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

Beyond the readOnlyHint and idempotentHint annotations, the description adds meaningful behavioral context: data is self-aggregated from CF analytics-engine, contains no PII, includes only (pack, tool, count), and is cached for 5 minutes to 1 hour depending on window. This discloses provenance, privacy, and caching behavior without contradicting the 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 approximately 100 words with a clear structure: it opens with the core purpose, lists the returned data, presents three specific use cases, and finishes with data provenance and caching details. Every sentence adds value and there is no redundancy or filler.

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 one-parameter read-only tool with no output schema, the description adequately covers the input (window), the output (top tools, packs, call volume), and data composition (pack, tool, count). It could be slightly more complete by specifying the exact response format or any pagination, but it is sufficient for practical use.

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 a detailed description of the 'window' parameter, covering the enum values and the tradeoff between shorter and longer windows. The tool description reinforces the window values and adds a minor note about cache duration varying by window, but this is more behavioral than semantic and does not significantly enhance understanding of the parameter beyond the schema.

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 returns top tools, top packs, and total call volume from other agents on Pipeworx, with a specific verb ('Returns') and resource ('what other AI agents are calling'). It also provides three concrete use cases that differentiate it from sibling tools like discover_tools by focusing on current aggregate usage patterns.

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 lists three use cases: discovering hot data sources, confirming canonical tools, and checking alignment with common agent needs. It gives clear context on when to use the tool, but does not explicitly name alternatives or provide when-not-to-use guidance, so it stops short of a 5.

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