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

Beyond the annotations (readOnly, openWorld, idempotent, non-destructive), the description adds valuable context: it is a self-aggregating signal derived from CF analytics-engine, contains no PII, returns a simple (pack, tool, count) structure, and is cached for 5min-1h depending on the window. This goes well beyond what annotations alone convey.

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: an engaging opening sentence, a clear listing of return values, a bulleted list of use cases, and a concise note on data source and caching. While slightly longer than the two-sentence minimum, every sentence earns its place and there is no 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?

For a simple tool with one optional parameter and no output schema, the description thoroughly covers what the tool does, what it returns, when to use it, and how the data is sourced and cached. The return format is described at a high level, which is sufficient given the lack of an output schema.

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 only parameter, window, is fully documented in the schema with enum values, defaults, and trade-off descriptions. The tool description repeats this information but adds no new semantic meaning. With 100% schema coverage, 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 opens with a clear, specific statement: 'What other AI agents are calling on Pipeworx right now.' It explicitly names the resources (top tools, top packs, total call volume) and the time windows. This distinguishes it from sibling tools like discover_tools or ask_pipeworx, making the purpose unmistakable.

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 three concrete use cases (discovering hot data sources, confirming canonical tool choice, aligning with agent demand) and explains the trade-offs between shorter and longer windows. While it doesn't explicitly name alternatives or say 'use X instead', the context is clear enough to guide appropriate usage.

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