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

Despite readOnlyHint and idempotentHint annotations, 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'. This informs the agent about data provenance, privacy, and caching without contradicting 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 three sentences with no redundancy. It front-loads the core purpose, then use cases, then technical details. Every sentence adds distinct value, making it highly concise and well-structured.

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?

The tool is simple (one optional param, no output schema), yet the description covers the return format ('top tools, top packs, and total call volume' and 'pack, tool, count'), behavioral traits, and use cases. This is complete for the tool's complexity.

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 single parameter window is fully described in the schema, including semantics ('Shorter windows surface what's hot right now; longer windows show steady-state demand'). The description only adds that caching depends on the window, which is marginal beyond the schema. Baseline 3 is appropriate due to 100% 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 what the tool does: 'What other AI agents are calling on Pipeworx right now' and explicitly lists the outputs ('top tools, top packs, and total call volume'). This specific verb+resource+output formulation distinguishes it from siblings like discover_tools and ask_pipeworx.

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, e.g., 'discovering what data sources are hot for current events' and 'confirming a popular tool is the canonical choice before asking your own question'. However, it does not name alternative tools or specify when not to use it, 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.