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

No annotations are provided, so the description carries the full behavioral burden. "Report" implies a side-effect-free read, and the provider-routing detail (transcripts always use youtube-transcript-plus) adds real context, but there is no explicit confirmation of read-only safety, cost, or failure 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?

Two tight sentences, front-loaded with the primary output (version and provider) and the caveat about transcript tools last. No filler text.

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

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

A zero-parameter diagnostic tool with an output schema; the description explains the meaning of the returned fields (what innertube vs api implies, per-tool backend, transcript exception), which is exactly the context the schema's field names cannot supply.

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 takes zero parameters, so the baseline for this dimension is 4; there are no parameter semantics to clarify and the description rightly spends its space on the return payload instead.

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?

States a specific verb ("Report") and enumerates the exact resources returned: server version, active provider per feature, and per-tool backend. That makes it unmistakably a diagnostic/meta tool versus the content-oriented siblings, though no sibling is named explicitly.

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 only implied — an agent can infer this is for inspecting server/provider configuration — but there is no explicit statement of when to call it (e.g., to debug why a provider behaves a certain way) and no exclusions or alternatives offered.

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 behavioral burden, and it does disclose the return content categories (language codes and names, manual and auto-generated captions), which is meaningful context. It does not discuss permissions, rate limits, or error behavior, but for a simple read-only enumeration that is a minor 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?

Three sentences, each earning its place: purpose, return contents, and workflow ordering. The core purpose is front-loaded and there is no filler.

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

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

An output schema exists, so the description need not enumerate return fields, and it still adds the useful manual-vs-auto distinction. Combined with the workflow guidance and full parameter documentation, an agent has everything needed to call it 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%, and the single 'video' parameter is fully documented in the schema as a URL or video ID. The description adds no format, alias, or validation detail beyond that, so the baseline 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?

States a specific verb (List) and resource (available caption/transcript languages) with the scope of a YouTube video, and explicitly notes it covers both manual and auto-generated captions. This clearly separates it from the sibling get_video_transcript, which fetches content rather than enumerating languages.

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 final sentence gives explicit sequencing guidance: call this first to discover available languages before fetching a transcript, which directly references and routes relative to the sibling get_video_transcript. An agent knows both when to use it and what to do next.

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, and it does disclose meaningful traits: the returned fields (text, author, likes, date), sorting behavior, the error condition when comments are disabled, and the provider dependency. It omits auth/permission needs and rate-limit behavior, 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?

Four compact sentences with no filler, and the core purpose is front-loaded. The trailing YT_PROVIDER note is environmental context of marginal value but does not bloat the definition.

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 a full output schema and 100% parameter coverage, the description need not explain return values, and it still adds the useful error and provider notes. It is essentially complete for a read-only comment fetcher.

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

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

Schema description coverage is 100%, so the schema already documents video, page, sortBy, and maxResults fully. The description's note on 'relevance' vs 'time' duplicates the enum documentation rather than adding new meaning, so the baseline 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?

States a specific verb and resource ('Get YouTube video comments with replies') and clearly differentiates from siblings like get_video_info and get_video_transcript, which retrieve different data about the same video.

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 sorting options and the error case, giving implied context for use, but offers no explicit when-to-use vs. when-not guidance or routing to alternative tools. Siblings cover different resources, so little overlap exists to disambiguate.

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 and does well: it discloses that unknown values come back as null, that results depend on a provider chosen via YT_PROVIDER (pointing to get_server_info), and that failures surface a code such as ACCESS_BLOCKED/VIDEO_UNAVAILABLE/TIMEOUT in both _meta["youtube-mcp/error"] and a [CODE] text prefix. It omits rate-limit, caching, or quota behavior, which keeps it short of a 5.

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?

Front-loaded with the returned fields, then the input contract, then error semantics — a sensible order with no filler. It is dense, but the only slightly expendable material is the redundant enumeration of return fields, which the output schema already covers.

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 single-parameter read tool with an output schema, the description covers input format, null semantics, provider dependency, and error signaling, which is enough to call and interpret it. Remaining gaps (auth/API-key requirement, rate limits, whether ACCESS_BLOCKED is retryable) are minor given an output schema exists.

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% and there is a single parameter, so the baseline is 3. The description's 'YouTube URL or video ID' simply restates the schema's own wording with no added syntax, accepted URL forms, or examples (e.g. youtu.be vs watch?v=).

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?

States a specific verb ('Get') plus resource ('YouTube video metadata') and then enumerates the exact fields returned (title, channel, duration, views, likes, comment count, upload date, tags), which cleanly separates it from get_video_comments, get_video_transcript, and search_youtube. An agent can identify the tool without opening the schema.

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 field enumeration and the 'Input: YouTube URL or video ID' line make the use case clear: fetch metadata for one known video. However, it never explicitly says when-not to use it or names an alternative (e.g. search_youtube for discovery, get_video_comments for engagement detail), so guidance is contextual rather than prescriptive.

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 and does so well: it discloses the return shape (timestamped and plain text versions), the pagination mechanism (startSegment/nextStartSegment), the non-error failure mode (available=false with NO_CAPTIONS or LANGUAGE_UNAVAILABLE), and that access problems surface as errors. Only auth and rate-limit behavior are unstated.

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?

Front-loaded with the core purpose and packed with useful detail in a few dense semicolon-joined clauses. Nothing is wasted, though the single run-on sentence is harder to scan than separated bullets would be.

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

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

For a 4-parameter read tool with an output schema and no annotations, the description covers purpose, language selection, pagination, and both failure modes. An agent has everything needed to call it correctly and interpret the response.

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 largely restates what the schema already documents (lang omission behavior, pagination with startSegment), adding no syntax or format details beyond it.

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?

States a specific verb and resource ('Get YouTube video transcript/captions') plus the distinguishing scope (manual or auto-generated, with timestamps). It also names the sibling get_transcript_languages, so an agent can route between the two without opening either schema.

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?

Explains the selection rule for 'lang' (provide a code, omit for first manual track else first auto-generated) and points to get_transcript_languages for valid codes. It gives clear context but no explicit exclusions against the other siblings (get_video_info, get_video_comments).

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 the full burden and largely meets it: it discloses the 50-result cap, provider dependence via YT_PROVIDER, and importantly that the default innertube provider approximates some options and emits warnings while the api provider applies them exactly. It omits auth requirements and rate limits, but the degradation caveats are the most valuable trait an agent needs here.

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 dense sentences, front-loaded with the core action and return shape before the parameter summary and the provider caveat. The enumeration of return fields (title, channel, views, duration, URL) slightly duplicates the output schema, but overall there is little 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?

An output schema exists, so return-shape explanation is optional, yet the description covers filtering, sorting, provider-dependent fidelity, and warnings, which is ample for a 5-parameter tool. Minor gap: 'Returns up to 50 results' can be read as the default result count when the schema states maxResults defaults to 10.

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

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

Schema description coverage is 100%, so the schema already documents query, sortBy, maxResults, uploadDate, and videoDuration with enum meanings and provider caveats. The description restates the same filter and sort options without adding syntax or format detail beyond the schema, which is the expected 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?

States a specific verb+resource ('Search YouTube videos by query') with the discovery scope made explicit. It is immediately distinguishable from siblings like get_video_info, get_video_comments, and get_video_transcript, which all operate on a known video rather than searching.

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 filtering, sorting, and provider context imply when the tool is useful, but the description never states usage conditions relative to alternatives (e.g. 'use get_video_info once you have a video ID'). Guidance is inferable rather than explicit, and no exclusions are given.

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