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

No annotations exist, so the description carries the full burden. It does disclose useful non-obvious traits: this is a 公開版 with no 案件固有名, the full text is ~88,000 characters, and truncation names the dropped sections. It does not state that the tool is strictly read-only, nor anything about permissions or rate limits — modest but real disclosure.

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?

Four sentences, front-loaded with what is returned and followed by output-shape and parameter behavior. Every sentence carries information; there is no filler. Minor overlap with the schema's parameter descriptions keeps it from a 5.

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?

For a parameterless-required, read-only retrieval tool with a fully documented schema and no output schema, the description covers what an agent needs: default behavior, size constraints, truncation semantics, and the recommended query path. The only gap is that it never describes the format of the returned index or matched sections.

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 the baseline is 3. The description goes beyond the schema by explaining the motivation behind the parameters — the corpus is too large to return whole, which is why full defaults to false and query is recommended — and by giving concrete query examples of the domain vocabulary. That rationale adds genuine meaning over the field-level text.

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 gives a specific verb and resource — it returns b612 の実戦ノウハウ and enumerates the content types (典型エラー・推測実装の傾向・過去に効いた意思決定). That is far more concrete than the bare name 'patterns'. It does not, however, distinguish itself from close siblings like b612_principles, b612_rules, or b612_notes, leaving the agent to infer which knowledge base to consult.

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 clearly explains the tool's own operating modes: default returns only the heading index, and passing a query returns just matching sections, explicitly marked 推奨. What it never addresses is tool selection — no statement of when to prefer this over b612_principles, b612_rules, or b612_notes. Usage is implied rather than routed.

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