run_data_seed

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

No annotations are provided, so the description must fully disclose behavior. It only states that SQL files are run, without mentioning potential destructive actions (e.g., truncating tables), idempotency, permissions required, or success/failure outcomes. This is insufficient for a seed tool that likely modifies data.

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, single-sentence, and front-loaded with the core action. However, it could be restructured to include more behavioral context without adding length.

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 zero parameters, no output schema, and no annotations, the description is minimally adequate. It explains the tool's purpose but lacks details on side effects, return value, or safety of repeated execution. For a seed tool, this context is important for proper use.

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 input schema has zero parameters, with 100% schema description coverage (empty). The description adds no parameter information, but since there are no params, the baseline of 4 is appropriate. No additional value needed.

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 runs all SQL files in data/ and specifies it is the 03-data.ee equivalent with real users, products, and courses. This gives a specific verb and resource. However, it does not differentiate from sibling tools like run_all_seeds or run_base_seed, which may have overlapping functionality.

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?

No guidance is provided on when to use this tool versus alternatives (e.g., run_all_seeds, run_base_seed). There are no prerequisites, exclusions, or context for appropriate use, leaving the agent without decision support.

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