query_cloud_resources

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

With no annotations, the description must carry behavioral disclosure. It states 'read-only', 'cached rows', and 'Large nested payloads are omitted from the summary; identity/scalar fields are shown as `key=value`'. This discloses that the tool returns a summary format, omitting heavy fields. It does not mention auth requirements or rate limits, but for a read-only query tool, this is reasonable. The description adds meaningful context beyond the schema.

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 well-structured: a concise summary, a prerequisite note, a behavioral note about output, and a clean Args list. Each sentence earns its place. The core purpose and read-only hint are front-loaded, and the parameter details are easy to scan. No fluff or repetition exists.

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?

For a generic query tool with an output schema (so return values are already described), this description is complete. It covers prerequisites, valid values, parameter semantics, pagination (page and page_size), and the output summary format. It even hints at how to handle region-specific behavior (e.g., 'global' for S3). Nothing an agent needs to call it correctly is missing.

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%, so the description must fully document parameters. It does exactly that with an Args list: account_id is tied to list_aws_accounts, service to list_cloud_resource_types, resource_type has examples ('aws_ec2_instance', 'aws_rds_db_instance'), region includes a special 'global' value for S3, and page/page_size have defaults and ranges. This adds substantial meaning beyond the bare schema.

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 opens with 'Query cached rows from any synced AWS resource table (read-only)', which clearly states the verb (query), resource (cached rows from any synced AWS resource table), and the read-only nature. It also calls itself a 'Generic accessor over every supported service', distinguishing it from specific tools like list_ec2_instances in the sibling list. This leaves no ambiguity about what the tool does.

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 instructs to 'Call `list_cloud_resource_types` first to find valid `resource_type` values', providing a clear prerequisite and usage context. It also states it is a generic accessor over every supported service, which implies it is the tool to use when querying any resource type rather than a specific one. However, it does not explicitly contrast it with sibling tools like list_ec2_instances or mention when not to use it, so it lacks explicit exclusions.

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