dry_run_deploy

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

Annotations already declare readOnlyHint=true and destructiveHint=false, confirming no side effects. Description adds rich behavioral details: returns specific error/warning categories, lists concrete checks (package.json, reserved table names, auth routes, usage caps), and specifically warns about async footguns (missing await on auth calls). No contradiction with annotations.

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?

Concise, front-loaded with purpose and return values, then logically grouped error and warning categories. Every sentence adds unique value.

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 single parameter, full annotations (readOnlyHint, destructiveHint), and no output schema, the description is complete. It explains what the tool does, what it returns, and specific checks performed.

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 100% with only one required parameter ('project_id'). The description does not add additional semantics beyond what the schema provides. Baseline 3 is appropriate.

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?

Clearly states the tool runs deploy-time validators without deploying, lists return values (errors, warnings, would_deploy), and distinguishes itself from sibling 'deploy' by explicitly noting it does not actually deploy.

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?

Implicitly suggests use before deploying to catch issues, but no explicit when-not-to-use or comparison to other validation tools. The context of avoiding 'deploy blindly' provides good usage context.

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