ai_usage_log_query

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

No annotations provided, so description carries full burden. Mentions 'returns detailed rows' but does not disclose pagination behavior, side effects (presumably read-only), auth requirements, or rate limits. Basic transparency but incomplete.

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: first states action, second specifies filters and return type. No redundant words, front-loaded with purpose. Highly concise.

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 9 parameters, no output schema, and no annotations, the description is too minimal. Omits details on pagination (limit/offset), billing filter (billed_only), connection handling, and result format. Incomplete for a complex query tool.

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 low (33%), and description adds value by listing filterable fields (tenant, state, source, date range) but does not explain all 9 parameters (e.g., connection, billed_only, limit, offset). Partially compensates but not fully.

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?

Description clearly states 'Query the AI usage billing ledger' with specific filterable dimensions (tenant, state, source, date range) and return type ('detailed rows for audit + monthly reconciliation'). Distinguishes from siblings like ai_usage_log_export and ai_usage_log_stats by focusing on querying detailed rows.

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?

Description implies usage for 'audit + monthly reconciliation' but does not explicitly contrast with sibling tools (e.g., when to use this vs ai_usage_log_export or ai_usage_log_stats). No when-to-use or when-not-to-use guidance.

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