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

The description goes well beyond the readOnlyHint annotation, disclosing sampling behavior (deterministic 1% sample for rule detail, TOTAL for every call), display gates (n×(1−q) ≥ 3), judgment gates (n ≥ 100), INSUFFICIENT_COHORT behavior, and the slow-rule flag formula. It also explains that percentiles can be null and why. This is rich behavioral context that an agent needs to interpret results correctly.

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 dense but well-organized, front-loading the core purpose and then explaining gates and defaults. Every sentence adds value, though the density of statistical details (display gate formula, thresholds) could be slightly overwhelming. It's appropriately sized for the complexity of the tool.

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?

For a read-only analytics tool with no output schema, the description covers the key things an agent needs: what data is returned, how it's sampled, what gates apply, what edge cases look like (INSUFFICIENT_COHORT), and defaults. The absence of an output schema is compensated by the detailed description of the result structure.

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 100%, so the schema already documents all parameters. The description adds context about defaults (last 24h, live version, cacheState HIT) and the cacheState meaning (HIT = compiled ruleset cache hit, MISS = deep-load + compile), which enriches the enum semantics. However, it doesn't add much beyond what the schema provides for individual parameters, so 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 it provides a per-rule latency profile of a policy group over a time window, with specific components: TOTAL distribution split by cache state, per-rule CONDITION/ACTION percentile table, and slow-rule flags. It distinguishes itself from siblings like lexq_profile_rule by focusing on group-level overview with per-rule breakdown.

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 explains the default time window, version, and cache state, and mentions the judgment gate (n ≥ 100) and display gate. It doesn't explicitly state when to use this vs alternatives like lexq_profile_rule, but the name and content make the group-vs-rule distinction clear. It also notes that absolute thresholds are intentionally not supported, which helps set expectations.

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