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validate_config

Validate job configurations against the Jsoncut API to check schema compliance, resource availability, and token cost before submission.

Instructions

Validate a job configuration against the jsoncut API.

This tool sends the configuration to the API's validation endpoint to check:

  • Schema compliance

  • Resource availability

  • Estimated token cost

  • Any configuration errors

WHEN TO USE:

  • ONLY call this tool if the user has provided actual media file paths (e.g., from uploaded files)

  • DO NOT validate configurations with placeholder paths like "/image/2024-01-15/userXXX/..."

  • Always call this after creating a configuration when real file paths are available

BENEFITS:

  • Catches errors before job submission

  • Provides accurate token cost estimates

  • Verifies that referenced files exist and are accessible

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesJob type: image or video
configYesThe configuration object to validate (from create_image_config or create_video_config)
apiKeyNoAPI key (optional if JSONCUT_API_KEY env var is set)
Behavior3/5

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

No annotations provided, so description carries full burden. It discloses that the tool sends to API validation endpoint and checks various items, but does not mention side effects, rate limits, or potential cost implications beyond token estimation.

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?

The description is well-structured with headings and bullet points, concise, and contains no unnecessary information. Every sentence adds value.

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

Completeness3/5

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

The tool has no output schema, and the description does not explain the return values or response format. It adequately describes the validation checks but lacks completeness regarding output.

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

Parameters4/5

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

Schema coverage is 100%, so baseline is 3. The description adds value by specifying that the 'config' parameter comes from create_image_config or create_video_config, and clarifies that apiKey is optional if env var is set (though schema already notes optional).

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 that the tool validates a job configuration against the jsoncut API, checking schema compliance, resource availability, estimated token cost, and errors. It distinguishes itself from sibling tools (create_image_config, etc.) by being a validation step.

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

Usage Guidelines5/5

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

The description explicitly says when to use: only when the user has provided actual media file paths, not placeholder paths. It also advises to always call after creating a configuration when real file paths are available.

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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