should_i_use

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

No annotations are provided, so the description carries the burden of disclosing behavior. It mentions useful outputs like 'when to skip it' and 'maintenance signals,' but it does not state whether the tool fetches live data, is subjective, or has side effects. This leaves some behavioral uncertainty.

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?

A single dense sentence front-loads the purpose ('Honest verdict') and lists key output components in a readable, colon-separated format. Every phrase contributes meaning; there is no filler.

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 one-parameter tool with no output schema or annotations, the description adequately conveys the tool's purpose and return contents. The vague reference to '4-axis scores' is a minor gap, but overall it is sufficiently complete for the tool's simplicity.

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 has 100% description coverage for the single 'library' parameter, so the baseline is 3. The description adds no parameter-specific details beyond the schema, merely referring to 'a specific library.'

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?

Description clearly identifies the tool as producing an 'Honest verdict' on a library, with specific output components like scores and maintenance signals. This distinguishes it from sibling tools, though the exact 4 axes are not enumerated, preventing a 5.

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?

Usage is implied: use when evaluating whether to adopt a library. It does not explicitly contrast with sibling tools like 'alternatives' or 'how_do_i,' so no clear exclusions or when-not-to-use guidance is provided.

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