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

With no annotations provided, the description shoulders the burden of behavioral disclosure. It explicitly states that media assets are temporary and details the exact deletion triggers: after post publication, after 24 hours if unused, or when the post is deleted. This goes beyond a basic functional description, though it does not cover authorization requirements 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 two sentences, front-loaded with the main purpose and followed by key workflow details and lifecycle behavior. Every sentence contributes necessary information with no wordiness or redundancy, making it highly concise and well-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's simplicity (zero parameters, no output schema), the description is quite complete: it covers purpose, required usage steps (PUT and then use in post), returned fields, and the critical temporary nature of media assets. It does not elaborate on file size/type constraints, but for a tool this straightforward, the description is sufficiently comprehensive.

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 tool has zero parameters, so the baseline is 4 per the rubric. The description adds no parameter-specific details because there are none, and the schema is already complete with an empty object. No gap exists.

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: 'Request a signed upload URL for a media file (image/video).' It specifies the exact action (request) and resource (signed upload URL for media), and distinguishes it from sibling tools like post creation or account management by focusing on media upload specifically.

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 procedural context: it tells the agent to PUT the file to the returned `upload_url` and then use `media_url` in a post. This implies when to use the tool (before publishing media content) but does not explicitly mention exclusions or alternative tools, though none are relevant. This is clear context without 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?

With no annotations provided, the description carries the burden of behavioral disclosure. It does add useful context: the override precedence ('most specific override wins') and the scheduling vs. immediate publishing behavior. However, it does not disclose other behavioral traits such as draft handling, media processing, idempotency, or potential side effects. For a mutation tool of this complexity, this is a moderate but incomplete 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 extremely concise—three sentences—and front-loaded. The first sentence states the core function, and each subsequent sentence adds a distinct piece of guidance (scheduling, overrides, precedence). No filler or redundancy; every word contributes to the tool's usability.

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 high complexity (8 parameters, nested objects) and the absence of an output schema, the description is relatively brief. However, the schema itself is extremely rich with detailed parameter descriptions. The tool description covers the essential decision-making points: schedule vs. immediate, override hierarchy, and multi-account support. It does not explain return values, but since no output schema is defined, that is acceptable. Overall, it is sufficient for an agent to select and invoke the tool correctly in most scenarios.

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?

Although the schema already provides 100% parameter coverage, the description adds meaningful semantics that are not in the schema: 'Omit scheduled_at to post instantly' clarifies the behavior of the scheduled_at parameter, and the description explains the roles of `platform_configurations` and `account_configurations` as override layers. The 'most specific override wins' rule adds precedence semantics that are absent from the schema. This justifies a score above the baseline of 3.

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: create and schedule (or immediately publish) a social media post across one or more accounts. It distinguishes this from sibling tools like pfm_create_media_upload_url or pfm_create_social_account by focusing on the post creation and scheduling aspect. The verb 'create' and resource 'social media post' 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 provides clear situational guidance: omit `scheduled_at` to post instantly versus scheduling, and use `platform_configurations` for per-platform overrides versus `account_configurations` for per-account overrides. However, it does not explicitly state when to prefer this tool over alternatives like pfm_create_post_previews, nor does it mention any exclusions or prerequisites. The guidance is clear for the parameters it covers but not exhaustive.

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 reveals the return format (per-account preview objects) and the placeholder behavior, but it does not explicitly state whether the operation is read-only, requires authentication, or has side effects. Since the tool name begins with 'create', an agent might assume mutation; the description clarifies it is a preview but stops short of confirming non-destructiveness.

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 exactly two sentences: the first states the core action, the second adds the placeholder capability and return format. Every sentence earns its place, with no redundancy or filler. Key information is front-loaded, making it immediately clear what the tool does.

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, nested objects, and no output schema, so the description must provide a mental model. It does so by outlining inputs (caption, media, per-account targets), the placeholder capability, and the return structure. It could elaborate on how account_configurations and platform_configurations override defaults, but the schema descriptions already cover those. Given the moderate complexity, the description is reasonably complete without being exhaustive.

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 a baseline of 3 applies. However, the description adds meaningful semantics beyond the schema by stating that non-connected accounts can be previewed with placeholder IDs, which directly applies to the preview_social_accounts.id parameter. It also mentions that the output includes resolved caption, media, platform, and configuration, clarifying how parameters like account_configurations and platform_configurations influence results. This additional context justifies a score above baseline.

