recent_work

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

The description reinforces annotations with 'Read-only' and adds behavioral context like 'Pure local git; no network', which goes beyond the annotations. It also describes the output structure. No contradictions with 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 two sentences: the first succinctly defines purpose and scope, the second details the return format. Every word contributes meaningful information, no fluff or repetition.

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 moderate complexity and the presence of an output schema in the description, the description covers defaults, return type, and key constraints. Minor omissions like the exact git command used are not critical for an AI agent.

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 coverage is 100%, but the description adds valuable default behavior information (e.g., author defaults to repo's user.name, since defaults to 7 days ago). This enriches the agent's understanding beyond the raw schema.

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 it's a read-only standup/changelog helper that shows one author's commits in a time window with file changes and insertion/deletion totals. This distinctively sets it apart from sibling tools like 'branch_hygiene' or 'co_change' by focusing on individual author activity.

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 implies usage scenarios (standup, changelog) and mentions defaults, but does not explicitly state when to avoid using it or compare it to sibling tools like 'who_touched' or 'commit_context'. However, the context is clear enough for an AI agent to infer appropriate use.

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