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

Annotations (readOnlyHint=false, destructiveHint=false) indicate a non-destructive write operation. The description adds that it fetches data from cloud providers and stores attributions, which aligns with annotations. However, it does not provide further behavioral context like rate limits, idempotency, or side effects beyond what is implied.

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 concise (3 sentences plus Args and Examples) with clear sections. Every sentence adds value: purpose, precondition, parameter definitions, and usage examples. No superfluous content.

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 covers preconditions and parameters but does not explain the return value (e.g., success message, status). Given no output schema, this is a gap. For a mutation tool, return behavior is important for the agent to confirm execution.

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 description coverage is 0%, but the description provides meaningful context for both parameters: start_date and end_date are ISO dates with defaults (30 days ago, today). This compensates for the lack of schema descriptions and adds clarity on expected date format and default behavior.

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 specifies the verb 'Fetch' and 'store' with clear resource 'tagged cost data' and 'team attributions'. It distinguishes from sibling tools like get_costs_by_team and get_label_costs by indicating this tool actually runs the attribution process rather than just querying results.

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 states a precondition ('after setting up tag_rules.yaml') and provides example usage. It does not explicitly mention when not to use the tool or suggest alternatives, but the context is clear enough for appropriate use.

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