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 'Generate a preview of what a post will look like for each specified account' clearly states the verb (generate), resource (post preview), and scope (per account). It distinguishes itself from siblings like pfm_create_post by explicitly focusing on preview, not publishing. The mention of previewing non-connected accounts via placeholder IDs further sharpens its unique 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 gives clear context for when to use this tool: when you need per-account previews of a post, including for non-connected accounts via placeholders. It does not explicitly name alternatives or exclusions, but the sibling list and the term 'preview' imply it is for pre-publication viewing rather than actual creation. The statement 'You can preview non-connected accounts by specifying a placeholder ID' provides a specific usage scenario.

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 discloses the critical upsert behavior (updates existing account if same platform+user_id), which goes beyond a simple 'create'. It also implies a direct create without an intermediate OAuth step. However, it does not detail what happens to existing fields (merge vs replace) or mention any side effects, so it's not fully transparent but provides meaningful insight.

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 exceptionally concise: two sentences that immediately state the primary action and the key behavioral nuance. It front-loads the most important information ('Create a social account directly') and includes the upsert caveat without unnecessary filler. 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?

Given the tool's complexity (9 parameters, no output schema, no annotations), the description covers the essential purpose, usage context, and core behavioral trait. It lacks explicit return-value information, but for a create/update tool the result is often self-evident. The combination of schema (100% parameter coverage) and description makes it sufficiently complete for an agent to invoke correctly.

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 100%, so the parameters are already well-documented in the schema. The description adds valuable semantic context by highlighting that 'platform' and 'user_id' serve as the unique key for the upsert operation, which is not apparent from the schema alone. This extra meaning earns a score above the baseline of 3.

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 with a specific verb ('Create') and resource ('social account'), and adds the crucial 'upsert by platform + user_id' behavior that distinguishes it from the sibling 'pfm_create_social_account_auth_url' (which handles OAuth flow initiation). It conveys exactly what the tool does in one concise sentence.

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 explicit when-to-use guidance: 'Use this when you have OAuth tokens from your own auth flow.' This clearly differentiates it from the auth-url flow tool, though it does not explicitly name alternatives or state a when-not-to-use scenario. The context is clear enough for an agent to make the right 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?

No annotations are present, so the description carries the full burden. It discloses a notable behavioral limitation (redirect_url_override is not accepted for Quickstart) and explains how permissions affect future behavior. However, it doesn't mention whether generating a URL creates a pending connection or has any side effects, leaving some safety ambiguity.

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 sentences long, front-loaded with the primary action, and every sentence provides actionable information. No fluff or repetition of schema details. The structure is ideal for quick parsing by an AI agent.

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, nested objects, and no output schema, yet the description covers the essential flow and key caveats. While it doesn't mention platform_data requirements (like Bluesky's handle/app_password), the schema already documents these sufficiently. The description is complete enough for the tool's core function, though a bit more about the response format would have helped.

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 100%, so the baseline is 3. The description adds value beyond the schema by clarifying that redirect_url_override is not available with system credentials and by advising to include 'feeds' for later feed access. These details help interpret the parameters correctly, pushing the score above baseline.

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 opens with a specific verb and resource: 'Generate an OAuth URL to connect a user's social media account.' This clearly distinguishes the tool from siblings like pfm_create_social_account, which likely creates an account record directly. It also explicitly describes the OAuth redirect flow, making the tool's function unmistakable.

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 immediate instructions: 'Redirect the user to this URL; they'll be redirected back after auth.' It also gives a usage constraint (Quickstart/system credentials) and a recommendation (include 'feeds'). However, it doesn't explicitly contrast with pfm_create_social_account or state when not to use this tool, so it stops short of full alternative 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?

With no annotations, the description carries the full burden of disclosure. It discloses that a secret is returned and should be stored to verify incoming requests via the 'Post-For-Me-Webhook-Secret' header, which is valuable behavioral context beyond the schema.

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 long, front-loaded with the core purpose, and includes only essential details (secret verification and event list). Every sentence earns its place with no 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 simple schema (2 required params) and no output schema, the description covers the essential points: purpose, return secret, and supported events. It does not explain the full response format or error cases, but for a create webhook 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 coverage is 100% for both parameters, so the baseline is 3. The description adds no additional parameter-specific meaning beyond what the schema already provides; it repeats the event list, which is already in the schema's event_types description.

