code_history

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

With no annotations, the description carries full transparency burden. It discloses the requirement for a git checkout, optional line-range blame, and the nature of outputs. It does not mention error cases or performance, but overall provides adequate behavioral context.

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 with no wasted words. The first sentence immediately conveys the tool's purpose and outputs. It is well-structured and front-loaded, making it easy to parse.

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 4 parameters, 100% schema coverage, and the presence of an output schema, the description does not need to detail return values. It covers key behaviors (blame, prerequisite) and mentions churn stats. It is complete enough for the complexity level, though it could briefly mention how to use max_commits.

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%, giving a baseline of 3. The description adds value by explaining that start_line/end_line enable blame on a specific region, which enriches the schema descriptions. It also clarifies the prerequisite (git checkout) implicitly linking to the file parameter.

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 uses a specific verb ('explain') and resource ('why code looks the way it does using git'), listing concrete outputs (commits, churn stats, blame). It clearly distinguishes from sibling tools like find_references or search_code, which serve different purposes.

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 when to use (to understand git history of a file) and mentions a prerequisite (git checkout). However, it lacks explicit guidance on when not to use this tool or direct comparisons to siblings, which limits its utility for an AI agent deciding between tools.

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