detect_attention_to_detail

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

No annotations are provided, so the description carries the full burden. It discloses the evaluation criteria (7 checks) and the return format (bonus points, anti-pattern flags, checklist), which is useful behavioral context. However, it does not state whether the tool is read-only, requires any authentication, or has side effects, leaving a notable gap for a tool with no annotations.

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 a brief intro followed by a bulleted checklist. It is front-loaded with the purpose, and every line adds value. No fluff or redundant information.

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 explains what the tool does, what exact checks it performs, and what it returns. Since an output schema exists, return details are covered elsewhere. The main missing element is usage guidance and explicit caveats, but overall the description covers the core behavior quite well for a moderately complex analysis tool.

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%, meaning every parameter already has a description. The tool description adds no additional semantics about how parameters like 'repo', 'since', 'until', or 'username' influence the analysis. Per the guideline, baseline 3 applies when schema does the heavy lifting.

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 specific verb ('detect') and resource ('attention-to-detail'), then enumerates a concrete checklist of criteria (README, CHANGELOG, tests, commit messages, etc.). This makes the tool's purpose highly specific and clearly distinguishes it from sibling analysis tools like get_contribution_metrics or analyze_karpathy_alignment.

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 checklist implies the tool is used to assess thoroughness of code changes, which gives some contextual hint. However, there is no explicit guidance on when to use this tool versus siblings, nor any exclusions or alternative tool mentions. It is only implicitly usable.

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