SocialGPT

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

With no annotations, the description discloses key behavior: async (returns job_id), adds to analysis library, requires polling for status, and results appear via list_creator_videos. Does not conflict with annotations. Adequately transparent.

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

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

Two efficient sentences, no redundant information. Front-loaded with core action and platforms, followed by essential async workflow details.

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

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

Despite having an output schema (unknown), the description covers the async workflow, how to retrieve results, and the side effect (add to library). Missing details on errors, authentication, or post_limit, but overall complete for an async analysis tool.

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

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

Schema has 3 parameters with 0% description coverage. The description explains platform and username implicitly ('public TikTok, YouTube, or Instagram creator'), but does not mention post_limit or its default. Partially compensates but leaves one parameter undocumented.

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

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

Clearly states the verb 'Analyze', resource 'creator's recent posts', and specifies supported platforms (TikTok, YouTube, Instagram). Distinguishes from siblings like analyze_post by indicating async behavior and integration with list_creator_videos.

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?

Describes the primary use case (analyze a creator's recent posts) and provides workflow instructions: async operation, returns job_id, poll get_analysis_status, results in list_creator_videos. Lacks explicit when-not-to-use or alternative tools.

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

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

Without annotations, the description covers all critical behavioral traits: async operation, immediate return of platform+post_id, analysis duration (30-60s), and the expected pending response. It also explains that the post is added to the library.

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 well-structured with three sentences, each serving a clear purpose: what it does, immediate return, and async behavior. It is slightly verbose but every sentence adds value.

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 async complexity, the description fully explains the workflow. It lacks error handling or rate limits, but the output schema existence mitigates some need. Overall, it provides sufficient context for an agent to use the tool 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?

The only parameter, post_url, is described as accepting TikTok, YouTube, or Instagram post URLs. This adds context beyond the schema (just string type). Though schema coverage is 0%, the description compensates well by specifying the URL type.

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 specifies the verb 'analyze', the resource 'post', and the platforms TikTok, YouTube, Instagram. It distinguishes itself from sibling tools like get_video_analysis by explaining the async workflow.

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

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

The description explicitly tells when to use this tool (to initiate analysis) and what to do next (call get_video_analysis). It explains the async pattern, expected pending response, wait time (~20s), and instructs not to give up.

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 full burden. It does not disclose any behavioral traits such as lack of side effects, required permissions, or output format. 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 very short and concise, but it sacrifices critical information. It is front-loaded but incomplete.

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 presence of many sibling tools and an output schema, the description is incomplete. It does not explain what resources can be fetched or what the output contains.

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

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

Schema description coverage is 0%, and the description does not add any meaning to the 'id' parameter beyond what the schema provides. No context on id format or resource types.

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

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

The description states the tool fetches a single resource by id, but it does not specify what kind of resource. This is too generic to distinguish from sibling tools like get_account, get_creator, etc., which target specific resources.

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

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

No guidance on when to use this tool versus alternatives. The phrase 'Connector-convention entrypoint' is jargon and does not clarify usage context 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?

No annotations exist, so the description carries full burden but only states the basic action. It does not disclose behavioral traits such as read-only nature, required permissions, or error conditions, which are important for safe invocation.

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 with no unnecessary words. Every part contributes to clarity.

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 output schema handles return values and the tool is simple (one parameter, get-by-id), the description is mostly complete. However, it could mention that the account must be connected or indicate potential error conditions.

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

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

With 0% schema description coverage, the description should add meaning. It says 'by id' but does not elaborate on the account_id parameter beyond what the schema already indicates (a string). No formatting, constraints, or source details are provided.

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

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

The description clearly states the tool retrieves a specific account by ID, uses a precise verb ('Get'), and distinguishes it from siblings like 'list_accounts' (which returns all accounts) and 'get_account_metrics' (which returns metrics).

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 notes that IDs come from 'list_accounts', providing a clear usage hint. It implicitly guides when to use this tool (after listing) but does not explicitly exclude alternative scenarios.

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 provided, so description fully shoulders behavioral disclosure. It describes the operation as a read (get), notes parameter limits (window_days up to 365, post_limit ≤100), and implies idempotency. It does not specify return format or pagination, but output schema exists to cover that.

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, two sentences long, and front-loaded with the main action. Every phrase provides essential information without waste.

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 tool complexity (4 params, output schema exists), the description covers all necessary aspects: what it returns, parameter usage, limits, and a reference to a sibling tool. It is sufficient for an agent to use 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 0%, but the description adds meaningful context for all four parameters: platform (optional filter), account_id (optional, referencing list_accounts), post_limit (max 100, default 20), and window_days (default 28, up to 365). This fully compensates for missing schema descriptions.

