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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable context beyond that, such as caching behavior ('Cached 5min-1h'), derivation from CF analytics-engine, and no PII. This extra information helps an agent anticipate latency and data sensitivity 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 moderately sized but well-structured: a clear lead sentence, a formatted 'Useful for' numbered list, and a final line on caching/PII. Each sentence earns its place; only minor redundancy exists with the schema's window description.

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?

With no output schema, the description compensates by specifying the exact return shape ('top tools, top packs, and total call volume' and 'just (pack, tool, count)'). It also covers window options, caching, and data source, making it complete for a simple read-only tool. A slight gap is the lack of explicit response structure for 'top packs', but it's sufficient.

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?

Schema coverage is 100% for the only parameter (window), with the schema description already explaining the default and tradeoffs between windows. The tool description mentions the window in the first sentence but doesn't add meaning beyond what the schema provides, so it meets the baseline for fully covered schemas.

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 specific, actionable statement: 'What other AI agents are calling on Pipeworx right now' and explicitly lists the returned data (top tools, top packs, total call volume). This clearly distinguishes it from siblings like discover_tools or ask_pipeworx by focusing on aggregated call-volume trends.

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 'Useful for' section names three concrete scenarios (discovering hot data sources, confirming canonical choices, checking alignment with agent needs). It doesn't mention exclusions or alternative tools, but the context is strong enough to guide appropriate use.

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