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

Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds valuable context beyond this: it discloses the data source ('derived from CF analytics-engine'), the privacy property ('no PII'), and caching behavior ('Cached 5min-1h depending on window'). It effectively communicates the read-only, self-aggregating nature of the tool.

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 a single, well-organized paragraph. It front-loads the core purpose, then provides a bullet-like list of use cases, and ends with additional data source and caching details. Every sentence earns its place with no wasted words.

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?

With only one optional parameter, no output schema, and strong annotations, the description still fully covers what the agent needs to know: what it returns (top tools, packs, call volume), when to use it, the data source, privacy, and cache timing. It is complete for a simple, read-only aggregation tool.

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% and the schema already provides a description for the window parameter. The description adds extra semantics by explaining that 'Shorter windows surface what's hot right now; longer windows show steady-state demand,' which helps the agent choose an appropriate value. This goes beyond simple schema repetition.

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: "What other AI agents are calling on Pipeworx right now. Returns the top tools, top packs, and total call volume over a recent window." It uses a specific verb ('Returns') and names distinct resources (tools, packs, call volume), making it easy to distinguish from siblings like discover_tools.

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 explicitly lists three concrete use cases (discovering hot data sources, confirming canonical tool choice, aligning with agent needs), providing clear context for when to use it. However, it does not name an alternative sibling or state when NOT to use it, so it falls short of the most explicit guidance.

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