Server Quality Checklist

Tool Scores

• search_videosA
  3.6/5.0
  Behavior3/5

  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 states that the tool returns titles, IDs, and URLs, which is useful, but it does not disclose any other behavioral traits such as sorting, pagination, rate limits, or whether results are limited by relevance. This is a minimal but not misleading description.

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

  Conciseness5/5

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

  The description is extremely concise: two short sentences that immediately convey purpose and return values. Every word is functional, with no redundancy or unnecessary content.

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

  Completeness4/5

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

  For a simple two-parameter search tool with no output schema, the description adequately covers the main purpose and return format. However, it lacks guidance on when to use it versus sibling tools, which slightly reduces completeness.

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

  Parameters3/5

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

  The input schema provides full descriptions for both parameters (query and limit), covering 100% of the schema. The description adds no additional parameter-level detail, so the baseline of 3 is appropriate.

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

  Purpose5/5

  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 ('Search') and resource ('YouTube'), and specifies the scope ('videos matching a query'). It implicitly distinguishes from siblings like list_channel_videos and get_transcript, which focus on specific retrieval rather than general search.

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

  Usage Guidelines2/5

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

  No explicit guidance is provided on when to use this tool versus the sibling tools. The description does not mention alternatives, exclusions, or scenarios like 'use list_channel_videos to get videos from a specific channel.' The usage context must be inferred.

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

• list_playlist_videosA
  3.7/5.0
  Behavior2/5

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

  No annotations are provided, so the description must disclose behavioral traits, but it only states the action and input. It omits details like the default limit (5), pagination, error behavior, or return format, leaving the agent with little insight into the tool's runtime behavior.

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

  Conciseness5/5

  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 is concise with no unnecessary words, and every phrase contributes to understanding the tool's purpose.

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

  Completeness3/5

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

  For a simple list tool with two parameters, the description is adequate but incomplete. It does not mention return values (no output schema) or behavioral details, and the absence of annotations increases the burden on the description to provide context, which it only partially fulfills.

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

  Parameters3/5

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

  The input schema provides complete descriptions for both parameters (playlist and limit), so the description adds no additional semantic value beyond what the schema already provides. The phrase 'Accepts a playlist ID or URL' merely restates the schema's parameter description.

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

  Purpose5/5

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

  The description clearly states the action ('List') and resource ('videos in a YouTube playlist'), using a specific verb that distinguishes it from siblings like list_channel_videos. It also mentions accepting a playlist ID or URL, further clarifying its scope.

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

  Usage Guidelines4/5

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

  The description implicitly conveys when to use the tool: when you have a playlist ID or URL and want its videos. It does not explicitly name alternatives or exclusions, but the purpose is clear enough that an agent can infer the appropriate context without ambiguity.

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

• list_channel_videosA
  3.8/5.0
  Behavior3/5

  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 that the tool accepts a channel handle, ID, or URL, which is useful behavioral context. However, it does not mention other behaviors such as result ordering (beyond 'recent'), pagination, rate limits, or error handling. For a read-only listing tool, this is acceptable but not fully transparent.

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

  Conciseness5/5

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

  The description is two sentences long, front-loaded with the core action ('List recent videos'), and every phrase earns its place. It avoids unnecessary detail, making it easy for an agent to quickly parse the tool's purpose.

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

  Completeness4/5

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

  For a simple listing tool with full schema coverage and no output schema, the description is adequately complete. It specifies the action, the resource, and accepted input formats. It could optionally mention the default limit or suggest using sibling tools for playlists, but these are not critical for using the tool correctly.

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

  Parameters3/5

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

  Schema description coverage is 100%: both parameters (channel and limit) are described in the input schema. The description repeats the channel format info already present in the schema and adds no new meaning for the limit parameter. Since the schema already provides full parameter semantics, a baseline score of 3 is appropriate.

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

  Purpose5/5

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

  The description clearly states the verb 'List' and the resource 'recent videos for a YouTube channel', making the tool's function immediately obvious. It also specifies the three accepted input formats (handle, ID, or URL), which helps differentiate it from sibling tools like list_playlist_videos (playlists vs channels) and search_videos (general search vs channel-specific listing).

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

  Usage Guidelines3/5

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

  The description implies usage: if you need recent videos from a specific channel, this is the tool. However, it does not explicitly mention when to use it over alternatives (e.g., list_playlist_videos for playlists, search_videos for broader search) or provide any exclusion criteria. The guidance is not misleading, but it's only implied, not stated.

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

• get_creditsA
  4.2/5.0
  Behavior4/5

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

  With no annotations, the description carries the burden. It discloses a key behavioral trait: 'this call is never billed.' It also clarifies it applies to 'the current API key.' It does not detail response format or error behavior, but for a zero-parameter balance check, this is reasonable.

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

  Conciseness5/5

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

  Two short sentences: the first states the core purpose, the second adds a valuable cost note. No filler or redundancy. Each sentence earns its place.

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

  Completeness4/5

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

  For a simple, zero-parameter tool, the description is sufficient. It states what it does and that it is free. It does not describe the return format or edge cases, but no output schema is provided, and the simplicity of the tool makes that less critical. It is complete enough 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.

  Parameters4/5

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

  The tool has zero parameters, and the schema coverage is 100% (empty schema). The description adds no parameter meaning because none exist. For 0-parameter tools, the baseline is 4, and the description does not need to compensate.

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

  Purpose5/5

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

  The description clearly states the tool's function: checking the remaining TranscriptFetch credit balance. The verb 'check' and resource 'credit balance' are specific, and this tool is distinctly different from sibling tools like get_transcript or search_videos, which fetch video data.

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

  Usage Guidelines3/5

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

  The description implies usage—you would check credits before making billed calls—but does not explicitly state when to use it versus alternatives or any exclusions. The context is clear enough for a simple utility, but it lacks direct guidance on timing or prerequisites.

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

• get_transcriptA
  4.3/5.0
  Behavior5/5

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

  With no annotations, the description discloses important behavioral traits: the result distinguishes between 'captions definitively do not exist' and 'transcribing audio would still work' via the aiFallback object. It also reveals that ai_fallback starts an async job costing 1 credit and taking 1-3 minutes. This goes well beyond a simple 'get transcript' statement and helps the agent anticipate edge cases.

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

  Conciseness4/5

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

  The description is a single dense paragraph that front-loads the purpose and then details formats and fallback behavior. It is slightly redundant with the schema but remains concise for the amount of context it provides.

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

  Completeness4/5

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

  Despite lacking an output schema, the description explains key result fields (captionsUnavailable, available) and the async fallback process, which covers the main edge cases. It does not describe the full transcript structure, but for a two-parameter tool this is reasonable. The absence of annotations is compensated by the description's rich behavioral detail.

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

  Parameters3/5

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

  The input schema already describes both parameters thoroughly (video formats, ai_fallback behavior, cost, timing). The description largely restates this information without adding new parameter-level meaning. Baseline is 3 due to 100% schema coverage, and this description does not elevate it.

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

  Purpose5/5

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

  The description clearly identifies the tool's function ('Fetch the full transcript for a video') and lists accepted input formats (YouTube ID/URL, TikTok, Instagram, X, Facebook, direct media URLs). This distinguishes it from sibling tools like search_videos or list_channel_videos, which focus on discovery rather than content retrieval.

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

  Usage Guidelines4/5

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

  Provides explicit usage guidance for the fallback flow: if no transcript returns and aiFallback.available is true, call the tool again with ai_fallback: true. It does not explicitly compare to alternative tools, but the description makes the primary use case clear and the fallback condition is actionable.

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