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

No annotations are provided, so the description carries full burden. It states 'Add a code block to a draft,' implying a write/mutation operation, but doesn't disclose behavioral traits such as whether this requires draft editing permissions, if changes are reversible, potential rate limits, or how it affects the draft's state. This is inadequate for a mutation tool with zero annotation coverage.

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, clear sentence with zero wasted words. It's front-loaded with the core action and resource, making it highly efficient and easy to parse without unnecessary elaboration.

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 mutation tool with 5 parameters, no annotations, and no output schema, the description is insufficient. It lacks context on permissions, side effects, error handling, or return values, leaving significant gaps in understanding how to use the tool effectively in practice.

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 high at 80%, with parameters like 'code' and 'language' well-documented in the schema. The description adds no additional parameter semantics beyond what's in the schema, such as explaining the purpose of 'draft_id' or usage examples. Baseline 3 is appropriate since the schema does most of the work.

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 ('Add') and target resource ('code block to a draft'), making the purpose immediately understandable. However, it doesn't differentiate this from sibling tools like 'substack_append_to_draft' or 'substack_update_draft' that might also modify drafts, missing explicit 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 provides no guidance on when to use this tool versus alternatives. With siblings like 'substack_append_to_draft' and 'substack_update_draft' available, there's no indication of whether this is for specific code formatting, how it integrates with other draft modifications, or any prerequisites 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?

With no annotations provided, the description carries full burden for behavioral disclosure. While 'Add' implies a mutation operation, it doesn't specify whether this requires authentication, what happens on failure (e.g., invalid URL), whether images are embedded or linked, or if there are rate limits. For a write operation with zero annotation coverage, this leaves significant behavioral gaps 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 a single, focused sentence that wastes no words. It front-loads the core action ('Add an image') and target ('to a draft') efficiently. Every word earns its place, making it immediately scannable and understandable without unnecessary elaboration.

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 mutation tool with 4 parameters, no annotations, and no output schema, the description is insufficient. It doesn't cover what the tool returns (success/failure, image ID), error conditions, or how it interacts with draft state. Given the complexity of adding media to a publishing system, more context about behavioral outcomes is needed for the agent to use this effectively.

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 75% (3 of 4 parameters have descriptions), providing good baseline documentation. The description adds no parameter-specific information beyond what's in the schema—it doesn't explain draft_id context, URL format requirements, or caption/alt usage. Since the schema does most of the work, the baseline score of 3 is appropriate despite the description's lack of parameter details.

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 ('Add') and target resource ('an image to a draft'), making the purpose immediately understandable. It distinguishes this from sibling tools like 'substack_append_to_draft' or 'substack_update_draft' by focusing specifically on image addition. However, it doesn't specify whether this adds images to existing content or creates new sections, leaving some ambiguity compared to more detailed 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 provides no guidance on when to use this tool versus alternatives like 'substack_append_to_draft' (which might handle general content) or 'substack_update_draft' (which might modify existing elements). There's no mention of prerequisites (e.g., needing an existing draft), constraints, or typical use cases, leaving the agent to infer usage from the tool name alone.

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?

With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool appends content but doesn't describe what happens to existing draft content, whether this requires specific permissions, if there are rate limits, or what the response looks like. For a mutation tool with zero annotation coverage, this leaves significant behavioral questions unanswered.

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 communicates the core purpose and context without any wasted words. It's appropriately sized and front-loaded with the essential 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 mutation tool with 4 parameters and no annotations or output schema, the description is minimally adequate. It states what the tool does but lacks important contextual information about permissions, side effects, error conditions, and return values. The 100% schema coverage helps with parameter understanding, but behavioral aspects remain underspecified.

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 100%, so the schema already documents all 4 parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema. With complete schema coverage, the baseline score of 3 is appropriate since the description doesn't compensate for any gaps (there are none).

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 ('Append content') and target resource ('to an existing draft'), with the parenthetical '(for live blogging)' providing helpful context about the primary use case. However, it doesn't explicitly differentiate from sibling tools like 'substack_update_draft' or 'substack_post_note', which could also modify draft content.

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 ('for live blogging') but doesn't provide explicit guidance on when to use this tool versus alternatives like 'substack_update_draft' (which might replace rather than append) or 'substack_post_note' (which might create separate content). No when-not-to-use guidance or prerequisites are 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?

With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool creates a draft, implying a write operation, but doesn't mention authentication requirements, whether the draft is saved automatically, if there are rate limits, or what happens on success/failure. This leaves significant gaps for a mutation tool.

