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

Annotations already mark read-only/idempotent, and the description adds valuable context: caching behavior ('Cached 5min-1h depending on window'), data provenance ('derived from CF analytics-engine'), and privacy ('no PII, just (pack, tool, count)'). All consistent with annotations and beyond them.

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?

One focused paragraph with a clear opening, a structured list of use cases, and a closing note on data sourcing. The content is relevant and well-organized, though the three use cases could be trimmed slightly without losing meaning.

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?

Covers purpose, return contents, window options, use cases, data provenance, privacy, and caching. Without an output schema, this is sufficient for an agent to correctly select and invoke the tool, and it distinguishes itself from the many sibling tools.

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 sole parameter 'window' is fully documented in the schema (100% coverage) including semantics of shorter vs longer windows. The description merely reiterates the window options and adds cache timing, which does not meaningfully extend parameter understanding beyond the schema. 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?

Description opens with 'What other AI agents are calling on Pipeworx right now' and specifies 'Returns the top tools, top packs, and total call volume over a recent window', using a specific verb and resource that clearly distinguishes it from sibling discovery tools 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?

Provides three explicit use cases ('Useful for: (1) discovering what data sources are hot... (2) confirming a popular tool... (3) seeing whether your use case aligns...'), which give clear context. It does not mention alternatives or when not to use, so it misses the 'exclusions' bar for a 5.

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