BulkTranscripts YouTube

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

No annotations are provided, so the description must disclose behaviors. It mentions the cost of 1 credit and the output fields, but doesn't disclose details like rate limits, authentication requirements, or what happens on invalid input.

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 and front-loaded with the core purpose, followed by input formats, cost, and chaining guidance. 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?

For a simple list operation with full schema coverage, the description is adequate but lacks some context like error handling or output structure beyond the basic fields.

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 has 100% description coverage for both parameters, so the description adds no additional parameter semantics beyond what the schema already provides.

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 lists a channel's videos with specific output fields, and explicitly notes it does not fetch transcripts, distinguishing it from sibling tools like get_transcripts.

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?

It specifies when to use this tool (to list videos) and suggests chaining with get_transcripts for bulk extraction, but doesn't explicitly state when not to use alternatives like get_latest_videos or search_channel.

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 free nature (no credit charged) and the data source (RSS feed), which are useful behavioral traits. However, it does not elaborate on potential failure modes, rate limits, or the exact response structure beyond stating publish dates. The description adds some value but is not comprehensive for a tool with zero annotation coverage.

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

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

The description is two sentences, front-loaded with the core purpose, then adds cost and use-case context. Every sentence earns its place with no redundant information. It is 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?

The tool is simple (one parameter, no output schema). The description states it returns newest uploads with publish dates, which is sufficient for an agent to understand the expected result. It does not cover errors or edge cases, but for a straightforward read-only tool the description is largely complete. Minor gaps like response format detail are not 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 coverage is 100% and the schema already describes the channel parameter as 'Channel @handle, URL, or UC… id.' The tool description repeats this essentially verbatim, adding no additional format or usage details. Since the schema carries the full burden, the description does not meaningfully augment it, 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.

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

The description clearly states the action (get a channel's newest uploads) and resource (channel), with a specific limit (up to 15) and source (RSS feed). It is unambiguous, but it does not explicitly distinguish from sibling tools like get_channel_videos, even though the RSS feed and limit imply a narrower scope. Thus it meets the 'specific verb+resource' but lacks explicit sibling differentiation.

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 use cases: 'ideal for monitoring channels, daily recaps, and did they post this week? checks.' This gives context for when to use it. However, it does not state when NOT to use it or name alternative tools. It offers clear context without explicit 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 the full burden. It usefully discloses cost (1 credit), ordering behavior, and accepted playlist formats. However, it claims to list 'every video' while the schema's limit parameter has a default of 100 and a max of 1000, with no clarification about pagination or whether the limit must be raised to see all videos. Return-value shape is also not described.

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 four short sentences, each earning its place: purpose and ordering, input format, cost, and a high-value usage tip. It is front-loaded with the core action and contains no filler or redundant restatements of the title.

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 2-parameter read tool, it covers purpose, input, cost, and use-case. But the unresolved tension between 'every video' and the limit parameter, plus no information about the response format or pagination, leaves meaningful gaps. Given there is no output schema or annotations to fill those gaps, the description alone is not fully 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 description coverage is 100%, so the schema already documents both parameters well. The description's 'playlist URL or bare playlist id' essentially mirrors the schema's 'Playlist URL or id (the list= value)' without adding significant new meaning. The chain-to-transcripts tip is workflow guidance, not parameter semantics.

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: 'List every video in a YouTube playlist,' and adds a distinctive trait (playlist order) that separates it from the sibling channel/search/latest tools. The title reinforces this clearly, and the input-form detail (URL or bare id) leaves no ambiguity about scope.

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

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

It gives clear contextual guidance: playlist order is preserved for courses/series, and it recommends chaining into get_transcripts for bulk extraction. It doesn't explicitly state when not to use it versus siblings like get_channel_videos, but the context is strong enough for an agent to select it appropriately.

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 behavioral burden. It discloses the credit/cost model ('1 credit the first time it is added to this account's library; repeat reads are free'), the cache bypass effect via fresh, and the output-size consequence of include_segments. It does not address failure modes (e.g. no transcript found) or auth requirements, preventing 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?

Four dense, front-loaded sentences with zero filler. The first sentence states the core purpose, the second covers acceptable inputs, the third covers cost/caching, the fourth covers the one parameter that changes output size. Every sentence 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?

For a moderately simple tool (4 params, 100%% schema coverage, no output schema/annotations), the description covers the what, the accepted input formatst, the metadada returned, and the credit/caching model. Missing edge-case details like behavior when a video has no transcript are minor for such a small tool, so it does not quite reach 5.

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 genuine meaning beyond the schema: it explains which URL formats the video parameter accepts, the practical tradeoff of include_segments ('much larger output'), and the caching/cost semantics that clarify the fresh parameter. This extra context pushes it 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?

