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

With no annotations provided, the description carries the full burden and does it well: it discloses the multi-stage pipeline, the expected return items, and the important architectural fact that the actual prose is produced client-side via sampling while the tool emits condition headers and quality-control reports.

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 compact and front-loaded: purpose, pipeline, output, and the key caveat about client-host generation are all expressed in a few dense clauses with no filler.

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?

The description names the return items despite the absence of an output schema and explains the unusual generation architecture. However, there is mild ambiguity about whether the tool's direct response contains the actual chapter text or only the condition header and QC report, so it is not fully complete.

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 100%, so work_id, chapter_no, and target_words are already documented in the schema. The description adds no additional parameter-level detail, so the baseline score of 3 is appropriate.

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 core purpose — generating a chapter — and summarizes the pipeline and output payload. It is specific enough about the resource and workflow, but it does not explicitly differentiate from siblings like continue_story or redline_audit.

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 guidance on when to use this tool versus the available alternatives, nor any mention of prerequisites or exclusions. The workflow description implies a chapter-generation use case, but the agent is left to infer when this is the right call.

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