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ck_skill_validate

Read-onlyIdempotent

Validate skill output against a JSON Schema to enforce typed, structured results. Accepts output with schema or skill name to use built-in schema.

Instructions

Validate skill output against a JSON Schema defined in the skill's result-schema frontmatter field. Skills can define a result_schema in their frontmatter; agents call this tool after running a skill to enforce typed, structured output. Accepts output + schema directly, or output + skill_name to validate against the skill's built-in schema.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
outputYesThe skill output to validate. Can be a JSON string or plain text, up to 100KB.
project_rootNoAbsolute path to the project root. Only used when skill_name is provided.
schemaNoJSON Schema as a string to validate against. Required if skill_name is not provided.
skill_nameNoOptional skill name to use the skill's built-in result_schema. If provided, schema is not required.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorsNo
skill_nameNo
validNo
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, so the description adds value by explaining the two validation paths and the source of the schema (frontmatter). No contradictions.

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 three sentences, front-loads the core action, and contains no redundant words. It is well-structured and efficient.

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?

Given the tool's complexity (4 params, output schema, annotations), the description covers the two main usage scenarios adequately. It does not detail error handling, but the output schema likely provides that. No major gaps.

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%, with each parameter already described. The description adds semantic value by explaining the two usage modes (output+schema vs output+skill_name), which clarifies the relationship between parameters beyond schema descriptions.

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 tool's purpose: validate skill output against a JSON Schema. It specifies the two modes (direct schema or built-in schema via skill_name), providing a specific verb+resource combination.

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?

The description explicitly says agents call this tool 'after running a skill to enforce typed, structured output,' providing clear context for when to use it. It does not mention when not to use it or alternatives like ck_validate, but the guidance is sufficient.

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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