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

Annotations declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, but the description adds valuable behavioral context: it mentions the data source (CF analytics-engine), that it contains no PII, and that results are cached for 5min-1h depending on window. This goes beyond what annotations provide.

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 question and returns statement, followed by a concise list of use cases and a note on data origin and caching. Every sentence adds value, though the list makes it slightly longer than strictly necessary.

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?

Given the tool's simplicity (one optional parameter, no output schema), the description adequately covers what it returns (top tools, top packs, total call volume, "(pack, tool, count)"), the data source, and the use cases. It's complete enough for an agent to invoke it 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?

The schema fully covers the only parameter 'window' with enum values and a clear description of how shorter vs longer windows affect results. The main description only repeats the options without adding new semantics beyond the schema, so baseline 3 applies.

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 clear question, "What other AI agents are calling on Pipeworx right now", then states it returns top tools, top packs, and total call volume. This is a specific verb+resource+scope that clearly distinguishes it from siblings like discover_tools or search.

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" section lists three concrete scenarios, giving clear context for when to use the tool. It doesn't explicitly exclude alternatives, but the use cases are specific enough to guide an agent on when this is appropriate.

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