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

The description adds valuable behavioral details beyond annotations: 'Self-aggregating signal — derived from CF analytics-engine, no PII, just (pack, tool, count)' and 'Cached 5min-1h depending on window.' These disclose data provenance, privacy, output shape, and caching behavior, far exceeding the readOnly/idempotent 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 front-loaded with the core purpose, followed by bullet-like use cases and then technical details. It is slightly longer than strictly necessary but every sentence adds useful information, with 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 read-only tool with one optional parameter and no output schema, the description fully explains what is returned ('top tools, top packs, total call volume'), the aggregation source, caching, and privacy guarantees. It is complete enough for an agent to invoke correctly.

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?

Schema coverage is 100% for the single 'window' parameter, so the baseline is 3. The description adds extra meaning by noting 'Cached 5min-1h depending on window,' which connects caching behavior to the selected parameter—value 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 opens with a specific verb ('Returns') and a clear resource: 'the top tools, top packs, and total call volume' from Pipeworx. This clearly distinguishes it from siblings like discover_tools by focusing on aggregated agent call trends rather than tool discovery or Q&A.

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?

It provides three explicit 'Useful for' scenarios: discovering hot data sources, confirming canonical tools, and checking use-case alignment. This gives clear context on when to use it, though it does not explicitly mention alternative tools or when not to use it.

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