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

Annotations already declare readOnly, idempotent, openWorld, and destructiveHint=false, but the description adds substantial context: data source (CF analytics-engine), privacy (no PII), exact data shape ((pack, tool, count)), and caching behavior (5min-1h per window). This goes well beyond the annotations and informs the agent about lag, freshness, and response scope.

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 compelling first sentence, a readable bullet-style enumeration of use cases, and a concise operational note on data provenance and caching. Each sentence contributes distinct information, though a few phrases (e.g., '24h, 7d, or 30d') redundantly echo the schema.

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 read-only tool with one optional window parameter and no output schema, the description fully accounts for what the agent needs: it names the return contents (top tools, top packs, total call volume), the window granularity, the data format ((pack, tool, count)), and the absence of PII. There is no significant ambiguity left for the agent to resolve.

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 sole parameter 'window' is fully described in the schema (100% coverage) with enum values and a tradeoff explanation ('Shorter windows surface what's hot right now; longer windows show steady-state demand'). The description merely restates the window options in the first sentence and adds no new semantic meaning beyond the schema, so the baseline 3 applies.

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 returns top tools, top packs, and total call volume over a configurable window, using the specific verb 'Returns' and identifiable resource ('what other AI agents are calling on Pipeworx'). It distinguishes itself from sibling tools like discover_tools by focusing on aggregate agent call behavior rather than individual tool discovery.

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?

An explicit 'Useful for' list provides three concrete scenarios (discovering hot data sources, confirming a canonical tool, checking alignment with agent needs), which gives strong context for when to use it. However, it does not explicitly name alternative tools or state when not to use it, so it misses the full guidance bar for a 5.

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