explain_absence

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

With no annotations provided, the description bears the full burden. It transparently discloses that results are 'authored judgements' not derived data, mentions the stale flag, and details the output fields (publisher, route, confidence, review date). This goes beyond surface-level description.

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 verbose, with several sentences repeating the same idea (e.g., 'reasoned counterpart to coverage' and 'authored judgements'). It could be tightened while preserving key details, unlike concise equivalents like the high-scoring example.

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?

Despite verbosity, it is thoroughly complete: explains the purpose, every classification, the output structure, the nature of the data (judgements vs. derived), and the appropriate timing for use. 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?

The schema already covers all parameters with descriptions. The tool description adds depth to the 'classification' parameter by explaining each enum value in detail, but does not significantly enhance understanding of the other parameters. Baseline 3 is appropriate.

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: to explain why a factor is not in the corpus, with detailed classifications. It distinguishes itself by being the 'reasoned counterpart to coverage' and provides specific use cases, making it distinguishable from sibling tools like lookup_factor.

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 guidance on when to use the tool ('Call this before concluding that a gap is permanent...'), but it does not explicitly name alternative tools or state when not to use it. The guidance is implied rather than directly contrasting with siblings.

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