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

Annotations already indicate readOnlyHint=true and destructiveHint=false, and the description adds valuable behavioral context: 'Self-aggregating signal — derived from CF analytics-engine, no PII, just (pack, tool, count). Cached 5min-1h depending on window.' This discloses caching, data source, aggregation, and privacy aspects beyond the annotations.

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 and front-loaded: a one-sentence summary, followed by a returns list, three numbered use cases, and a concise note on aggregation/caching. Every sentence earns its place, with no redundancy or fluff.

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 tool without an output schema, the description adequately explains the return content ('top tools, top packs, and total call volume') and even hints at the data shape ('just (pack, tool, count)'). It does not specify the exact JSON structure, but for a simple trending endpoint this is a minor gap.

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 has 100% coverage with a clear enum description: '24h (default) | 7d | 30d. Shorter windows surface what's hot right now; longer windows show steady-state demand.' The main description only lists the window options without adding further semantic nuance, so it does not exceed the baseline 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 clearly states the tool's function: 'What other AI agents are calling on Pipeworx right now. Returns the top tools, top packs, and total call volume over a recent window (24h, 7d, or 30d).' This uses a specific verb ('Returns') and resource, and distinguishes it from siblings like `discover_tools` by focusing on current trending behavior.

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 tools, and alignment with agent needs. However, it does not name alternatives or state when not to use this tool, so it falls short of the 'explicit when/when-not/alternatives' standard, but the context is clear.

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