get_text_fixes

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

With no annotations, the description carries the full disclosure burden, and it does add real value: it states the call is a 'Free preview' (cost expectation) and that output shape varies by preparation state (preview list vs. exact find/replace edits). It says nothing about permissions, what happens when run_id is not a completed review, or failure modes, which is a meaningful gap for a zero-annotation tool.

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 tight sentences: the first front-loads what the fixes are, the second covers the state-dependent behavior, followed by a minimal Args block. The parenthetical category list is dense but informative and nothing is redundant.

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 needn't be explained, and the description covers purpose, scope, lifecycle, and the one parameter. The remaining gap is the lack of dependency guidance on prepare_text_fixes and error/eligibility behavior for non-completed runs.

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 coverage is 0%, so the description must compensate, and it does: the Args block constrains run_id to 'The Run ID of a completed review,' which is a real semantic restriction beyond a plain string. It does not give format examples or say where a run_id comes from (e.g., list_my_reviews), so compensation is partial but solid for a single parameter.

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 names the specific resource (text fixes of a completed review) and enumerates the categories of change it covers (wording, overstated claims, citations, missing references, method details, typos), so an agent knows exactly what it returns. It implicitly separates itself from prepare_text_fixes by describing the pre-prepared vs. prepared states, though it never names the sibling explicitly.

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 establishes clear call context: this applies to a completed review, and the response depends on whether the fixes have been prepared yet ('Free preview before they are prepared; once prepared, the exact edits...'). What's missing is an explicit pointer to prepare_text_fixes as the step that transitions between those states, leaving the agent to infer it from the sibling name.

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