search_user_metrics

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

No annotations are provided, so the description carries the full burden. It discloses a key behavioral constraint (date range max 7 days, end_date requires start_date, IT Glue rejects open start) and explains what the data represents. However, it doesn't mention read-only safety, auth requirements, or potential rate limits. For a search tool, these missing traits are less critical, but the lack of any explicit safety statement prevents a higher score.

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?

Two sentences, front-loaded with the primary purpose, then adding essential constraints. Every word earns its place, with no repetition of schema details or fluff. The structure is highly efficient and scannable.

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 adequately explains the return value concept (counts grouped by user, organization, resource type, and date bucket). It also covers the critical date constraint. It doesn't detail response formatting or pagination structure, but for a search metrics tool, the provided information is sufficient for an agent to understand what to expect.

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%, so baseline is 3. The description adds value beyond the schema by explicitly stating that end_date requires a start_date and that IT Glue rejects an open start, which the schema does not mention. It also clarifies the 'bucketed by date' semantics, giving a better mental model of how start_date/end_date affect output. This pushes it above baseline.

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 a specific verb and resource: 'Search IT Glue user activity metrics' with detailed specification of what is measured (per-user, per-organization, per-resource-type counts of created/viewed/edited/deleted actions, bucketed by date). This distinguishes it from sibling search tools that target different entities like organizations or configurations. The extra context about being raw data behind reputation scores adds distinctive clarity.

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 clear context for when to use this tool: when you need user activity metrics or the raw data behind IT Glue reputation scores. It doesn't explicitly mention alternatives or exclusions, but the purpose is clear enough to imply the appropriate use case. No sibling tool covers the same domain, so the differentiation is inherent.

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