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, clear sentence with zero wasted words. It's front-loaded with the core purpose and appropriately sized for a straightforward creation tool, 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 mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., draft ID, success status), error conditions, or behavioral nuances like whether the draft is published or saved privately. This leaves the agent with insufficient context for reliable 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 100%, so the schema fully documents all parameters. The description adds no additional parameter information beyond what's in the schema (e.g., no examples, format details, or constraints). This meets the baseline for high schema coverage but doesn't enhance 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 action ('Create') and resource ('new Substack draft post'), making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling tools like 'substack_append_to_draft' or 'substack_update_draft', which also work with drafts, so it doesn't fully distinguish from 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 provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a Substack account), when to choose this over 'substack_update_draft' or 'substack_append_to_draft', or any specific context for creation versus modification 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. 'List all drafts' implies a read-only operation, but it doesn't specify whether this requires authentication, how drafts are ordered, if there's pagination, or what the output format looks like. It lacks details on rate limits, error conditions, or any side effects, leaving significant gaps for a tool that likely interacts with user data.

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 with just three words ('List all drafts'), front-loading the core action and resource without any wasted text. It's appropriately sized for a simple tool, making it easy to scan and understand quickly.

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 annotations and output schema, the description is incomplete. It doesn't explain what 'drafts' entail (e.g., unpublished posts), how results are returned, or any behavioral nuances. For a tool that likely returns user-specific data, more context is needed to ensure proper usage, especially without structured fields to fill the 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?

The input schema has 0 parameters with 100% coverage, so there are no parameters to document. The description doesn't need to add parameter semantics, and it correctly implies no inputs are required. This meets the baseline for tools with no parameters, as the description aligns with the empty 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 'List all drafts' clearly states the verb ('List') and resource ('drafts'), making the tool's purpose immediately understandable. It distinguishes from siblings like 'substack_get_posts' (which lists published posts) and 'substack_create_draft' (which creates drafts), though it doesn't explicitly mention this differentiation. The purpose is specific but could be more precise about 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 provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., authentication), when not to use it, or how it differs from similar tools like 'substack_get_posts' for retrieving published content. Usage is implied by the name but not explicitly stated.

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?

With no annotations provided, the description carries full burden but adds minimal behavioral context. 'List published posts' implies a read-only operation but doesn't disclose traits like pagination, sorting, error handling, or rate limits. It lacks details on what 'published' entails (e.g., date ranges, status) and the return format, making it inadequate for a tool with zero annotation coverage.

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 with 'List published posts'—a single, front-loaded sentence that directly states the purpose without waste. Every word earns its place, making it efficient and easy to parse, though this brevity contributes to gaps in other dimensions.

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 annotations, no output schema, and a simple input schema, the description is incomplete. It doesn't explain return values (e.g., post details, format), behavioral aspects like ordering or pagination, or error conditions. For a tool that likely returns a list of posts, more context is needed to guide an agent effectively, making it minimally adequate but with significant 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?

The input schema has 100% description coverage, with the 'limit' parameter well-documented in the schema. The description adds no parameter semantics beyond what the schema provides, as it doesn't mention the 'limit' parameter or other filtering options. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but doesn't need to heavily.

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 'List published posts' clearly states the verb ('List') and resource ('published posts'), making the purpose immediately understandable. It distinguishes from siblings like 'substack_get_drafts' by specifying 'published' rather than 'drafts'. However, it doesn't specify scope (e.g., all posts vs. filtered) or differentiate from potential other listing tools, keeping it from a perfect 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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., authentication), exclusions (e.g., not for drafts), or comparisons to siblings like 'substack_get_drafts' for unpublished content. Usage is implied by the name but not explicitly stated, leaving gaps for an agent.

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?

With no annotations provided, the description carries full burden but lacks behavioral details. It states the action ('End') but does not disclose effects (e.g., whether the session is saved, deleted, or archived), permissions required, or error conditions. This is a significant gap for a mutation tool with zero annotation coverage.

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, front-loaded sentence with zero waste. It directly conveys the tool's purpose without unnecessary words, 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 moderate complexity (ending a live session with a parameter) and no annotations or output schema, the description is minimally adequate. It states what the tool does but lacks details on behavior, outcomes, or error handling, leaving gaps for an agent to operate effectively.

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 input schema has 100% description coverage, documenting the single parameter 'publish' with its type, default, and purpose. The description does not add parameter details beyond the schema, but with only one parameter and high schema coverage, a baseline of 4 is appropriate as no compensation is needed.

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 specific action ('End') and target resource ('the current live blogging session'), distinguishing it from siblings like 'substack_live_blog_start' (which begins a session) and 'substack_publish' (which publishes content). It uses precise verb+resource phrasing without redundancy.

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 by referencing 'the current live blogging session', suggesting it should be used when a live session is active. However, it does not explicitly state when to use it versus alternatives (e.g., 'substack_publish' for non-live content) or provide exclusions, leaving some ambiguity.

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?

With no annotations provided, the description carries full burden but only states the action without disclosing behavioral traits. It doesn't mention if this requires authentication, has side effects (e.g., creating a public session), rate limits, or what happens after starting (e.g., how to add content). This leaves critical gaps for a tool that likely initiates a mutable state.

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, front-loaded sentence with zero waste—it directly states the tool's purpose without unnecessary words. This is appropriately sized for a simple action, earning full marks for 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?

