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

Annotations already declare readOnly/idempotent/non-destructive, so the safety profile is covered; the description goes further by enumerating the return fields (verdict, percent, best_match, star_page, offset, case, advice) and interpreting the verdict enum. However, 'percent' is never explained, so a key piece of returned behavior is left ambiguous.

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 core check is front-loaded in the first sentence, then return values, then case identification, so scanning order is sensible. It is dense and mixes in agent-workflow rules (quotation-mark conventions, running check_brief) that make it longer than strictly needed, though each rule is actionable.

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 no output schema, the description carries the return-value burden and mostly does so, including how to act on 'near' and 'absent'. Gaps remain: the meaning of 'percent' and the handling of quotes shorter than the schema's three-word minimum are unaddressed, which matters for a tool whose whole value is the verdict.

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%, so the baseline is 3; the description adds real meaning by explaining how the case is identified — cluster_id or reporter citation, with case_name as the fallback for citations newer than the reporter index. That precedence rationale goes beyond the schema's terse per-field 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 first sentence states a precise verb and resource — checking one quotation against the full text of the opinion it is attributed to — and scopes it with a trigger ('before it goes in quotation marks'). It is clearly distinguishable from siblings like search_quotes (finding quotes) and check_brief (draft-level review).

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 gives explicit when-to-use rules ('before it goes in quotation marks', 'if you typed a quote from memory, run verify_quote and use best_match') and names the alternative workflow for text that was pasted from a tool result, plus a downstream routing instruction to check_brief. Alternatives and conditions are both stated.

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