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 webhook to receive event notifications. It uses a specific verb (create) and resource (webhook), and lists the available event types, making its purpose distinct from sibling tools like update/delete/get webhooks.

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 this tool: to create a webhook for event notifications. It does not explicitly mention exclusions or alternatives, but the purpose is unambiguous and the sibling tools for updating/deleting are implicitly differentiated.

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 but does not mention irreversibility, potential side effects (e.g., related media deletion), required permissions, or error behavior. A delete operation typically warrants a warning about permanence, which is absent.

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 sentence, front-loaded with the action, and contains zero superfluous words. It is highly concise and well-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?

Although the tool is simple (one param, no output schema), the description omits critical context for a delete operation, such as whether deletion is permanent or if there are cascading effects. The lack of any warning or clarification makes it incomplete for safe 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 100%, with the parameter 'id' already documented as 'Post ID to delete'. The description adds no new meaning beyond what the schema provides. Baseline 3 is appropriate when the schema handles 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 uses a specific verb ('Delete') and identifies the resource ('a social post') plus the required identifier ('by its ID'). This clearly distinguishes it from sibling tools like update_post or create_post.

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 a social post. However, it does not explicitly state when to prefer this over alternatives (e.g., update_post) or provide any conditions or exclusions. No alternative tools are mentioned, so guidance is implicit rather than 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?

No annotations are provided, so the description carries the full burden. It only states that a delete occurs, but fails to disclose permanence, required permissions, side effects on associated data, or error behavior. For a destructive operation, this is a significant transparency gap.

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, concise sentence that conveys the action without unnecessary wording. 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?

Given the tool's simplicity (one required parameter, no output schema), the description is mostly complete for its purpose. However, it lacks mention of side effects or irreversibility, which would add context for the agent. The low complexity and full schema coverage prevent this from being a major gap.

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 100% with the 'id' parameter described as 'Webhook ID to delete'. The description adds no new meaning beyond 'by its ID', so it does not enhance understanding of the parameter beyond 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 'Delete a webhook by its ID' uses a specific verb (delete) and resource (webhook) with a clear method (by ID), fully distinguishing it from sibling CRUD tools like pfm_get_webhook or pfm_update_webhook.

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, such as when a webhook should be deleted or how it relates to creating/updating webhooks. No exclusions or prerequisites are stated, leaving the agent without usage 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?

No annotations are provided, so the description carries the full burden. It discloses that auth tokens are removed, the account is marked disconnected, the record is kept, and it can be reconnected by the owner. This is strong behavioral disclosure, though it omits potential edge cases like idempotency or permission requirements.

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 with no redundancy. The first sentence states the action and its immediate effects (removes tokens, marks disconnected), while the second clarifies retention and reconnection. Every word contributes meaning.

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 a single parameter and no output schema, the description covers the essential behavioral outcomes, record retention, and recovery path. It could mention error conditions or idempotency, but overall it 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 coverage is 100% with a clear description for the 'id' parameter. The tool description adds behavioral context (record kept, reconnection) but doesn't provide additional parameter-specific details beyond what the schema already states.

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 the specific verb 'Disconnect' with the resource 'social account', and explicitly distinguishes from deletion by stating the record is kept. This differentiates it clearly from sibling tools like create/update/get social account.

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 clearly implies when to use this tool (to disconnect while retaining the record for potential reconnection). It doesn't explicitly name alternatives or exclusions, but the absence of a delete_social_account sibling and the retention clause provides sufficient 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?

With no annotations, the description carries the full burden of disclosing behavior. It clearly states the scope (every post, including non-Post-for-Me), the permission requirement ('feeds' permission), and the optional analytics via expand. It does not describe error behavior or return structure, but it provides meaningful context beyond the schema.

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 sentences, front-loaded with the purpose and scope, followed by a practical usage tip and prerequisites. Every sentence contributes value, 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?

Given 7 parameters, 100% schema coverage, and no output schema, the description sufficiently covers the tool's core behavior, permission requirement, supported platforms, and the expand option. It leaves pagination and filtering details to the schema, which is acceptable. It could mention return format, but the absence of an output schema makes this less critical.