Given the complexity of starting a live blogging session (likely a stateful operation with siblings like substack_live_blog_end), no annotations, and no output schema, the description is incomplete. It doesn't explain the tool's role in the workflow, expected outcomes, or how it interacts with other tools, 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?

The description adds no parameter semantics beyond what the input schema provides. With 100% schema description coverage, the schema already documents both parameters (title and subtitle) clearly. The baseline score of 3 reflects adequate coverage by the schema, but the description contributes no additional meaning.

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 'Start a live blogging session' clearly states the action (start) and resource (live blogging session), but it's vague about what 'live blogging session' entails compared to other drafting/publishing tools. It doesn't differentiate from siblings like substack_create_draft or substack_post_note, which also involve content 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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a draft or post first), exclusions, or how it relates to siblings like substack_live_blog_end or substack_publish, leaving the agent to infer usage from context alone.

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?

With no annotations provided, the description carries full burden for behavioral disclosure. While 'Post' implies a write operation, it doesn't specify whether this creates a draft or publishes immediately, what permissions are required, whether it's reversible, or what happens on success/failure. The analogy to a tweet is helpful but insufficient for a mutation tool with zero annotation coverage.

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 (6 words) with zero waste. Every word earns its place: 'Post' establishes the action, 'a short note' defines the resource, and '(like a tweet)' provides helpful context through analogy.

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 mutation tool with no annotations and no output schema, the description is incomplete. It doesn't address critical behavioral aspects like publication status, permissions, error conditions, or return values. The analogy to a tweet provides some context but leaves too many operational questions unanswered.

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 100%, so the schema already fully documents both parameters (text and link_url). The description adds no additional parameter information beyond what's in the schema. Baseline 3 is appropriate when the schema does the heavy lifting for parameter documentation.

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 ('Post') and the resource ('a short note'), with the parenthetical 'like a tweet' providing helpful analogy for understanding the format. However, it doesn't explicitly differentiate this tool from its siblings (e.g., substack_create_draft or substack_publish), which would require 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 provides no guidance on when to use this tool versus alternatives. With multiple sibling tools for content creation and publishing (substack_create_draft, substack_publish, substack_append_to_draft), there's no indication of whether this is for immediate publication, draft creation, or how it differs from other posting methods.

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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('Publish') but lacks critical details: it doesn't specify whether this is a destructive operation (e.g., if publishing is irreversible), what permissions are required, or what happens upon success (e.g., draft becomes a post). This leaves significant gaps for a mutation tool.

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, direct sentence with no wasted words, making it highly concise and front-loaded. Every part of the sentence ('Publish a draft to your Substack') contributes essential information, earning its place without 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?

Given the complexity of a publishing operation with no annotations and no output schema, the description is incomplete. It fails to address key contextual aspects like behavioral traits (e.g., irreversibility), expected outcomes, or error handling, which are crucial for an agent to use this tool effectively in a real-world scenario.

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 input schema has 100% description coverage, with clear documentation for both parameters ('draft_id' and 'send_email'). The description adds no additional semantic context beyond what's in the schema, such as explaining what 'draft_id' refers to or the implications of 'send_email'. Thus, it meets the baseline for high schema coverage.

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 ('Publish') and the resource ('a draft to your Substack'), making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling tools like 'substack_post_note' or 'substack_update_draft', which might also involve publishing-related functionality, so it doesn't reach the highest 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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a draft created first), exclusions, or comparisons to siblings like 'substack_post_note' for different publishing scenarios, leaving the agent to infer usage from context alone.

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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states 'Update an existing draft's content,' which implies a mutation operation, but doesn't specify permissions required, whether changes are reversible, rate limits, or what happens to existing content not mentioned (e.g., does 'body' replace all content?). This is inadequate for a mutation tool with zero annotation coverage.

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 directly states the tool's purpose without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse quickly, which is ideal for conciseness in tool descriptions.

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 a mutation tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral traits (e.g., side effects, error handling), usage context compared to siblings, and what the tool returns. This leaves significant gaps for an agent to operate effectively in a multi-tool environment.

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 minimal value beyond the input schema, which has 100% coverage with clear descriptions for all 4 parameters. It implies that 'body' replaces existing content ('replaces existing' is in the schema description), but doesn't provide additional context like formatting requirements or interactions between parameters. Baseline 3 is appropriate when the schema does the heavy lifting.

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') and resource ('existing draft's content'), making the purpose immediately understandable. However, it doesn't differentiate this from sibling tools like 'substack_append_to_draft' or 'substack_create_draft', which would require more specific language about replacing content versus appending or creating new drafts.

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. It doesn't mention prerequisites (e.g., needing an existing draft ID), exclusions (e.g., not for published posts), or comparisons to siblings like 'substack_append_to_draft' for partial updates or 'substack_create_draft' for new drafts, leaving the agent to infer usage context.

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