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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint, so the safety profile is known. The description adds valuable context about the data sources (LinkedIn, BLS benchmarks) and the kind of output (ranked list, risk scores, retention actions), exceeding what annotations alone provide.

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 front-loaded, with the core action in the first sentence. It is reasonably concise, though the keyword list at the end is somewhat redundant and adds no value beyond the previous sentences. Overall, it is efficient without being overly verbose.

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 moderate complexity, an output schema exists, and the description covers the key aspects: what it analyzes, what it returns, and the intended use case. It does not need to explain return values in detail since the output schema handles that. The description is complete enough for an agent to select and invoke the tool.

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%, so all parameters are documented in the schema. The description does not add meaning beyond the schema—it references LinkedIn activity and compensation benchmarking, but does not explain specific parameters like department or min_tenure_months. Baseline 3 is appropriate.

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 the tool's function: analyzing employee poaching risk using LinkedIn activity and compensation benchmarks, and returning a ranked list with risk scores and retention actions. It uses specific verbs and resources, and the focus on poaching risk distinguishes it from other HR/talent tools like comp_benchmark_geo_delta or candidate_screening_ranking.

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 identifies a clear use case ('Ideal for proactive talent retention strategies') that implies when to use it. However, it does not explicitly state when not to use it or name alternative tools, though the context is sufficient for an agent to make a reasonable choice.

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