run_base_seed

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

No annotations are provided, so the description carries full burden. It states the tool 'runs all SQL files', implying execution but does not disclose side effects (e.g., whether it is destructive, requires authentication, or impacts existing data). This is insufficient for behavioral transparency.

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 a single sentence with no wasted words, front-loaded with the verb 'runs'. It is appropriately concise for the tool's simplicity.

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 has no parameters, no output schema, and no annotations, the description is minimal. It explains what is run but lacks information about expected outcomes, return values, or post-execution state. For a zero-parameter tool, it is adequate but not complete.

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% coverage. Per guidelines, baseline is 4. The description adds context about what is executed (base/ files with real data), which adds meaning beyond the 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 clearly states the tool runs all SQL files in the base/ directory, specifying it is equivalent to 02-base and uses real natuleadan company data. This distinguishes it from sibling tools like run_all_seeds and run_data_seed by being specific about scope and data.

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 implies usage for running base seed data, but provides no explicit guidance on when to use this tool versus alternatives like run_all_seeds or run_data_seed. The context of 'real natuleadan company data' gives some direction, but without exclusion criteria, the guidance is minimal.

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