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 baseline is 3. The description adds a usage example for the expand parameter ('Pass expand=['metrics']'), which reinforces the schema, but does not elaborate on other parameters beyond what the schema already documents. The addition is minor, so a 3 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 uses a specific verb 'Get' and clearly identifies the resource as the social media feed for a connected account, with the scope 'every post made under that account.' It explicitly distinguishes this from sibling tools by noting it includes posts not created through Post for Me, which differentiates pfm_get_account_feed from pfm_get_posts.

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 on when to use this tool (retrieving the full account feed), a prerequisite (requires 'feeds' permission), and a list of supported platforms. It does not explicitly name alternative tools or state when not to use it, but the distinction from Post-for-Me-only posts implies the difference from pfm_get_posts.

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, the description must convey behavioral traits itself. It communicates that this is a read operation for a single post by ID, which is useful. However, it does not disclose any error behavior, authentication requirements, or return format, leaving some gaps.

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 sentence that is front-loaded with the action and resource. It contains zero filler or redundant information, making it 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?

Given the simplicity of the tool (one required parameter, no output schema), the description provides enough context for an agent to understand what it does and when to use it. The only minor omission is a description of the return value, but for a simple getter, this is largely self-evident.

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 already documents the only parameter 'id' with a description ('Post ID'), achieving 100% coverage. The description adds no additional parameter semantics beyond confirming the ID is used to fetch the post, so the baseline of 3 applies.

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 the specific verb 'Get' and clearly identifies the resource as 'a single social post' with the scope 'by its ID'. This distinguishes it from the sibling tool pfm_get_posts, which presumably retrieves multiple posts.

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 phrase 'by its ID' clearly indicates this tool is for retrieving one specific post when the ID is known, providing clear usage context. However, it does not explicitly mention alternatives or when not to use it, hence not 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?

No annotations are provided, so the description carries the full burden. It discloses the response structure (success/failure, errors, platform_data, media), which is useful, but it does not mention behavior for missing IDs, error conditions, or any side effects. The mention of 'errors' adds some transparency but not complete 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 a single, well-structured sentence that front-loads the action and directly lists key response elements. No unnecessary words or repetition, making it concise and easy to scan.

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 get-by-ID tool with one parameter and no output schema, the description effectively covers the main response components (success/failure, errors, platform_data, media). It could mention not-found behavior or auth requirements, but the listed fields provide a useful mental model 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?

The input schema already provides 100% coverage for the single parameter 'id' with description 'Post result ID'. The description adds no additional semantics beyond 'by its ID', so it aligns with the high schema coverage and earns the baseline score.

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 (Get), the resource (a single social post result), and the identifier (by its ID). It distinguishes from sibling 'pfm_get_post_results' by emphasizing 'single' and listing specific return fields, leaving no ambiguity about the tool's 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 when you have a post result ID and need details about it. It does not explicitly mention alternatives or exclusions, such as when to use pfm_get_post_results instead, so the guidance is merely implied rather than 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?

With no annotations, the description carries the full burden. It discloses pagination, OR logic for filters, and the contents of the result (success/failure, errors, platform URL, per-platform data). This adds meaningful context beyond a simple 'get' operation, though it does not cover rate limits or authorization.

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, front-loaded with the main purpose, and every sentence adds information. It is effectively three short sentences with no fluff or repetition.

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 read-only list tool with 5 optional parameters and no output schema, the description explains pagination, filtering, and response contents. However, it does not clarify how filters from different groups combine (e.g., AND vs OR across types), which is a minor gap in completeness.

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 100% and each parameter already has a description. The description adds a brief summary that all filters use OR logic, but this mostly repeats schema details. It does not provide additional parameter-level meaning beyond what the schema already offers.

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 a paginated list of social post results, with a specific verb and resource. It distinguishes itself from the singular sibling pfm_get_post_result by explicitly saying 'list' and describing 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 usage for retrieving multiple post results with filtering, but does not explicitly name alternatives or state when NOT to use it. No comparison to pfm_get_post_result or pfm_get_posts is provided, so the guidance 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It does disclose pagination and the OR-logic behavior for multiple filter values, which is a useful non-obvious trait. However, it omits other behavioral details such as sorting, default return when no filters are applied, or pagination metadata. These gaps prevent a higher score.

