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

Beyond the readOnlyHint/idempotentHint annotations, the description reveals caching behavior ('Cached 5min-1h depending on window'), data provenance ('derived from CF analytics-engine'), and privacy ('no PII, just (pack, tool, count)'). It does not mention rate limits or failure modes, but it adds substantial behavioral context.

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 a concise 'Useful for' list and a transparency note. Each sentence adds value, and the overall length is appropriate for the tool's simplicity.

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 read-only tool with one optional enum parameter and no output schema, the description fully covers purpose, use cases, return contents, caching, and data privacy. The agent has enough information to select and invoke the tool correctly without requiring additional clarification.

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 already fully described in the input schema, including the default '24h' and the tradeoff between short and long windows ('Shorter windows surface what's hot right now'). The tool description repeats but does not add new semantic meaning 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 and resource: 'What other AI agents are calling on Pipeworx right now' and clearly states it returns top tools, top packs, and total call volume over a selectable window. This distinguishes it from sibling tools like discover_tools or ask_pipeworx by focusing on aggregated agent-usage trends.

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 explicitly enumerates when to use the tool: discovering hot data sources, confirming canonical tools, and checking alignment with agent demand. It lacks an explicit 'when not to use' or direct comparison to alternatives, 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.