ProClipper - Bulk Transcripts

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint. The description adds useful behavioral context by stating that it reads account information and credits and that the operation is free, with no contradiction to the 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 two short sentences, front-loads the operation and returned information, and wastes no words. 'Free' is a compact and relevant addition for an account-credit tool.

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 zero-parameter, read-only account tool with rich annotations, the description is complete enough to support correct invocation. It identifies the returned information, and no output schema exists that would require further return-value explanation.

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

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

The tool has zero parameters, so there are no parameter semantics for the description to explain. The empty input schema is fully described by the context, and the description correctly does not invent parameter usage details.

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

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

The description uses a specific verb, 'Read,' and names the exact resources: account information and remaining transcript credits. This clearly distinguishes it from sibling tools focused on transcripts, transcription, and 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?

The intended use is implied by the stated resources, but the description does not explicitly say when to use this tool versus alternatives such as get_transcript or get_video_list. The 'Free' note adds minor usage context but not routing 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?

Annotations already cover safety (readOnly, idempotent, non-destructive), and the description adds genuinely new behavioral facts: the call is free and it is gated on readiness states (ready video / completed job / combinedReady). It does not disclose response shape, size limits, or behavior when the video is not yet ready.

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 short sentences, no filler, with the core action front-loaded and the readiness gate placed after it. 'Free' earns its place as a decision-relevant fact.

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 4 parameters, 25% schema coverage, and no output schema, the description leaves real gaps: the meaning of the format enum and the effect of timestamps are unexplained, and the return value (the entire point of a transcript fetch) is never characterized. The readiness gating is the strongest part; the output-side semantics 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?

Schema description coverage is 25%, so the description must compensate, and it only partly does: it explains videoId ('a video id returned by get_transcription, or all'). Nothing is said about 'format' (what 'ai-ready' or 'vtt' actually produce) or 'timestamps', both of which are undocumented in the schema as well.

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?

Specific verb+resource ('Fetch transcript content') with explicit scope: one ready video or all ready results in a completed job. It hints at the pipeline relationship to get_transcription, but never states how this differs in output from that sibling, so an agent must infer the boundary.

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 concrete preconditions for use: video must be ready, job must be completed, and 'all' requires combinedReady to be true. It also points at get_transcription as the source of the video id. It stops short of naming alternatives or when-not-to-use cases, so it is clear context rather than full routing 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?

Annotations already declare readOnly, idempotent, non-destructive, and open-world behavior, so the safety profile is covered. The description adds useful context beyond annotations: the call is free, polling cadence, terminal states, and the categories of returned data.

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 tight sentences with no wasted language. The return contents, cost, and polling instruction are front-loaded, and the sentence 'Free.' earns its place by clarifying billing behavior.

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

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

For a simple one-parameter polling tool with no output schema, the description is complete enough: it names the return categories, terminal states, polling cadence, and cost. Annotations cover safety, and no additional information is 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?

There is only one parameter, jobId, and schema description coverage is 100%; the schema already states it is the job ID from submit_transcription. The description does not add further syntax or meaning beyond the schema, so baseline 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?

States a specific verb+resource (get transcription job information) and enumerates exactly what it returns: progress, ready video IDs, skipped videos, and remaining credits. This clearly distinguishes it from get_transcript (transcript content retrievals), submit_transcription (job creation), and the video-listing siblings.

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?

Gives clear operational guidance: poll every few seconds until the job is completed, partial, or failed. This tells the agent the intended use pattern and terminal conditions, though it does not explicitly name when to switch to get_transcript or other 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 readOnlyHint and idempotentHint already declared, the description still adds real value: it states the call is free, that polling is the expected interaction pattern, and that no credits are consumed. It does not describe what the returned result contains or what status values may appear.

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 short sentences, front-loaded with the core action, then polling cadence, then the exclusion. Nothing is redundant and every clause carries information.

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

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

There is no output schema, so the description carries the burden of explaining the return value, and 'retrieve its result' is vague — status fields, job states, and any error conditions for a job are undocumented. Combined with the unexplained jobId, an agent knows when to call but not fully what it will get back.

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 single jobId parameter has 0% schema description coverage and the description says nothing about it — no indication that it is a UUID, or that it comes from a prior listing submission. The agent must infer the parameter's origin entirely.

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: checks a video-listing job and retrieves its result. The clause 'Does not submit a new listing' preempts confusion with a submission tool, though it never explicitly contrasts with the sibling list_videos, which the name get_video_list could be mistaken for.

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?

Gives concrete operational guidance — poll every few seconds while the job is pending or processing — and rules out submission/spending credits. It stops short of naming which sibling actually submits the listing job, so the alternative is implied rather than stated.

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?

Adds real cost and lifecycle context the annotations cannot express: 1 transcript credit per successful request even for an empty list, and the pending/processing → poll get_video_list with jobId recovery path. Annotations declare destructiveHint=true and idempotentHint=false; the credit-charging disclosure explains the cost side effect, though the description never addresses repeated calls / non-idempotency directly, which is the remaining 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?

Front-loaded with purpose, then mode choice, then cost and error handling; every sentence carries operational information. It is on the long side (six sentences) but nothing is redundant 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?

For a credit-charging, open-world listing tool with no output schema, it covers mode tradeoffs, scope exclusions, cost, and the async polling path. It does not describe what metadata fields come back or how many results flat mode returns per item, which is the only material omission.

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 67% and maxVideos has no schema description, so the description compensates by tying it to a use case ('a small maxVideos to see its latest Videos-tab uploads'). It reinforces mode semantics (full is slower, missing dates remain null) and the url requirement for full-mode single-video lookups beyond what the schema states.

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

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

States a specific verb and resource ('List video metadata from one YouTube channel or playlist') plus the single-video variant via mode full. It clarifies the boundary against transcription ('Does not transcribe') and names the sibling used for async polling, so an agent can place it among get_transcript/get_video_list without inspecting schemas.

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?

Explicit selection rules: default flat for normal listings, full only for exact upload dates, use a known video URL for a specific-video question, and find the URL in a flat channel listing first if only a title is known. It also gives a concrete usage pattern (channel URL + small maxVideos for latest Videos-tab uploads) and states the Shorts/live tabs exclusion.

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?

Adds substantial context beyond the annotations: credit cost per video (including unavailable captions), refunds on processing failure, and return of a jobId. The annotations already declare destructiveHint=true and idempotentHint=false, so the description's job is to explain the cost/refund model, which it does well. It stops short of stating whether resubmitting the same links double-charges, which would complete the behavioral picture.

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 tight sentences, front-loaded with the action, then the cost model, then the return value and polling guidance. 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 an async, credit-consuming mutation with no output schema, the description covers the essential return contract (jobId) and polling path. It leaves a minor gap on parameter behavior (maxVideos/links credit interaction), so not fully complete but adequate for correct invocation.

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 50%: language and fallbackToOriginal are documented in-schema, but links and maxVideos are not, and the description does not compensate for them. The description adds no parameter-level meaning (e.g., credit implications of maxVideos), so it sits at the baseline for a partially-covered schema.

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

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

States a specific verb and resource ('Start an asynchronous transcription job') and immediately distinguishes itself from the polling sibling get_transcription. An agent can tell exactly what this tool initiates versus what get_transcription does.

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 routes the agent: 'poll get_transcription instead of submitting again.' This names the alternative and the condition (after submission, use the getter) rather than leaving it to inference.

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