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

Beyond the annotations (readOnlyHint, openWorldHint, etc.), the description adds valuable behavioral context: it is 'Self-aggregating signal — derived from CF analytics-engine, no PII, just (pack, tool, count). Cached 5min-1h depending on window.' This discloses data source, privacy, and caching behavior, enriching the tool's operational understanding.

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 with a clear opening statement and enumerated use cases. Every sentence earns its place, providing high information density without unnecessary fluff.

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 (1 optional parameter) and the description fully covers what it returns, caching behavior, and data privacy. No output schema exists, but the return format is explicitly described ('top tools, top packs, and total call volume'), making it complete for the intended use.

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 has 100% coverage with descriptive text for the 'window' parameter, including default and trade-offs. The description mentions windows but does not add beyond the schema's explanation, so a baseline of 3 is appropriate.

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: 'Returns the top tools, top packs, and total call volume over a recent window (24h, 7d, or 30d).' It uses a specific verb and resource, and distinguishes itself from siblings like discover_tools by focusing on agent call trending.

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, such as 'discovering what data sources are hot for current events' and 'confirming a popular tool is the canonical choice.' While it gives clear context for when to use it, it does not mention when not to use it or name specific alternative tools, so it lacks full exclusionary guidance.

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