verify_quotes

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

With no annotations provided, the description fully discloses behavior: input structures (evidence pack or audit doc), output (present, absent, missing_source_text), and limitations (no outbound requests, no factual truth verification). No contradictions.

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 a single, well-structured paragraph. Each sentence adds value: purpose, usage context, input format, output, and limitations. No wasted words.

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?

Given two parameters (one required), nested objects, and no output schema, the description is thorough. It explains input types, output types, and what the tool does not do, ensuring the AI agent can invoke 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 description coverage is 100%, so baseline is 3. The description adds meaning beyond schema: explains that pack_json can be an evidence pack or audit doc, and that span checks carry claim_id. This adds useful context.

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 clearly states the tool's verb ('Check'), resource ('quoted fragments appear in caller-provided source text'), and scope. It distinguishes itself from siblings by explicitly listing what it does not do (e.g., no outbound requests, no source reputation).

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 explicitly states when to use the tool ('Use when you have local excerpts and need to catch citation drift or misquoted snippets') and lists exclusions ('Local-text only: it does not make outbound requests...'). It does not name specific alternative tools, but the context is clear.

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