parse_transcript

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that it uses a Python backend and generates accurate word timings, but it does not disclose whether this operation is read-only or mutating (does it write anything? does it modify the video file?), whether it is idempotent, or what happens if the input format is invalid. It also doesn't state any side effects like caching or file writes. Given no annotations, this is a significant gap for a tool that processes and likely produces output.

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 sentences: the first states the core function and input format, the second adds a credibility note about the backend. Every sentence earns its place; the input format is front-loaded, which is practical. No redundant 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 4 parameters, 2 required, and no output schema, the description covers the input format and mentions the file path indirectly. It does not explain what the tool returns (presumably timestamps, but no output schema to clarify), nor does it address edge cases like malformed input or the relationship between file_path and the transcript. It is adequate for a straightforward parsing tool but leaves the agent to infer return structure and error behavior.

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 description coverage is 100%, meaning every parameter has a description in the schema. The tool description adds value by specifying the exact input format for raw_text ('Speaker (MM:SS)\ntext...'), which is not fully captured in the schema's generic 'Raw speaker-labeled transcript text'. It also implies that time_adjust and total_duration are optional enhancements. This goes beyond the schema baseline.

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 ('Parse'), a clear resource ('raw speaker-labeled plain text transcript'), and the key output ('word-level timestamps'). It also includes the input format, which adds specificity. However, it does not distinguish itself from the sibling 'import_transcript', which likely overlaps in function, and the phrase 'Parse a raw speaker-labeled plain text transcript' could be more explicit about the scope (e.g., that it processes text, not audio files).

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 implies usage when you have a speaker-labeled plain text transcript and want word-level timestamps, and it references the Python backend for accuracy. However, it provides no explicit when-to-use vs. alternatives, no mention of prerequisites (e.g., that the video file path is required for context), and no guidance on when NOT to use this tool in favor of import_transcript or transcribe_start. The context is clear but lacks exclusions or alternatives.

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