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

Beyond the readOnlyHint, openWorldHint, idempotentHint, and destructiveHint annotations, the description reveals valuable behavioral traits: it is a 'self-aggregating signal' derived from the CF analytics-engine, guarantees 'no PII', returns only '(pack, tool, count)', and is cached for 5min-1h depending on window. This additional context about data provenance, privacy, and freshness goes far beyond the annotations and clearly informs the agent.

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 efficiently structured: the lead sentence states the core output, the second sentence lists concrete use cases, and the third adds technical context about data source, PII, and caching. It is slightly longer than strictly necessary, but every sentence contributes distinct value and it is front-loaded with the primary purpose. This earns a 4 rather than a 5.

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 the tool's simplicity (one optional parameter, no output schema), the description covers the essential aspects: what is returned, how to choose the window, use cases, and data freshness. It does not specify the exact output format or edge cases, but the mention of '(pack, tool, count)' and the absence of an output schema make it sufficiently complete for a straightforward read-only trending 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 input schema already provides 100% coverage for the only parameter (window) with an enum and a detailed description differentiating short vs. long window semantics. The tool description merely repeats the allowed values without adding new meaning, so the baseline of 3 is appropriate. It does not enrich the parameter's semantics beyond the schema.

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 what the tool does: 'Returns the top tools, top packs, and total call volume' over a recent window, making the specific verb and resource explicit. It distinguishes itself from siblings like discover_tools by focusing on what other AI agents are calling on Pipeworx, a unique aggregative signal. The purpose is unmistakable.

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 when-to-use guidance via three enumerated use cases, such as confirming a popular tool is canonical or aligning with agent needs. It also gives window-selection guidance ('Shorter windows surface what's hot right now; longer windows show steady-state demand'). However, it does not mention when not to use the tool or explicitly name alternative sibling tools, so it stops short of a full 5.

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