audit_aws_waste

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 describes the scanning and output but does not disclose whether the tool is read-only, requires permissions, or has any side effects. The behavioral traits beyond the basic operation are not addressed.

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 front-loaded purpose sentence, clear parameter descriptions, and helpful examples. Every sentence adds value without redundancy or 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?

Given the tool's complexity (multiple services scanned) and no output schema, the description adequately covers inputs and high-level output (findings sorted by savings). It could specify the return format more, but it is sufficiently complete for an AI agent.

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?

With 0% schema coverage, the description fully compensates by explaining each parameter: regions (defaults to all opted-in), checks (lists valid values), account_id (auto-discovered). These details add substantial meaning beyond the schema's type information.

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 it performs a deep AWS waste audit scanning EC2, EBS, RDS, Lambda, NAT Gateways, CloudWatch Logs, S3, and CloudTrail, returning findings sorted by monthly savings. This distinguishes it from sibling tools like audit_gcp_waste or more specific audits.

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 example use cases (full audit, specific waste types) but does not explicitly state when to use this tool versus more specific sibling tools like audit_ebs_snapshot_replication or audit_rds_manual_snapshots. Guidance is implied but not explicit.

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