Uses a specific verb + resource: "Fetch the full transcript of one YouTube (or TikTok) video as clean text with metadata". The singular scope ('one...video') clearly distinguishes it from the sibling get_transcripts (plural), and the metadata list (title, channel, duration, upload date, language) tells the caller exactly what to expect 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?

Provides clear usage context by enumerating the accepted input forms (watch URL, youtu.be link, Shorts URL, or bare 11-character id) and by giving an explicit condition for include_segments ('only when per-line timestamps are needed'). It does not explicitly name sibling alternatives or exclusions (e.g. when to prefer get_transcripts), which keeps it 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?

With no annotations present, the description carries the full burden and does so thoroughly. It discloses immediate cost effects ('new library addition costs 1 credit'), free repeats, per-item error handling ('Videos without captions are reported per-item and do not fail'), and partial failure semantics ('partial=true and an out_of_credits stopped block'). This is an unusually complete account of 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 about five sentences and front-loads the core call shape before covering cost and failure nuances. Every sentence serves a purpose, including credit warnings and workflow for channels or playlists. It is slightly dense — the balance sentence includes multiple clauses — but still efficient for this amount of behavioral detail.

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 no output schema, the description explains per-item failures and partial success enough for an agent to understand batch side effects. It also gives a sensible orchestration path for channel/playlist usage. It could mention the normal per-video transcript structure, but that omission is minor given the strong behavioral focus.

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 repeats the schema's point about 'YouTube URLs or ids' and adds the 20-video limit, but it does not explain the language parameter. No additional meaning is added beyond the structured schema, so a solid baseline score 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 opens with a specific action and scope: 'Fetch transcripts for up to 20 videos in one call.' It clearly names the resource (YouTube transcripts) and the input format (array of URLs or ids). It also implies the plural batch nature, distinguishing it from the singular sibling get_transcript.

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 a clear funnel for channels or playlists: 'first list the videos with get_channel_videos / get_playlist_videos, then batch the ids through this tool.' It also explains what happens without captions and when the balance runs out. However, it never explicitly contrasts with the singular get_transcript tool, so an agent might not know when to choose this tool over that one.

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 credit cost, which is useful, but it does not explicitly state the operation is read-only (though 'search' implies it) or mention pagination/result limits beyond the schema's `limit` field. It does not describe edge cases or error behavior. This is an adequate but minimal disclosure for a simple 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?

Two compact sentences. The primary purpose is front-loaded, followed by a use-case hinteb, then identifier formats and cost. Zero filler, every phrase contributes.

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 search tool, the description is mostly adequate, but it omits what the response looks like (no output schema). An agent would not know whether the result is a list of video titles, URLs, or IDs. Also missing are error conditions (e.g., invalid channel handle). Given the lack of an output schema, this gap is notable.

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?

Schemas cover all 3 parameters at 100%, so the baseline is 3. The description adds one meaningful insight to the `channel` parameter — accepting @handle, channel URL, or UC… id — though this is already stated in the schema's description of the channel field. It adds no other semantic value beyond the schema, so it stays at 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 clearly states the tool's function: searching within a single channel's uploads for videos on a given topic. This immediately distinguishes it from the sibling `get_channel_videos` (which lists the entire archive) and `search_youtube` (global search). Specific verb + resource + 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?

Provides a clear use case: researching a topic within a known channel without sifting through the full archive. This effectively implies when to choose this tool over `get_channel_videos`, but it does not name alternatives or give 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 provided, the description carries the full burden of behavioral disclosure. It discloses a meaningful side effect: 'Costs 1 credit per search.' It also states what the response includes (titles, ids, URLs). It stops short of detailing pagination or result ordering, but for a simple keyword search this is sufficient to prepare an agent.

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 with no wasted words. It front-loads the core action and scope, then provides return information, use cases, and cost. Every clause earns its place; the cost disclosure is especially valuable to surface early.

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 three parameters, no output schema, and no annotations, the description covers the essential invocation context: what to search, what to expect back, and the cost. The only minor gap is that it does not explicitly mention the default type (video) or hint at how results vary by type, though the schema already covers the default.

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 of 3 applies. The description adds the phrase 'set type' which maps to the type parameter, and 'by keyword' clarifies query usage, but these are already evident from the schema. The limit and default behavior are fully documented in the schema, so the description adds no significant semantic value.

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 specific verb and resource ('Search YouTube by keyword') and explicitly enumerates the retrievable object types ('videos, channels, or playlists'). It also names the return fields (titles, ids, URLs), making the tool's function distinct from siblings like get_channel_videos or get_transcript, which have different retrieval logic.

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 application context ('useful for research, discovery, and finding videos to transcribe'), which helps an agent decide when this tool is appropriate. However, it does not explicitly mention alternatives or exclusion conditions, such as reserving get_latest_videos for recency-based needs or get_playlist_videos for playlist-browsing.

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