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

Beyond the annotations (readOnlyHint=true, etc.), the description adds valuable behavioral context: it explains the data source ('derived from CF analytics-engine'), privacy ('no PII'), output format ('just (pack, tool, count)'), and caching behavior ('Cached 5min-1h depending on window'). This fully discloses operational characteristics.

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: the first sentence states the core purpose, followed by return details and a numbered list of use cases. While the numbered list adds length, each item is purposeful and helps the agent decide when to use the tool. It is slightly verbose but not wasteful.

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 simple tool with one optional parameter and no output schema, the description is complete. It explains the input window choices, return contents (top tools, packs, call volume), use cases, data provenance, privacy, and caching. There are no significant gaps; an agent could invoke it correctly without further clarification.

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 already provides 100% coverage for the single 'window' parameter, including enum values and semantic guidance ('Shorter windows surface what's hot right now; longer windows show steady-state demand'). The description adds only minor extra context about caching varying by window, so baseline 3 is appropriate given the schema's completeness.

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 with a specific verb and resource: 'What other AI agents are calling on Pipeworx right now' and then details output ('top tools, top packs, and total call volume'). It distinguishes itself from siblings like discover_tools by emphasizing real-time aggregated usage trends rather than static tool listings.

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 use cases ('Useful for: 1, 2, 3'), giving clear context on when to use the tool. However, it does not mention alternatives or explicitly state when NOT to use it, so it falls short of the highest bar requiring exclusions/alternatives.

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