observe_pattern

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

With no annotations, the description carries full burden and does exceptionally well: it discloses cost (1 DAC), auth requirement, payment flow via x402 (including the challenge-response mechanism), and trial exclusion. It also notes version history ('formerly free'), providing valuable operational context.

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 long and densely packed with relevant information: what it does, what data it returns, cost, auth, and payment specifics. Every phrase earns its place, and the structure is front-loaded with purpose before operational details.

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 no output schema and no annotations, the description explains the return data (EE distributions, action-type breakdowns) and the payment flow sufficiently. It could be more explicit about response format or pagination, but the core behavior is clear. The 'across agents' scope is somewhat ambiguous but acceptable.

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 the baseline is 3. The description adds little beyond the schema: it re-emphasizes the auth_token requirement and mentions payment_signature in passing, but these are already described in the schema. No additional parameter-level insights are provided.

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 uses a specific verb 'Observe' with a clear resource ('pattern-level analytics') and specifies the data types ('EE distributions and action-type breakdowns across agents'). This directly distinguishes it from sibling tools like observe_environment, which likely focuses on environment-level observations.

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 clearly states the tool's purpose and adds crucial context about cost and authorization, implying when it should be used (when you need pattern analytics and can pay). However, it does not explicitly mention alternatives or when not to use it, so it lacks explicit exclusions.

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