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

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

The description clearly states the tool retrieves per-platform metrics as a time series, specifying views/engagement. It distinguishes from siblings by mentioning aggregation across accounts and optional filtering by platform and 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 provides clear context on when to use the tool: omit account_id for aggregate, pass a specific ID from list_accounts, and optionally filter by platform. It states defaults and limits for window_days and post_limit, but does not explicitly mention when not to use or compare to siblings.

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?

Discloses that this tracks the creator-ingest job, not a single post's analysis. Describes behavior of related tool get_video_analysis. Without annotations, it sufficiently covers behavioral traits for a status check 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?

Three sentences, front-loaded with purpose, then usage guidance. No extraneous words. Efficient 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?

For a simple tool with one parameter and one closely related sibling, description covers its role and how it differs. Output schema exists, so return values are handled. No 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?

Only parameter is job_id with no schema description. Description only says 'by job_id' without adding format, examples, or constraints. With 0% schema coverage, description fails to compensate.

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

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

Clearly states it checks the status of an analyze_creator or analyze_post creator-backfill job by job_id. Distinguishes from sibling get_video_analysis which tracks a single post's video analysis.

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?

Explicitly tells when to use this tool (check job status) and when not (to know when one post is ready, poll get_video_analysis). Provides clear alternative.

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 provided, so description carries full burden. It discloses the synthesized, user-level, aggregated nature, adding value. However, missing details on authentication, rate limits, or behavior with no content.

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 concise sentences with no unnecessary words. Key information is front-loaded: 'Get the caller's content profile / DNA'.

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 zero parameters and presence of output schema, description fully explains what the tool does. Covers scope (user-level, aggregated) and components (topics, pillars, voice).

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?

No parameters defined, so baseline 4 applies. Description adds no parameter info, which is acceptable as schema coverage is 100%.

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

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

Description clearly states verb 'Get', resource 'content profile / DNA', and specifics (topics, pillars, voice). It also distinguishes from siblings like 'analyze_creator' by emphasizing it's the caller's aggregated profile.

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?

Implies usage for retrieving own content profile, but lacks explicit when-to-use or alternatives. No mention of when not to use or comparison with siblings.

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 fully discloses key behaviors: it does not ingest, only returns creators already in the library, and explicitly states what happens if the creator is not found (404 with a retry instruction).

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 with no wasted words. The first sentence states purpose, the second clarifies scope, the third gives fallback instructions. It is front-loaded and efficient.

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

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

Given the tool's simplicity (2 required params, no annotations, rich output schema), the description covers all needed aspects: purpose, usage, behavior, parameters. No gaps are apparent.

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

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

Schema coverage is 0%, so the description must compensate. It provides an example ('instagram, 'natgeo'') clarifying that platform is a string and username is a handle. However, it does not enumerate all supported platforms, which could be improved.

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 ('Get'), the resource ('public/competitor creator's profile'), and the key parameters ('platform + handle'). It also distinguishes itself from sibling tools by stating it only returns existing creators, not ingesting.

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 guidelines: when to use this tool vs. analyze_creator, the prerequisite (calling analyze_creator first for new creators), and the error behavior (404 with instruction).

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 burden. It discloses the capability to fetch owned and public/analyzed videos, but does not mention required permissions, error handling, 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?

Single sentence that is front-loaded with the core action and resource. 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?

Adequate for basic understanding given the presence of an output schema. However, lacks details on failure scenarios, pagination, or behavioral nuances that would help an agent use it reliably.

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?

Describes 'platform' and 'post_id' implicitly through the phrase 'platform + post id', but does not explain the optional 'include_analysis' parameter or value formats. With 0% schema coverage, more detail would help.

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?

Clearly states the tool retrieves a single video using platform and post ID. The phrase 'owned or public/analyzed' clarifies the scope, distinguishing it from sibling tools that list or search many videos.

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?

Implied usage: for fetching a specific video. But no explicit guidance on when to use versus alternatives like list_videos or search_videos, nor when to avoid it.

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 full burden. It thoroughly discloses the async nature (runs ~30-60s), the expected pending response with 'retry_after_seconds', and the genuine 404 meaning. This exceeds expectations for behavioral 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 moderately long but every sentence adds value. It is front-loaded with the main purpose and then explains behavior. Could be slightly more concise, but overall efficient.

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

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

Given there is an output schema (not shown), return values need not be described. The description covers async handling, error cases, and prerequisites. However, it omits details about parameter constraints, which moderately reduces 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 description coverage is 0%, so the description must compensate. It mentions using platform and post_id from 'analyze_post' but does not describe allowed values for platform, format of post_id, or any validation rules. This is a significant gap.

