentences. Slightly could be more structured but it is efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 6 parameters with 0% schema description coverage, no output schema, and nested objects, the description should provide more context. It covers atomicity and bulk support but omits details about parameter formats, how the segments map is keyed, usage of 'account', and error handling. This is a complex mutation tool, and the description is insufficient for a smooth agent invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It mentions 'segments' are for translations and that project_ids/language_ids enable batch execution, which adds some meaning. However, it does not explain the structure of the 'segments' object (which is an arbitrary object), the purpose of 'account', or the relationship between single and bulk parameters (project_id vs project_ids, language_id vs language_ids). The description partially bridges the gap but leaves key ambiguities.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Update Dubbing Target Transcript Segments') and the resource (target transcript segments for dubbing). It also specifies the operation is about editing translations for a language target. However, it does not explicitly distinguish from sibling tools like elevenlabs_dubbing_transcript_segments_update or the other target transcript segment tool, so it stops short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description mentions 'Enterprise only' as a usage constraint and notes bulk support via project_ids/language_ids, but it does not explain when to use this tool versus the related segment update tools, nor does it provide any exclusions or alternative suggestions. It gives some context of when it is applicable (enterprise) but lacks explicit when-not-to-use guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate readOnly, idempotent, non-destructive. The description adds that the transcript is returned as editable segments, which is behavioral context about the return format and mutability. No contradictions; adds value beyond annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short but the first sentence 'Get Dubbing Transcript' is a tautology of the tool name. The second sentence adds meaningful info but the structure could be tighter by combining. Still concise, but not maximally efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema, so description must explain return structure. It mentions 'editable segments' but doesn't give details (e.g., segment fields, pagination). It also fails to explain the account parameter and relationship between project_id and project_ids. Missing essential context for a tool with no output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so description must compensate. It explains project_ids for bulk support but doesn't explain project_id or account. project_id is implied by name but not specified, and account is entirely unexplained. Incomplete param guidance.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool gets the dubbing transcript, specifically the project's source transcript as editable segments. It distinguishes from sibling tools like elevenlabs_dubbing_target_transcript_get and segment-level tools, and mentions bulk support. This is a specific verb+resource with clear scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context: retrieving the source transcript and supporting batched execution via project_ids. It doesn't explicitly state when not to use (e.g., for target transcript), but the name plus siblings make the distinction clear. Bulk support is a usage guideline.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate this is a mutating, non-idempotent operation. The description adds useful context with the 'Enterprise only' restriction and bulk execution capability, but it does not disclose side effects, validation behavior, or response characteristics.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded, with no filler. The first line is near-tautological but is immediately clarified by the more specific 'Add a new source segment to the transcript' and the bulk-support note.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For an 8-parameter mutation tool with no output schema and minimal annotations, the description leaves too much unspecified: required parameter semantics, how bulk parameters interact with singular required fields, and expected behavior after adding a segment.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It only explains project_ids and speaker_ids for bulk execution; required parameters like text, start_s, end_s, speaker_id, and project_id remain semantically unexplained.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action: 'Add a new source segment to the transcript.' The phrase 'source segment' distinguishes this from sibling target-transcript and segment-update/delete tools, making the purpose clear.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear usage context: 'Enterprise only' and bulk support via project_ids/speaker_ids. It does not explicitly name alternatives or state when not to use the tool, but the source-vs-target distinction gives adequate situational guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description says 'Delete' and 'Remove,' but annotations declare destructiveHint: false, which is a direct contradiction. It does add 'Enterprise only' and bulk-support context, but the contradiction with annotations makes behavioral transparency severely flawed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded. Both sentences add meaningful information: the first defines the operation and constraint, the second explains bulk execution. No wasted text.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and sparse annotations, the description leaves important details unclear: batch execution combination rules, what a successful deletion returns, reversibility, and behavior when the segment is absent. It is too thin for a destructive enterprise-grade tool with 5 parameters.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate for parameter meaning. It only mentions project_ids and segment_ids for bulk support, leaving ambiguity about when to use these vs the required project_id and segment_id, and the 'account' parameter is completely unexplained.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states a specific verb and resource: 'Remove a source segment from the transcript.' This distinguishes the tool from sibling delete tools like elevenlabs_delete_dubbing and elevenlabs_delete_transcript_by_id, and from transcript segment add/update tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context: it is 'Enterprise only,' targets source transcript segments, and supports batched execution via project_ids and segment_ids. However, it does not explicitly describe when not to use it or name alternative tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations indicate a write operation (readOnlyHint false). The description adds useful context: 'Enterprise only' (access constraint), 'atomic request' (all-or-nothing behavior), and 'bulk support' (batched execution). These go beyond annotations, but it doesn't disclose potential side effects, reversibility, or detailed behavior on failure beyond atomicity.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise with four short sentences, each adding distinct value: purpose, enterprise restriction, core functionality, and bulk support. There is no redundant text, and key information is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (nested segments object, optional project_ids, atomic behavior) and lack of an output schema, the description is incomplete. It does not explain how to construct segments, what fields are editable in detail, error/response behavior, or prerequisites beyond enterprise status. The schema is vague, so more descriptive guidance is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It mentions editing 'text, speaker, or timing' (hinting at segments content) and explains project_ids for bulk execution, but does not explain the 'account' parameter or the structure/format of the 'segments' object. This is inadequate for a 0% coverage parameter set.