youtube_find_in_video

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

With no annotations, the description carries the full burden of behavioral disclosure. It explains the underlying search mechanism (Hybrid RRF with FastEmbed ONNX and BM25) and precisely what is returned: deep-link URLs, relevance scores, chapter context, and spoken quotes. This is transparent about the tool's operation and output. It doesn't mention any side effects or prerequisites, but for a read-only search tool, the disclosed behavior is sufficiently clear.

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, with the core purpose front-loaded in the first sentence, followed by technical details and a usage recommendation. It wastes no words and is easy to scan. It could be slightly more structured (e.g., separating the technical method from the usage note), but it is efficient and appropriately sized.

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 is present (indicated by 'Has output schema: true'), so the description doesn't need to detail return values, but it does list the key output elements (URLs, scores, chapter context, quotes) which helps agents understand what to expect. It lacks explicit mention of error conditions or prerequisites (e.g., transcript availability), but given the tool's simplicity and the schema coverage, it is reasonably complete for an agent 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?

The schema has 100% description coverage, so the baseline is 3. The description adds minimal extra meaning beyond the schema: it rephrases 'query' as 'specific question, topic, or concept' and mentions output types, but it does not elaborate on parameter specifics like language or max_results behavior beyond what the schema already provides. Thus, it meets the baseline without adding substantial 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 clearly states the tool's purpose: pinpoint exact sections and timestamps in a long video for a specific topic. It uses a specific verb (pinpoint), a specific resource (long video), and distinct output details (deep-link URLs, relevance scores, quotes). It also distinguishes itself from siblings like youtube_transcript by explicitly positioning itself as the preferred tool over full transcripts for long 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 description gives concrete usage guidance: it is 'PREFERRED over reading full transcripts for videos longer than 10 minutes.' This implies when to use it (long videos) and contrasts with the transcript tool. It doesn't explicitly mention alternatives like youtube_search or youtube_research, but the context is clear. A minor gap is not specifying when not to use it beyond the transcript context.

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