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

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

The description clearly states the tool retrieves the full analysis including scene breakdown for a video. It specifies the tool is for owned or public/competitor videos, and distinguishes itself from 'analyze_post' which initiates analysis, and 'get_analysis_status' which likely checks status. The verb 'get' and resource 'video analysis' are precise.

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 explicitly tells when to use this tool: after 'analyze_post' returns platform and post_id. It explains how to handle the pending response ('retry_after_seconds') and what a 404 means (call 'analyze_post' first). It does not compare directly to sibling tools, but the usage context is clear.

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

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

No annotations provided, description discloses return structure and smooth connection flow. Could mention any rate limits or max accounts, but overall transparent.

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

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

Three concise sentences: purpose+filter, usage with other tools, post-connection behavior. No wasted words, well front-loaded.

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

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

Simple tool with one optional param and output schema present. Description covers key flow and integration hints, complete for its complexity.

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

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

Schema coverage is 0%, description adds 'optional platform filter' but does not enumerate possible platform values. Partially compensates but lacks specifics for the parameter.

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

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

Description clearly specifies verb 'list', resource 'connected social accounts', and optional filter. It differentiates from siblings like get_account and list_videos.

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

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

Provides guidance on what to do when list is empty and notes automatic appearance on same token. Does not explicitly mention when not to use, but context is clear.

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

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

No annotations are provided, so the description carries the full burden. It implies a read-only operation (listing) but does not explicitly state that it is safe or non-destructive. It mentions a behavioral constraint (only returns ingested creators) but does not discuss permissions, rate limits, or what happens if the creator is not in the library. A score of 3 is appropriate given the lack of annotations and partial 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 two sentences long, with the core action and parameters front-loaded in the first sentence, and the important prerequisite in the second. Every sentence adds value with 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?

The tool has an output schema (not shown), so the description does not need to explain return values. It provides the essential prerequisite (calling analyze_creator first). It does not mention pagination, error handling, or the exact behavior for missing creators, but given the presence of an output schema and the simplicity of the operation, it is largely complete. Score 4.

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

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

Schema description coverage is 0%, so the description must compensate. It explains 'platform' and 'username' implicitly via context, explains 'sort' with examples ('recent' or 'top'), and clarifies 'include_analysis' as 'with analysis inline'. However, 'limit' is not explained beyond its default in the schema. Overall, the description adds significant meaning beyond the raw schema, earning a 4.

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

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

The description clearly states that the tool lists a public/competitor creator's videos by platform and handle. It distinguishes itself from siblings like 'list_videos' (which likely lists all videos) and 'analyze_creator' (which must be called first for new creators).

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 explicitly states the condition for use: only for creators already in the analysis library, and directs the agent to call 'analyze_creator' first for new creators. It also explains sort options and the optional analysis inclusion, providing clear when-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, the description carries full burden for behavioral disclosure. It only mentions the effect of include_analysis, but omits critical details like authentication needs, rate limits, pagination, similarity criteria, or behavior with private videos.

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

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

The description is extremely concise: two sentences that front-load the core purpose and immediately follow with a specific usage tip about a parameter. No unnecessary words.

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

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

Given the tool has 4 parameters with no schema descriptions, no annotations, but an output schema exists, the description is too sparse. It lacks explanation of required identifiers (post_id, platform), the limit parameter's behavior, default values, and error conditions. Essential context for correct invocation is missing.

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

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

Schema description coverage is 0%, requiring the description to compensate. Only include_analysis is explained in terms of its effect; the required parameters post_id and platform, and optional limit receive no description, leaving their semantics to inference from names.

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: 'Find videos similar to a given one', and specifies the scope as 'public/competitor content'. It implies differentiation from sibling tools like search_videos by mentioning similarity, but does not explicitly distinguish them.

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

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

No guidance is provided on when to use this tool versus alternatives such as search_videos or list_creator_videos. There is no mention of prerequisites, limitations, 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?

No annotations provided, so description carries full burden. It discloses filtering, scoping, sorting, and analysis inclusion. Lacks pagination or rate limit info, but output schema may cover return format. Adds value beyond 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?

Single sentence, 21 words, front-loaded with core action. No redundancy; every phrase adds value. 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?

Given 6 parameters with 0 required and output schema present, description covers core functionality well. Missing limit/pagination details, but overall sufficient for agent 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 coverage is 0%, so description must compensate. It explains platform, query, account_id, sort (enum values), include_analysis, but does not mention limit parameter. Covers 5 of 6 parameters effectively.

