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Misata Studio: verified synthetic data

Validate a blueprint

validate_blueprint
Read-onlyIdempotent
Check a blueprint before generating it: every error said as what to change, the design traps it
falls into (a column that will round away, a copy of a value not made yet, a window that counts
nothing), its size against your row cap, and a small preview run (a few thousand rows) with the
verifier's findings and sample rows, so you can see the data behave before the real call. Free.

Returns:
    valid, errors (fix these), warnings (read these), estimated_rows, row_cap,
    preview: {passed, findings, tables: {name: first rows}} when `preview`.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
previewNo
blueprintYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, and non-destructive, and the description adds genuinely useful context beyond them: it is 'Free,' the preview runs a few thousand rows, and it describes the verifier's findings and sample rows. It does not cover permissions or rate limits, so 4 rather than 5.

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

Conciseness4/5

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

Front-loaded with the core purpose and benefits, with the Returns block cleanly separated. The parenthetical trap examples are verbose but informative rather than redundant, so it is appropriately sized though slightly dense.

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

Completeness4/5

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

With no output schema, the description carries the return-value burden and does so: it lists valid, errors, warnings, estimated_rows, row_cap, and the preview shape. Safety is covered by annotations. The remaining gap is the unspecified blueprint object structure, but overall an agent has enough to invoke it correctly.

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 description coverage is 0%, so the description must compensate. It explains the `preview` parameter well ('a small preview run (a few thousand rows)'), but the required `blueprint` object (with additionalProperties and nested objects) gets no structural description beyond the general behavior of what is checked. Partial compensation warrants a 3.

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?

States a specific verb and resource ('Check a blueprint before generating it') and enumerates exactly what gets checked: errors, design traps, size against row cap, and a preview run. This clearly distinguishes it from generation siblings like generate_dataset or start_generation.

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?

'before generating it' places it clearly in the workflow ahead of the real generation call. It does not explicitly name alternative siblings (e.g., blueprint_guide) or state when not to use it, so it stops short of a 5.

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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