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

Beyond the readOnlyHint and idempotentHint annotations, the description adds valuable behavioral context: the data is self-aggregating, derived from CF analytics-engine, contains no PII, is cached for 5min-1h depending on window, and the output shape is (pack, tool, count). This goes well beyond the annotations and gives the agent an accurate mental model.

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 well-structured, front-loaded with the core function, then use cases, then data-source/caching details. It's slightly longer than strictly necessary but every sentence adds information; the bulleted use cases make it scannable.

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 read-only tool with a simple single-parameter schema, the description fully explains what is returned, the data source, the caching behavior, privacy characteristics, and why the tool is useful. There's no output schema, so the description's description of return contents is essential and sufficient.

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 input schema fully documents the single 'window' parameter, including its enum values and the trade-off between shorter and longer windows. The description repeats the enum values but adds no additional syntax or formatting guidance, so it's at the baseline 3 for high schema coverage.

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 states a specific verb and resource: 'returns the top tools, top packs, and total call volume' for Pipeworx, based on what other AI agents are calling. This clearly distinguishes it from sibling tools like discover_tools or ask_pipeworx, focusing on aggregate trending signals.

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 enumerates three concrete use cases: discovering hot data sources, confirming canonical tool choice, and checking alignment with other agents. It provides strong context but does not name alternatives or state when not to use this tool, so it misses the full 'when-to-use vs alternatives' bar.

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