Blame an entity

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

Annotations already confirm the tool is read-only, non-destructive, and idempotent. The description adds value by disclosing the error case (returns error with isError: false when no history exists) and the specific fields returned (what changed, when, who, why).

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 extremely concise: three sentences that cover purpose, analogy, error behavior, and return content. No wasted words; every sentence adds value.

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 that the tool has an output schema (not shown but indicated in context), the description does not need to detail return values. It covers purpose, error handling, and behavioral traits. For a single-parameter tool with strong annotations, this is 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 coverage is 100% for the single parameter, so the schema already provides meaningful description. The tool description does not add further parameter-level detail, which is acceptable given the schema's completeness, resulting in a baseline score of 3.

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 returns the most recent change to an entity with details (what, when, who, why) and uses the 'git blame' analogy to make the purpose instantly familiar. It also distinguishes itself from generic git blame by specifying semantic entities and AI agents.

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 that the tool is for retrieving the latest change on a single entity, but it does not explicitly state when to use it over sibling tools like 'history' or 'log_change'. There is no 'when not to use' or alternative tool mention.

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