record_test_run

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

With no annotations, description carries full burden. It discloses that the tool executes a test suite (potentially side-effecting) and persists results, and it emphasizes the explicit, distinct nature preventing implicit side effects. It does not mention failure behavior or data overwrite semantics, but it provides security context (repo_path must resolve under allowed roots).

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, first is direct action, second adds valuable context on when to use. No redundant filler.

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 executes arbitrary Python tests and persists data, description covers the core role and relation to siblings. Output schema exists, so return values are documented elsewhere. Missing some edge-case behavior but adequate for an AI agent to select and invoke.

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 covers the only parameter fully with a description including absolute path and allowed root constraint. The tool description does not add further meaning, so baseline 3 applies.

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?

Description starts with a specific action: 'Execute the test suite once and persist the results to the database.' It clearly distinguishes from siblings by explaining that this is the explicit write step while get_test_history and train_risk_model consume the data, and it never runs implicitly, so it's unambiguous.

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?

It explains that this tool is the explicit step for writing history versus reading or analyzing, referencing sibling tools get_test_history and train_risk_model. It could be more explicit about when NOT to use it (e.g., for read-only queries, use get_test_history), but the contrast between 'written versus just read or analysed' provides clear context.

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