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

Beyond the annotations (readOnlyHint, idempotentHint, etc.), the description discloses that data is self-aggregated from CF analytics-engine, contains no PII, and is cached for 5 minutes to 1 hour depending on the window. This adds valuable behavioral context about caching, privacy, and data source. No contradiction with annotations.

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 remarkably concise: two sentences. The first sentence states the primary function and output; the second elaborates with a bulleted use-case list. It is front-loaded with the action, and every sentence adds value without repetition or fluff.

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?

The tool has a single optional parameter, no output schema, and read-only annotations. The description compensates by specifying the exact return contents (top tools, top packs, total call volume, and 'pack, tool, count' format), caching behavior, and privacy guarantees. For its simplicity, the description fully covers what an agent needs to know.

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 input schema already provides 100% coverage of the single parameter 'window', including its enum values and a description of how shorter vs. longer windows affect results. The tool description merely repeats the window options without adding semantic detail beyond what the schema provides, so the baseline score of 3 applies.

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: it returns top tools, top packs, and total call volume over a recent window. It explicitly focuses on 'what other AI agents are calling on Pipeworx right now,' which distinguishes it from siblings like ask_pipeworx (Q&A) and discover_tools (tool discovery). The verb 'returns' plus specific resources makes the purpose unambiguous.

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 'Useful for' list with three concrete scenarios, giving clear guidance on when to use this tool. It does not explicitly state when not to use it or name alternative tools, but the use cases implicitly contrast with asking a question (suggesting ask_pipeworx as alternative). This is strong contextual guidance, though not exhaustive.

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