get_qa_recommendations

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

With no annotations, the description carries the burden of behavioral disclosure. It transparently explains that the tool aggregates recorded journeys and recent run cases for app_url, and describes the return structure (RecommendationSet plus embedded qa_context with specific stats). It omits side-effect safety but for a read-like view this is adequate.

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 concise sentences, front-loaded with a clear overview and no unnecessary words. Every phrase adds meaningful context.

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?

The tool is moderately complex (no output schema, no annotations, 4 params). The description covers the key output and mentions one param, but lacks semantics for release_id and lookback_runs and does not provide alternative/usage context. It is adequate for basic use but has clear gaps.

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 0%, so the description must compensate. It only explains 'scope' (use to narrow recommendation lists) and implicitly mentions app_url in the aggregation sentence. release_id and lookback_runs are completely unexplained, and even app_url lacks detailed semantics. This is insufficient for 4 parameters.

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 a specific QA-engineering view: test pyramid health, coverage gaps, flakiness signals, and prioritized recommendations. It also names concrete outputs (RecommendationSet, qa_context with risk matrix, defect mix, pyramid stats), which distinguishes it from sibling tools like debug_test_case or triage_release_blocker.

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 provides context for when the tool would be used (QA analysis aggregating journeys and run cases) and gives param-level guidance for scope. However, it does not explicitly mention when to prefer this tool over siblings or include exclusions, leaving usage guidance implied rather than explicit.

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