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

Beyond the readOnly/idempotent annotations, the description discloses the data source ('CF analytics-engine'), privacy ('no PII, just (pack, tool, count)'), and caching behavior ('Cached 5min-1h depending on window'). This provides meaningful operational context for the agent without contradicting 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 front-loaded with the core purpose, then organized into numbered use cases and a concise data/caching note. Every sentence contributes distinct useful information with no fluff or redundancy.

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 description fully covers a simple read-only tool: what it returns, what the window controls, why it exists, how the data is sourced, and freshness/caching. No output schema is present, but the 'just (pack, tool, count)' statement gives a clear return shape.

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 complete (100%) with an enum and description of window semantics. The tool description adds that cache duration depends on the window, giving a parameter-dependent behavioral nuance not present in the schema. However, it largely repeats the window options already in 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 opens with a specific question ('What other AI agents are calling on Pipeworx right now') and explicitly states it returns top tools, top packs, and total call volume over a recent window. This clearly identifies the resource and differentiates it from sibling tools like discover_tools or search_within.

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' list provides concrete scenarios: discovering hot data sources, confirming canonical tools, and checking alignment with other agents' needs. It also explains window trade-offs ('shorter windows surface what's hot right now; longer windows show steady-state demand'), but does not explicitly name alternatives or when-not-to-use.

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