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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, but the description adds valuable behavioral context: 'Self-aggregating signal — derived from CF analytics-engine, no PII, just (pack, tool, count)' and 'Cached 5min-1h depending on window.' These disclose data provenance, privacy, and caching behavior 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 structured with a lead sentence stating the primary output, followed by use cases and technical details. Each sentence earns its place: it explains what it returns, why it's useful, what the data is, and how it's cached. No fluff or repetition.

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?

Given no output schema, the description compensates by explaining the output format ('top tools, top packs, and total call volume', 'just (pack, tool, count)'), the time windows, use cases, data source, privacy, and caching. It is complete for an agent to decide whether and how to invoke the tool.

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 covers the only parameter (window) with 100% description coverage, including semantics: 'Shorter windows surface what's hot right now; longer windows show steady-state demand.' The description mentions the window values but adds no additional parametric meaning beyond the schema, so the baseline 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 opens with a clear, specific statement of what the tool does: 'Returns the top tools, top packs, and total call volume over a recent window.' It uses a specific verb ('returns') and resource ('top tools/packs/call volume'), and distinguishes itself from siblings by emphasizing the aggregated, self-referential nature ('What other AI agents are calling on Pipeworx right now').

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 usage scenarios: 'Useful for: (1) discovering what data sources are hot for current events, (2) confirming a popular tool is the canonical choice before asking your own question, (3) seeing whether your use case aligns with what most agents need.' It gives clear context for when to use the tool, though it does not explicitly name alternative tools or state when not to use it.

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