save_approved_verification

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

Beyond the annotations, the description explains that saving writes an intellectual record rather than modifying the report, that errors are not a reason to refuse saving, and that the tool rejects only when the approval token mismatches current findings or when an error is paired with a 'pass' conclusion. This substantially enriches the agent's understanding of the tool's behavior and failure modes.

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 longer than average, but every section earns its place: safety condition, behavioral nuance, explicit rejection rules, return value, and usage examples. Critical approval guidance is front-loaded, and the structure makes the information easy to parse.

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 write tool with 6 parameters, annotations, and an output schema, the description covers the critical operational context: when to call, what the token is, what causes rejection, and what the response contains. The optional file/path parameters are sufficiently documented in the schema, so nothing essential is missing.

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 schema already documents all parameters. The description adds valuable context around 승인토큰 and 결론 constraints, but these largely reinforce schema descriptions rather than introducing new parameter-level meaning.

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 opens with a clear verb and resource: saving user-approved verification results to a file, and explicitly states this is the only write tool, which distinguishes it from the sibling read/analysis tools. It immediately signals the tool's unique role in the workflow.

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 gives explicit when-to-use and when-not-to-use guidance: call only after explicit user approval, never before showing the preview, and never without the approval phrase. It also names preview_verification_report as the source of the approval token and lists the two rejection conditions, providing an agent with concrete gating logic.

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