get_cost_summary_all_accounts

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

The description discloses the behavior: it fans out across all accounts, combines results, and sorts by total spend. It also explains default values and parameter options. Without annotations, it carries the full burden, and it does well by stating the scope ('ALL configured AWS accounts') and output structure. However, it does not mention whether the operation is read-only or any potential latency, though as a query tool this 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 with a clear opening sentence, followed by an 'Args' section for parameter details and relevant examples. Every sentence adds value; there is no redundancy. The structure is front-loaded with the primary purpose.

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?

Given the tool has three optional parameters, no output schema, and no annotations, the description provides complete context: purpose, scope (all accounts), output format (combined, per-account totals and top services), defaults, and usage examples. It answers what the tool does, what it returns, and how to use it.

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 description provides parameter descriptions under 'Args:' beyond the input schema, including formats (ISO date), defaults (30 days ago, today, MONTHLY), and accepted values for granularity. This adds significant meaning beyond the bare schema, which has no descriptions. The 0% schema coverage is compensated by the inline parameter documentation.

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 fans out cost queries across ALL configured AWS accounts and returns a combined view sorted by total spend, showing each account's total and top services. The verb 'fan out cost queries' and resource 'ALL configured AWS accounts' are specific, distinguishing it from siblings like get_cost_summary which likely operates on a single account.

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 implies usage contexts via examples (e.g., 'Show costs across all my AWS accounts', 'Compare spend across production and staging accounts') but does not explicitly state when to use this tool versus alternatives like get_cost_summary or get_costs_by_service. No exclusions or prerequisites are provided, leaving ambiguity for an AI agent.

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