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

Beyond the readOnly/idempotent annotations it discloses real behavioral traits: a hard coverage boundary (case law ends 2026-09-30, exact count), staleness signaling via body_as_of/body_pending/body_note, the inconclusive-empty-result case when a count is unreadable, and a 503 cold-index behavior with a single server-side retry.

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?

Front-loaded with purpose and mechanism before the caveats, and each sentence carries operational information an agent would otherwise get wrong. It is dense and long for a two-parameter tool, with coverage/staleness detail that could partly live in the response note, costing it a point.

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 tool is simple, but the corpus has real traps (date cutoff, stale text, cold index). With no output schema, the description still explains the notable response fields and how to interpret empty results, leaving nothing an agent needs in order to call and read it correctly.

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-schema (id sourced from search/fts/semantic result opinion_id; limit 1-20, default 20). The description confirms that the id is an opinion id, not a case id, but adds no syntax or default detail beyond the schema, so the baseline 3 applies.

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?

Opens with a specific verb+resource: 'Given one opinion id, returns other opinions whose wording overlaps it, ranked by keyword match (BM25 more-like-this).' It explicitly delimits the mechanism ('Keyword overlap only') which separates it from search/semantic_search siblings, and states the exclusion of the seed opinion and its own case.

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?

Strong contextual guidance: it says what the result does NOT mean (not same issue, same result, or good law) and how to read a thin/empty result against the collection cutoff. It never names an alternative tool (e.g. semantic_search for conceptual similarity, treatment for validity), so the agent must infer the fallback, which keeps it below a 5.

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