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

Annotations already declare readOnlyHint=true and idempotentHint=true, covering safety. The description adds behavioral detail by clarifying the computation includes both raw rates and rates excluding pending matters, which is useful context. It does not contradict annotations and provides meaningful nuance about the output.

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 sentences with zero waste. The core function is front-loaded, followed by concrete example queries that immediately ground the agent. No redundant information is present.

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?

There is no output schema, so the description must convey what the tool returns. It mentions raw and excluding pending rates, implying counts or percentages, and the limit parameter implies examples. However, it doesn't explicitly state the structure of the returned data (e.g., buckets, examples, percentages). For a tool with moderate complexity, this is a notable gap, though not critical for basic 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?

Schema description coverage is 100%, with both parameters (firm_name and limit) documented in the input schema. The description does not add additional meaning beyond the schema; it only references resolving a firm, which is already implied by the firm_name parameter. Per rubric, baseline 3 is appropriate when schema fully covers parameter semantics.

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 identifies the tool's function: resolving a trademark law firm and computing mark-level Office Action outcome rates. It distinguishes from siblings by specifying firm-level aggregation, which is not covered by other tools like get_latest_office_action or research_office_action that operate per-mark. The verb 'resolve and compute' is specific and the resource is well-defined.

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 explicitly states when to use the tool with example queries ('what percentage registered after an OA?' or 'OA success rate for this firm'). It provides clear usage context, though it doesn't mention when not to use it or alternative tools. Since no sibling directly overlaps, the guidance is sufficient for routing.

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