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

Annotations already declare read-only, idempotent, open-world, and non-destructive. The description goes beyond by disclosing that it is self-aggregating, derived from CF analytics-engine, contains no PII, and is cached 5min-1h depending on the window. These are meaningful behavioral traits not present in 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 well-structured and efficient. It front-loads the core purpose, then lists return items and use cases in a scannable format. Every sentence provides 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 tool with one optional parameter and no output schema, the description is very complete. It explains what the tool returns (top tools, top packs, total call volume, and the aggregation details), gives use cases, and discloses caching and PII behavior. Nothing essential is missing.

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 single parameter 'window' is fully documented in the schema with an enum and a clear description of how short vs. long windows behave. The tool description only echoes the available windows and adds a caching note, which is more about behavior than parameter meaning. With 100% schema coverage, a 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 specific, action-oriented statement: 'What other AI agents are calling on Pipeworx right now.' It then details exactly what it returns (top tools, top packs, total call volume) and the time windows. This clearly distinguishes it from siblings like discover_tools and market_snapshot.

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 an explicit 'Useful for' list with three concrete use cases (discovering hot data sources, confirming canonical tool choice, checking alignment with agent needs). This gives clear when-to-use guidance, but it does not mention when not to use the tool or alternative tools, 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.