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

The description adds substantial behavioral context beyond the annotations: it states the data is self-aggregating, derived from CF analytics-engine, contains no PII, and is cached for 5min-1h depending on the window. This gives agents crucial information about freshness, privacy, and reliability without contradicting the read-only, idempotent, and non-destructive hints.

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 appropriately sized at three sentences, with the purpose front-loaded in the first sentence, followed by useful use cases and technical notes. Each sentence earns its place, and there is no redundant or fluff content.

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?

Even without an output schema, the description covers the return shape (top tools, packs, volume), the simplified data format (pack, tool, count), and the absence of PII. It also mentions caching behavior. For a simple one-parameter read-only tool, this is sufficiently complete 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 already fully describes the only parameter 'window' with an enum and explanation of short vs long window semantics, achieving 100% schema coverage. The tool description merely repeats the existence of a window without adding additional meaning, so the baseline score of 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 the tool's function: returning top tools, top packs, and total call volume for what other AI agents are calling on Pipeworx. The verb 'returns' and specific resource ('top tools', 'top packs', 'total call volume') make it specific, and it distinguishes itself from siblings like discover_tools by focusing on aggregate trending data rather than individual tool discovery.

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 three explicit use cases (discovering hot data sources, confirming canonical tool choice, aligning use case with agent needs), which is clear context for when to use it. However, it does not explicitly mention alternative tools or provide 'when not to use' guidance, so it falls 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.