ask_transcript

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

Annotations are absent, so the description carries full responsibility for behavioral disclosure. It only says the tool answers from transcripts; it does not disclose that an LLM is involved, potential hallucination or grounding limitations, output format, or whether the operation is read-only. Some behavior is implied, but little is actually transparent.

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 a single short sentence that front-loads the tool's purpose. It contains no wasted words, though the phrasing 'Ask a question answered from' is slightly awkward and the conciseness comes at the expense of useful behavioral and usage context.

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?

Given the small parameter surface and fully documented schema, an agent can infer the basic call pattern: provide transcript IDs and a question. However, there is no output schema, no note about return value, no guidance versus sibling tools, and no limitation disclosure, leaving meaningful gaps for an agent that needs to actually invoke this 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?

All three parameters (transcript_ids, question, model) are fully described in the input schema, including the model default. The description adds no parameter-level meaning beyond what the schema already provides, so the baseline score of 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 clear action ('Ask a question') and resource ('transcripts'), and the phrase 'answered from one or more transcripts' conveys an understanding/Q&A role rather than a retrieval/list role. It does not explicitly name a sibling like search_transcript or summarize_transcript to differentiate itself, so it stops just short of a 5.

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?

There is no explicit guidance on when to use this tool versus alternatives such as search_transcript, summarize_transcript, or get_transcript. The description only implies the obvious case—asking a natural-language question over transcripts—but provides no exclusions, preferences, or context for choosing it over sibling tools.

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