validate_project

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

Beyond the annotations, the description discloses that runtime, examples, tests and release query the warehouse and may build a seeded DuckDB file, plus the special prerequisite for impact. This gives the agent important behavioral expectations that annotations alone do not capture. The idempotent/read-only annotations are not contradicted; building a seeded file is presented as a side effect consistent with a non-destructive cache-like operation.

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?

Three compact sentences deliver the purpose, recommended usage order, and important gotchas with zero filler. The main purpose is front-loaded and every clause adds useful information.

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 output schema exists, the description need not explain return values. The mode list, usage order, warehouse side-effect warning, and impact prerequisite cover the behavioral and invocation context an agent needs to call the tool correctly. The required project_path is simple enough to leave to the schema.

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 carry parameter meaning. It effectively explains the valid mode values and the relationship between impact, compare_path, and base_ref. It does not explicitly describe project_path or environment, though their names and the context make their roles reasonably inferable.

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 action ('Validate the package') and enumerates the distinct modes (parse, runtime, examples, tests, impact, release). This makes it easy for an agent to distinguish validation from sibling tools like project_status or preview_query.

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?

It gives explicit usage directives: use parse after each change, and run runtime before trusting answers. It also notes that impact requires compare_path or base_ref, providing meaningful when-to-use context. It stops short of saying when not to use this tool or how it compares with alternative tools.

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