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 concise sentences, front-loaded with the core purpose ('Get a paginated list of social posts') followed by succinct filter details. Every word earns its place; there is no fluff or restatement. It is highly efficient and effectively 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's moderate complexity (6 params, no output schema, no annotations), the description provides a solid overview: it names the resource, mentions pagination, and lists all filter categories with OR logic. It does not describe the response shape, but for a list operation this is partially implied. The only notable gap is the absence of any mention of return format or sorting, but overall it is sufficiently complete for an agent to select and invoke correctly.

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 baseline is 3. The description merely summarizes the filter parameters and repeats the OR logic that is already documented in each parameter's schema description. It adds no new semantic meaning beyond what the schema provides, so no bonus 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 'Get a paginated list of social posts' with specific verbs and resource. It distinguishes from sibling tools like pfm_get_post (singular) by specifying 'paginated list' and listing filter dimensions. The purpose is unambiguous and actionable.

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 through the phrase 'Get a paginated list' and the filter options, indicating this tool is for listing/searching posts. However, it does not explicitly state when to use this over alternatives like pfm_get_post (for a single post), nor does it provide exclusions or alternative guidance. The advice is implicit rather than 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 provides no behavioral context beyond the operation itself. It does not disclose what happens if the ID is invalid, whether authentication is required, or the return format. With no annotations, the description carries the full burden and fails to address these aspects.

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 one succinct sentence that immediately states the tool's purpose. It is front-loaded and contains no 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?

For a simple single-resource retrieval, the description covers the basic purpose and parameter, but it lacks details about return values or error handling. Given no output schema and no annotations, a bit more context would improve completeness.

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 fully documents the 'id' parameter with a description and example. The description adds no additional semantic value beyond what the schema already provides, so the baseline of 3 applies.

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 a single social account by ID. It uses a specific verb and resource, and the word 'single' distinguishes it from the sibling tool pfm_get_social_accounts.

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 tool is for retrieving one specific account when you know its ID, but it does not explicitly mention alternatives or when not to use it. The sibling pfm_get_social_accounts exists for listing, yet no direct comparison 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?

No annotations are provided, so the description carries the burden of behavioral disclosure. It adds useful context about pagination and OR logic for filters, but it does not explain return format, default limit, ordering, or whether the 'connected' wording is restrictive despite the status filter allowing disconnected accounts.

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 concise sentences, front-loaded with the main purpose, and every word earns its place. No fluff or 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?

For a moderately complex list tool with 7 parameters and no output schema or annotations, the description covers the essential aspects: pagination, filterable fields, and OR logic. It lacks information about return value structure or default behaviors, but it is sufficiently complete for a straightforward listing 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 100% for all 7 parameters, so the baseline is 3. The description adds the general statement 'All filters use OR logic', which reinforces what is already in each parameter's schema description. It does not add significant new meaning beyond that.

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 a paginated list of connected social accounts', specifying the verb (Get), resource (social accounts), and scope (paginated list). It distinguishes itself from the sibling tool pfm_get_social_account (singular) by implying list semantics.

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 retrieving multiple social accounts with filters, but it does not explicitly mention when to use this tool over the singular pfm_get_social_account or other alternatives. No exclusions or specific scenarios are stated, so usage guidance remains implicit.

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?

No annotations are provided, so the description carries the full burden. It does not disclose any behavioral traits such as return format, error handling, authentication needs, or that it is read-only beyond what the verb 'Get' 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?

A single, front-loaded sentence conveys the essential action and scope with no unnecessary words. It is appropriately concise for a simple getter.

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 one-parameter read operation, the description is adequate but minimal. Since there is no output schema or annotations, the description lacks context on response structure, potential errors, or any additional behavior that might be relevant for the AI 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?

The schema already provides 100% coverage for the single parameter 'id' with a clear description and example format. The tool description adds only 'by its ID', which does not exceed what the schema already communicates.

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 ('Get') and resource ('webhook') and clearly specifies the scope ('single webhook by its ID'). It distinguishes from the plural sibling tool pfm_get_webhooks, which lists all webhooks.

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 wording implies usage when you have a specific webhook ID and need that one webhook. However, it does not explicitly state alternatives or when not to use it, leaving room for interpretation.

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?

