Analyze Writing Voice & Drift

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

No annotations are provided, so the description carries the burden. It discloses that the tool reads a style_guide.json baseline and performs drift comparison, which is useful context, but it does not say what happens if no style guide exists, whether the operation is read-only, or what the result contains.

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?

A single dense sentence with the analyzed dimensions front-loaded before the drift check; no filler. Slightly over-packed as a parenthetical list, but efficient.

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?

With two simple, fully documented parameters and no output schema, the description is enough to invoke the tool, but it never describes the return shape (drift score? per-metric verdicts?) or the dependency on style_guide.json, which an agent needs to interpret results.

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 100% and both parameters are documented in the schema, so baseline is 3. The description adds no meaning beyond the schema — it does not clarify whether omitting 'chapter' analyzes the whole arc or what 'chapter' accepts (number vs path).

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?

States a specific verb (phân tích / analyze) plus the exact facets measured (sentence length, vocabulary, POV, tense, dominant emotion) and a second function: detecting voice drift against style_guide.json. That distinguishes it from siblings like story_analyze_pacing and story_analyze_sentiment, though the emotion overlap is not resolved.

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 tells what is compared (style_guide.json) but never states when to use this tool versus story_analyze_sentiment, story_analyze_pacing, or story_query_context, nor any preconditions such as requiring an existing style guide. Usage must be inferred.

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