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SeedBase Test Data

by io.github.marcelglaeser

Fetch generation result

fetch_generation
Read-onlyIdempotent

Fetch a previously started generation by id: returns its status, and the SQL INSERT statements once completed. Use this when generate_test_data reported the generation as still running.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
generation_idYesThe generation id (UUID) reported by generate_test_data

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
sqlNoComplete SQL INSERTs. Absent when the result is too large — download it from download_url instead; no partial SQL is ever returned.
statusYes
sql_charsNo
truncatedNoTrue when the SQL was too large to inline. The response then contains NO sql; fetch the complete file from download_url.
download_urlNoAuthenticated download endpoint for the complete SQL (send your API key as 'Authorization: Bearer …').
generation_idYes

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare safe/idempotent behavior. Description adds value by specifying return details (status, SQL INSERT statements) and conditional behavior (once completed), enhancing transparency beyond annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences with no redundancy. Front-loaded with purpose and key details, every word adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With one parameter and presence of output schema, description adequately covers purpose, usage condition, and return type. No gaps for this simple fetch tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema covers 100% of parameter details, so baseline is 3. Description adds no extra parameter information beyond what schema provides, but schema is sufficient.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action (fetch generation by id) and the resource (generation result), explicitly distinguishing from sibling generate_test_data by specifying it retrieves status and SQL INSERT statements.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly advises use when 'generate_test_data reported the generation as still running', providing clear context. Could mention when not to use (e.g., if already completed), but sufficient for guidance.

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

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TDQS

A4.1/5.0
Disambiguation5/5

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.

Naming Consistency4/5

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.

Tool Count5/5

With 6 tools, the server is well-scoped for its purpose of managing test data generation. Each tool is necessary and none feel extraneous.

Completeness4/5

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.

Resources