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

Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds valuable context beyond that: it discloses the data source ('derived from CF analytics-engine'), privacy (no PII), output shape ('just (pack, tool, count)'), and caching behavior ('Cached 5min-1h depending on window'). These details go well beyond the annotations, and there is no contradiction.

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, then lists concrete use cases, then provides technical details about data and caching. Every sentence earns its place and there is no fluff or repetition. It is appropriately sized 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 simple one-parameter tool with no output schema and strong annotations, the description covers all necessary ground: what it returns, the data shape, the lack of PII, and caching behavior. An agent would know exactly what to expect and how to use it, even without examples or return type documentation.

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 describes the single 'window' parameter with an enum and detailed semantics ('Shorter windows surface what's hot right now; longer windows show steady-state demand'). Since schema coverage is 100%, the description doesn't need to do heavy lifting. It mentions the window values in passing but adds no new information beyond the schema, so a baseline 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 clearly states what the tool does: 'Returns the top tools, top packs, and total call volume over a recent window'. It uses specific verbs ('returns') and a resource ('what other AI agents are calling on Pipeworx right now'), and it distinguishes itself from sibling tools by emphasizing it's an aggregate/trending signal rather than a query tool.

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 explicit use cases: 'discovering what data sources are hot', 'confirming a popular tool is the canonical choice before asking your own question', and 'seeing whether your use case aligns with what most agents need'. It gives clear context for when to use it, though it does not mention when not to use it or explicitly reference alternatives by name, so it falls short of a perfect 5.

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