create_projectCreate a new, empty SeedBase project. Use import_schema afterwards to add the schema.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Project name | |
| db_type | No | Target database type (default: postgresql) |
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ||
| name | Yes | ||
| db_type | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are all false, so no additional safety cues. The description mentions 'empty' hinting at no initial schema, but does not elaborate on return value or side effects. With no destructive behavior, this is adequate but minimal.
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?
Two concise sentences with no wasted words. Essential information is front-loaded: purpose is stated first, followed by actionable guidance.
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's simplicity (2 params, 1 required), the description is complete: it covers purpose, parameters (via schema), and successor tool. Output schema exists, so return details are covered elsewhere.
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 clear descriptions for both parameters. The description adds no extra parameter meaning beyond what the schema provides, meeting baseline expectations.
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 creates a new empty SeedBase project, with a specific verb ('Create') and resource ('project'). It also implies the distinction from import_schema by directing to use it afterwards.
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 explicitly instructs when to use the tool (to create an empty project) and what to do next ('Use import_schema afterwards'), providing clear workflow guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clearly distinct purpose: creating projects, importing schemas, generating data, fetching generation results, getting DDL, and listing projects. No overlap or confusion possible.
Tool names follow a consistent verb_noun pattern in snake_case, though some verbs are compound (e.g., 'generate_test_data' vs 'create_project'). Minor deviation but overall predictable.
With 6 tools, the server is well-scoped for its purpose of managing test data generation. Each tool is necessary and none feel extraneous.
The set covers the essential workflow: create project, import schema, generate data, fetch results, view DDL. Missing delete or update project, but those are not core to generation.