get_test_report

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

With no annotations, the description carries the full burden. It discloses that it reads a file from a previous run, is non-destructive, and returns a summary. It also explains the conditional edge_metrics block. However, it does not explicitly state idempotency or potential side effects (though none likely).

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 detailed and contains important usage guidance. However, it includes version-specific details that could be separated (v1.3.0+ edge AI runner info). It is front-loaded with the core functionality.

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 no output schema, the description thoroughly explains the return shape (fields total, passed, failed, skipped, flaky_in_run, duration) and the error case. It also covers the edge metrics block for Edge AI runner. The tool has no parameters, so this is sufficient for complete usage.

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?

There are zero parameters, so baseline 4 applies. The description correctly adds no parameter information since none exist.

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 reads the previous test report and returns a lightweight summary, specifying exact fields (total, passed, failed, skipped, flaky_in_run, duration). It distinguishes itself from run_tests (cheaper) and get_failure_details (for detailed failure info).

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?

Explicitly states when to use (between continuous operations, checking status cheaply) and when not (if no previous run, returns error). It also provides alternative actions: if failed > 0, use get_failure_details. Mentions edge AI runner specifics and leads to get_optimization_plan.

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