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 'List the caller's videos' with specific verb and resource. It distinguishes from siblings like search_videos by limiting to caller's own videos, and adds filtering/sorting details.

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

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

Provides context on when to use: to list caller's videos with filters, scope to account_id from list_accounts, sort by recent/top. Does not explicitly state when not to use or compare to siblings like list_creator_videos.

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 full responsibility for behavioral disclosure. It does not state whether the operation is read-only or has side effects, nor does it mention authentication requirements, rate limits, or the scope of 'caller's content'. The description is vague about behavior.

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

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

The description is brief (two sentences), which is concise, but it lacks substance. While brevity is valued, the lack of critical details reduces effectiveness. It could be restructured to be more informative without adding length.

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 three parameters, no schema descriptions, no annotations, and the presence of an output schema, the description is insufficiently complete. It does not explain what the search returns (e.g., list of items, pagination), nor does it clarify the scope of 'caller's content'. Essential details for a search tool are missing.

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

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

With 0% schema description coverage, the description must compensate. It only adds 'optional platform filter' for the platform parameter, but does not explain 'query' or 'limit' beyond their types. The default values are already in the schema, so the description adds minimal value beyond the parameter names.

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 'Search the caller's content' but does not clearly specify what type of content (e.g., videos, posts). It mentions an optional platform filter, but the term 'caller's content' is ambiguous. Sibling tools like 'search_videos' likely have a more specific purpose, and this description does not effectively distinguish from them.

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

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

No explicit guidance on when to use this tool versus alternatives like 'search_videos'. The phrase 'Connector-convention entrypoint' is jargon without explanation. There is no mention of prerequisites or conditions that would inform the agent's 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?

With no annotations, the description bears full responsibility for behavioral disclosure. It only states the basic function, omitting details like what 'analyzed' means, whether it searches transcripts or metadata, or any side effects or limitations.

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

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

The description is very short (one sentence), which is concise but at the cost of omitting critical details. It front-loads the main verb, but the extreme brevity hinders completeness.

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 presence of an output schema, the description need not detail return values, but the lack of parameter descriptions and behavioral context leaves the tool underdefined. Three parameters with zero description or guidance 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?

Schema coverage is 0% and the description adds no information about parameters. The agent only knows names and types from the schema; the description fails to compensate by explaining how query, limit, and platform affect the search.

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

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

The description clearly states it searches the caller's analyzed videos by query, specifying the verb and resource. It avoids tautology and is specific enough to distinguish from sibling tools like list_videos or search, though it lacks detail on the 'analyzed' 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?

No guidance on when to use this tool versus alternatives like list_videos or search. There's no mention of prerequisites, exclusions, or context for when this tool is appropriate, leaving the agent with no explicit direction.

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 of behavioral disclosure. However, it only states 'Return basic info' without detailing what 'basic info' includes (e.g., server name, version, scope list), whether it is idempotent, or if it requires authentication. The description is too vague for a tool with no annotations.

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

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

The description is a single sentence that is front-loaded and contains no unnecessary words. Every part earns its place, 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 low complexity (zero parameters) and the presence of an output schema, the description is somewhat complete but lacks usage guidance and behavioral details. It tells what the tool returns but not when or why to use it. A score of 3 reflects adequate but not comprehensive coverage.

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

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

The tool has no parameters and schema coverage is 100% (trivially). The description adds minimal meaning beyond stating the tool returns server info and scopes. Since there is an output schema, the description does not need to explain return values, but it remains generic. A score of 3 is adequate.

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

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

The description clearly states it returns basic info about the MCP server and its supported scopes. This verb+resource pair is distinct from sibling tools like analyze_creator, fetch, or list_videos, which have different focuses. The purpose is unambiguous.

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

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

No guidance is provided on when to use this tool versus alternatives. For example, there is no mention that this tool should be used first to check server capabilities before making other calls. Given the presence of many sibling tools, explicit usage context would be beneficial.

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 fully discloses the behavior: returns user id and granted scopes, proving auth wiring. It is transparent about the read-only nature, but could explicitly state no side effects.

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-loading the core purpose and output. Every word 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 zero parameters and presence of an output schema, the description is complete. It explains the tool's purpose and what it returns, meeting all contextual needs for a simple introspection tool.

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

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

No parameters exist, so the description correctly adds no parameter details. The schema already covers all (100% coverage), and no additional meaning 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 verb 'Return' and the resource 'authenticated caller' with specific outputs 'user id + granted scopes'. It distinguishes itself from siblings by focusing on authentication identity, which no other tool covers.

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 use for verifying auth wiring, but does not explicitly provide when-to-use or alternatives. It lacks guidance on scenarios where this tool is not appropriate.

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