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

The description discloses behavioral traits well beyond the annotations. It explains that the data is self-aggregating, derived from CF analytics-engine, contains no PII, and is cached for 5 minutes to 1 hour depending on the window. These details about data source, privacy, and caching are not present in the annotations and significantly enrich understanding. There is no contradiction with the readOnlyHint or idempotentHint.

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 well-structured, front-loaded with the core purpose, followed by return details, use cases, and technical notes. Each sentence earns its place, and the 'Useful for' list is compact and informative. The length is appropriate for the tool's complexity, with no redundancy or fluff. It balances detail with readability.

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 tool has only one optional parameter and no output schema, the description provides complete context. It explains what is returned (top tools, packs, call volume, and aggregated tuples), the data source, privacy, caching behavior, and use cases. With rich annotations already covering safety, the description fully covers the remaining behavioral and contextual aspects. The tool is simple, but this description leaves no 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?

The schema already covers the single parameter (window) with a 100% description, including the tradeoff between shorter and longer windows. The tool description mentions the window options but does not add new meaning beyond what the schema provides. The return format (top tools, top packs, total call volume, (pack, tool, count)) is mentioned, but this is more about output than the parameter itself. Since schema coverage is high, the baseline of 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 what the tool does: returns top tools, top packs, and total call volume over a recent window. It uses a specific verb 'returns' and identifies the resource (Pipeworx traffic), distinguishing it from siblings like discover_tools or ask_pipeworx. The scope is explicit with the window parameter and the aggregating nature. This is a precise, non-tautological statement of purpose.

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 a clear 'Useful for' list with three specific use cases: discovering hot data sources, confirming canonical tool choices, and aligning use cases. This gives explicit context on when to use the tool. However, it does not explicitly mention when not to use it or name alternative tools, so it falls short of a 5. The guidance is practical and clear enough for an agent to decide.

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