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

The description discloses that the data is 'Self-aggregating signal — derived from CF analytics-engine, no PII, just (pack, tool, count)' and notes 'Cached 5min-1h depending on window.' This adds meaningful context beyond the annotations, which already indicate read-only and non-destructive behavior. It also clarifies the data's origin and freshness.

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: a clear one-sentence summary, a results line, a numbered use-case list, and a concise data-source/caching note. Every sentence adds distinct value without redundancy or padding, making it easy to scan.

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 one optional parameter (fully covered by schema), clear annotations, and a description that explains the return content (top tools, top packs, total call volume), use cases, data source, privacy, and caching. It is fully complete for an agent to decide when and how to invoke it, even without 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 described in the schema with 100% coverage, including the enum values and their semantic difference (hot vs steady-state). The tool description merely mentions the window options without adding extra interpretation, so it meets the baseline for schema-sufficient parameters.

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 the top tools, top packs, and total call volume over a recent window (24h, 7d, or 30d).' The opening phrase 'What other AI agents are calling on Pipeworx right now' provides a specific, distinctive purpose that separates it from sibling tools like discover_tools or ask_pipeworx.

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 'Useful for:' list gives explicit scenarios (discovering hot data sources, confirming canonical tool choice, aligning use case with agent needs), but does not mention when not to use it or name alternative tools. This is clear guidance but lacks exclusion/alternative comparisons.

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