ask_video

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

With no annotations provided, the description carries the full behavioral burden and does a genuinely useful job: it discloses the RAG retrieval step (ChromaDB transcript chunks), that an external Groq LLM on a free tier generates the answer, and that responses include timestamps for jumping to the moment. That is real operational context beyond the schema, though it omits permission/auth needs and any rate-limit consequences implied by 'free tier'.

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 short paragraphs, with the core purpose front-loaded in sentence one and pipeline detail following. The implementation specifics (ChromaDB, Groq free tier) are borderline but do serve transparency; nothing is repetitive or padded.

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 values need no explanation, and the description covers purpose, mechanism, and the timestamped nature of answers. The main remaining gap is the unresolved relationship to the sibling search_video, which an agent selecting between them would want resolved.

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 all three parameters (question, video_name, n_context_chunks) are already documented in the schema, including defaults and examples. The description adds no syntax, format, or tuning guidance for them, 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?

The description states a specific verb and resource: ask a natural-language question about your videos and receive an AI-generated answer. It clearly distinguishes an answering/synthesis tool from pure retrieval, but it never names or contrasts with the closest sibling, search_video, so the boundary between them must be inferred.

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 implied by the phrasing 'get an AI-generated answer' versus search_video's likely raw-results behavior, but there is no explicit when-to-use, when-not-to-use, or alternative-naming guidance. An agent has to guess whether to reach for this or search_video when both would accept a question about a video.

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