No annotations are provided, so the description carries the full burden. It mentions 'paginated list' but that is also evidenced by the limit/offset parameters in the schema. There is no disclosure of authentication needs, rate limits, sorting behavior, or response format, providing minimal behavioral insight beyond the schema.

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 that effectively communicates the core purpose and key capabilities without 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?

Given the tool's simplicity and rich schema with all parameters documented, the description is fairly complete. It covers the list nature and filtering, and with no output schema, the 'list' wording implies the return type. Minor gaps like sorting or default behavior are not critical for this straightforward read 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 100% with detailed parameter descriptions for each filter and pagination parameter. The description does not add any semantics beyond what the schema already provides, so baseline of 3 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 'Get a paginated list of webhooks', which is a specific verb and resource. It distinguishes from sibling tool pfm_get_webhook (singular) by emphasizing a list, and the filtering options are summarized.

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 retrieving multiple webhooks with pagination and filtering. It provides clear context for a list operation, though it does not explicitly name alternatives or exclusions such as using pfm_get_webhook for a single webhook.

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, the description must disclose behavioral traits. It does highlight the critical full-replacement behavior ('all fields are re-set'), but it omits other important aspects like return values, error handling, or whether the update triggers re-publishing to social accounts.

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 that immediately state the purpose, then clarify the key behavior. No word is wasted, and it is front-loaded for quick comprehension.

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 extremely complex schema, no output schema, and no annotations, the description is too thin. It fails to explain return values, prerequisites like the post needing to exist, or side effects. For such a complex mutation tool, this is a significant gap.

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 covers 78% of parameters, and the description adds meaning by confirming the parameter set is exactly the same as create and that all fields are re-set. This helps the agent know that all create parameters apply and are fully overwritten, which is useful beyond the raw 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's function: 'Update an existing social post' with the crucial detail that it 'replaces the entire post definition.' This specific verb+resource pairing distinguishes it from sibling tools like create_post and delete_post.

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—when updating an existing post rather than creating one—and points to the create schema for consistency. However, it does not explicitly mention alternatives or warn against partial updates, so it stops short of 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?

No annotations are provided, so the description is the only source of behavioral information. It does not disclose whether updates are partial or full, whether username and external_id can be updated together, idempotency, error conditions, or any side effects. This is a significant gap 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 that is easy to parse and front-loads the action and resource. It is appropriately concise for a simple update tool, though it lacks depth in other areas.

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 three parameters, no annotations, and no output schema, the description is insufficiently complete. It does not explain expected outcomes, partial update behavior, or any constraints. For a straightforward API, basic info is present, but the lack of behavioral details makes it incomplete.

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 each parameter is already described. The description adds 'username or external_id,' reinforcing the two updateable fields, but does not clarify if both can be supplied simultaneously or if they are mutually exclusive. It meets the baseline but adds little beyond 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 action ('Update') and the resource ('a social account'), and specifies the two fields that can be updated ('username or external_id'). It distinguishes from siblings like create or disconnect, though it doesn't explicitly mention it only updates these fields and not others.

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 vs alternatives such as create_social_account or disconnect_social_account. The description simply states what it does without any context, 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?

With no annotations, the description carries full burden for behavioral disclosure. It mentions the 'and/or' partial-update capability, but does not disclose permissions, idempotency, error conditions, return values, or what 'update' means operationally (e.g., whether missing fields are left unchanged). This is a mutation tool with minimal 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 a single, front-loaded sentence with no redundant or filler content. It conveys the essential purpose and scope efficiently.

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 simple update tool with a comprehensive input schema, but no output schema and no annotations. The description covers the primary function but lacks guidance on partial-update behavior, required permissions, or expected response. It is minimally viable but leaves room for more 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 100%, so the schema already defines id, url, and event_types with descriptions and an enum. The description adds little beyond confirming these are the updatable fields; the 'and/or' phrasing adds slight semantic value about independence of updates, but not enough to exceed the baseline.

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 clear action ('Update') on a specific resource ('a webhook') with the specific updatable aspects ('URL and/or subscribed event types'). This distinguishes it clearly from sibling tools like create_webhook, get_webhook, and delete_webhook.

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 modifying an existing webhook, but provides no explicit guidance on when to use it versus alternatives (e.g., when to use create_webhook instead) nor any exclusions or prerequisites. It's enough to infer the primary use case.

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