fit_check_audit

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

No annotations are provided, so the description must fully convey behavioral traits. It describes the tool as parsing and auditing, implying a read-only analysis, but does not explicitly state side effects, permissions, or whether it modifies state. The return example and keys provide some insight, but more explicit behavioral context would be helpful.

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 well-structured with distinct sections: purpose, usage, params, returns, example. It is concise with no wasted words; every sentence adds value.

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 the tool's simplicity (one parameter, output schema exists), the description covers the return keys and provides an example. It distinguishes from relevant siblings (fit_check_drift, fit_check_emit). It is slightly lacking in prerequisites or edge cases, but overall sufficient for the complexity level.

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?

The input schema has 0% description coverage, so the description compensates by explaining the single parameter: 'cluster_slug: cluster whose briefing is audited.' This adds meaning beyond the schema, which only provides the name. An example usage further clarifies.

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 purpose: 'Parse the latest NotebookLM briefing for off-topic flags.' It uses a specific verb 'parse' and a resource 'NotebookLM briefing', and distinguishes itself from sibling 'fit_check_drift' by noting it audits before drift check.

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?

Explicit usage guidance is provided: 'When to use: after NotebookLM flags papers. When NOT to use: to emit scoring prompts; use `fit_check_emit` instead.' This clearly indicates when to use this tool versus an alternative.

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