prepare_lint

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

The description explicitly states that no server-side LLM call happens, which is a key behavioral trait. However, without annotations, it should disclose more (e.g., side effects, permissions). The single behavioral detail helps but is insufficient for full transparency.

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?

Two sentences, no redundancy, and the first sentence immediately states the tool's core purpose. Efficient and well-structured.

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?

The description provides the essential purpose and a key behavior, but lacks details on output format, parameter semantics, and expected usage patterns. Given no output schema and only 2 parameters, it is minimally adequate but not complete.

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 0%, so the description should compensate. It mentions 'case batch' and 'lint instructions' but does not explain the 'cases' array format or 'feature_title' purpose. The description adds minimal value beyond the schema's parameter names.

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 states it returns a case batch with lint instructions for client-side evaluation, which is clear. It distinguishes from sibling tools that fetch cases from external sources, but could be more precise about what 'lint instructions' entail.

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?

No guidance on when to use this tool versus alternatives like prepare_cases_from_confluence or prepare_cases_from_jira. The description implies it's for client-side evaluation, but does not explicitly state selection criteria or when not to use it.

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