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

Annotations already declare readOnly/openWorld/non-idempotent/non-destructive, so the safety profile is covered. The description adds real behavioral context beyond that: it makes LLM model calls per scenario and runs scorers, implying network access, latency, and cost. It does not mention rate limits, token cost, or runtime, which keeps it out of 5 territory.

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, front-loaded with the pipeline and outcome, followed by the routing hint. No filler, no restatement of the title, and every clause carries information an agent needs.

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?

With an output schema present, return values need not be explained, yet the description still summarizes them helpfully, and annotations plus a fully-covered schema handle safety and parameters. The only minor gap is that prerequisites such as required API keys or network/cost implications are left implicit.

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 description coverage is 100% and the schema already explains contract_path, inline_contract, overrides, api_keys, and validate_only in detail. The description only alludes to the contract file and 'the specified LLM model', adding essentially nothing over the structured fields, so the 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?

The description gives a specific verb chain (parse, call, run, return) over a named resource (.ia-eval.yaml LLM test suite) and states the concrete output (per-scenario Pass/Fail verdicts plus Markdown summary). This is distinguishable from siblings like run_semantic_tests, run_vlm_test_suite, and generate_eval_yaml without opening any schema.

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 gives a clear usage context (evaluating a .ia-eval.yaml suite) and explicitly routes the agent to list_local_tests to discover test files, which is a concrete prerequisite. It stops short of saying when NOT to use it or how it differs from run_semantic_tests/run_vlm_test_suite for adjacent evaluation tasks.

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