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it updates dubbing transcript segments, with a specific verb ('Update') and resource. It further specifies editing 'text, speaker, or timing' and distinguishes from the singular sibling tool by emphasizing 'several source segments' and 'atomic request'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It provides context that this tool is for editing multiple segments at once and mentions bulk support via project_ids. However, it does not explicitly contrast with the singular segment update tool or state when not to use it, though the plural naming and bulk hints imply use for multi-segment operations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description aligns with annotations by framing the operation as a mutation ('Update', 'Edit'). It adds useful behavioral context such as the enterprise-only restriction and batched execution support. However, it does not disclose what happens to omitted fields, the meaning of null values, or whether bulk updates are atomic or partial.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and front-loaded: the core action is stated first, then the enterprise restriction, then editable fields, then bulk support. The first sentence is somewhat redundant with the tool name but the overall text is efficient and free of unnecessary detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 10 parameters, no output schema, and no parameter-level schema documentation, the description is too thin. It omits important context such as expected return values, partial-update behavior, null-field handling, and how the bulk parameters interact with the required singular parameters.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must compensate. It identifies the editable fields (text, speaker, timing) and mentions bulk array parameters, but leaves several parameters unexplained, including 'account', the relationship between singular and plural parameters, and null-value semantics. For 10 parameters, this is insufficient.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool updates a dubbing transcript segment and specifies the editable aspects: text, speaker, or timing. The phrase 'source segment' helps differentiate from target-transcript segment siblings, though it does not explicitly identify the closely named 'elevenlabs_dubbing_transcript_segments_update' sibling.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides some usage context: it is enterprise-only, edits source segments, and supports bulk execution via arrays. However, it does not explain when to use this tool versus the plural 'segments_update' sibling or the target-transcript segment tools, leaving the agent without explicit alternative-selection guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already signal that this is not read-only (readOnlyHint=false), and the description adds a useful behavioral trait: bulk execution via project_ids and chapter_ids. However, it does not disclose whether updates are partial or full replacements, what happens to omitted fields, or any side effects beyond annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and front-loaded, but the opening 'Update Chapter. Updates a chapter.' is redundant and wastes words. The bulk-support sentence is concise and useful. Overall, it is compact but contains repetition that reduces efficiency.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema and 0% schema description coverage, the description is too minimal for a tool with 7 parameters including a nested content object. It does not explain return values, update semantics, or how the content blocks should be structured, leaving significant gaps for an agent to resolve.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description carries the burden of explaining parameters. It only adds meaning for chapter_ids and project_ids (batch execution), while leaving name, content, and account semantically unexplained. The complex content object structure is not described at all.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the operation as updating a chapter, with 'Update Chapter. Updates a chapter.' providing a specific verb and resource. It is distinct from sibling tools like add_chapter and delete_chapter_endpoint, though it does not explicitly name alternatives. The redundancy between the first two sentences slightly weakens clarity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The statement 'Bulk support: accepts project_ids, chapter_ids for batched execution' gives a concrete usage feature, implying when batched updates are relevant. However, it does not explicitly state when to prefer this tool over alternatives like elevenlabs_edit_project or provide exclusions for non-bulk use cases.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations indicate readOnlyHint=false, which aligns with the description's 'update' action, so no contradiction. The description adds the bulk support capability, which is useful behavioral context beyond annotations. However, it does not detail side effects like whether partial updates are allowed or if there are constraints on the update process.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is brief and to the point: two sentences that state the purpose and bulk support. It is front-loaded with the core function, but the second sentence could be merged or expanded without issue. No wasted words, but it lacks detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the large parameter count (12) and zero schema description coverage, the description is incomplete. It does not explain which parameters are updatable, how the bulk parameters interact with single parameters, or any constraints. With no output schema, it also fails to indicate return values. It is adequate only for a simple tool but falls short here.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 0%, so the description must compensate, but it only mentions three bulk parameters (project_ids, default_title_voice_ids, default_paragraph_voice_ids) and does not elaborate on the meaning of required parameters like project_id, name, default_title_voice_id, and default_paragraph_voice_id. It provides minimal added value for the 12 parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that it updates a Studio project with parameter values. It names the resource (Studio project) and the action (Update), which distinguishes it from other edit tools like edit_chapter, though it does not explicitly differentiate from those siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for updating Studio projects, but does not provide explicit guidance on when to use this tool versus alternatives like edit_chapter or create_podcast. There is no mention of prerequisites or conditions for use.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations include destructiveHint=false and readOnlyHint=false, so the description must clarify mutation effects. It only says 'Edit PVC voice metadata' without mentioning what fields are updatable, whether existing values are overwritten, or any side effects. The bulk support note hints at batch execution but lacks detail on behavior (e.g., partial failures).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is brief and to the point, with the bulk support note separated. It is compact, but it could be more informative without being verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 7 parameters, 0% schema coverage, no output schema, and no annotations for safety, the description is incomplete. It lacks details on parameter constraints, required vs optional fields, and any side effects of editing. It does not provide enough context for an agent to safely invoke the tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must explain parameters. It only mentions voice_ids for bulk support and voice_id implicitly through the schema. The description does not explain 'labels', 'account', 'language', or 'description' semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states it edits PVC voice metadata, which is a clear verb+resource. However, it does not distinguish from sibling tools like elevenlabs_edit_pvc_voice_sample or elevenlabs_edit_voice_settings. The phrase 'Edit Pvc Voice' is somewhat redundant with the name.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives. It does not mention any prerequisites or scenarios. The bulk support note is a feature, not a usage guideline.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description matches the annotations: readOnlyHint=false and destructiveHint=false, so it is consistent. It adds some behavioral context by specifying what can be changed, but it does not mention side effects, reversibility, permission requirements, or what happens to the sample after editing.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.