get_transcript

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

Beyond the annotations (readOnly, idempotent, non-destructive), the description discloses lazy pagination, ~8k token response caps with truncated=true and next_start_ms continuation, diarized speaker roster behavior, and format-specific output fields. These are critical behavioral traits not inferable from the schema or 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 long, but every sentence carries essential information: purpose, formats, pagination, exclusions, and a dozen usage examples. It is front-loaded with the core operation followed by structured examples, making it dense and efficient with zero fluff.

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 tool's complexity (multiple formats, pagination, diarization, sibling tools), the description covers all decision points: when to use which format, how to paginate via next_start_ms, how to handle wall_clock=null, and how to re-process with diarize=true. The presence of an output schema means return-structure details are not required, and output behavior is well documented.

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 0%, but the description fully compensates by explaining each format value (segments/text/srt), what fields appear (seq, t_ms, t_wall, speaker, text), how start_ms/end_ms work with concrete examples, and how to use next_start_ms for continuation. This adds substantial meaning beyond the bare 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?

The description uses a specific verb+resource ('Retrieve the transcript of a processed job') and immediately scopes it with 'lazily and paginated', formats, and response caps. It explicitly distinguishes from siblings by stating when NOT to use it (search for keywords, get_moment for visuals), making its purpose unmistakable.

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 provides explicit guidance with a 'When NOT to use' section naming search and get_moment as alternatives, plus concrete examples for pagination, diarized jobs, meeting audio, and time-range queries. The anti-examples ('where did they mention checkout?' → search) clarify boundaries clearly.

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