Skip to main content
Glama
KyaniteLabs

checkyourself

by KyaniteLabs
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Validate Artifact

validate
Read-onlyIdempotent

Check inline JSON artifacts against a bundled schema to surface validation errors. Supports scan, coverage, score, backlog, next, diff, report, dashboard, learning-plan, and capabilities.

Instructions

Validate an inline JSON artifact against one bundled CheckYourself schema subset and return validation errors. Supported kinds include scan, coverage, score, backlog, next, diff, report, dashboard, dashboard-data, learning-plan, and capabilities. Requires no authentication. It reads local inputs only, does not make network calls, does not modify local files, and has no external rate limits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindYesBundled schema kind to validate against.
artifactYesInline JSON object to validate. MCP mode does not read a file path for this tool.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed5 schema fields changedv0.1.2
    • addedInput schema / additionalProperties
      Added value: +false
    • addedInput schema / properties / artifact / description
      Added value: +"Inline JSON object to validate. MCP mode does not read a file path for this tool."
    • addedInput schema / properties / kind / description
      Added value: +"Bundled schema kind to validate against."
    • addedInput schema / properties / kind / enum
      Added value: +[
+  "backlog",
+  "capabilities",
+  "challenge",
+  "challenges",
+  "coverage",
+  "dashboard",
+  "dashboard-data",
+  "diff",
+  "learning-plan",
+  "next",
+  "receipt",
+  "report",
+  "scan",
+  "score"
+]
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "description": "Validation result using schema checkyourself-validation/1.",
+  "type": "object"
+}
  2. First observedv0.1.0

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the annotations (readOnlyHint, idempotentHint), the description explicitly states that no authentication is required, it reads local inputs only, makes no network calls, does not modify local files, and has no external rate limits. This provides detailed behavioral transparency that exceeds the annotation hints.

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 compact and well-structured: it front-loads the core function, lists supported kinds, then covers behavioral constraints. Every sentence contributes meaningful information without unnecessary elaboration.

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 an output schema present, the description need not detail return values. It sufficiently covers purpose, acceptable inputs (including the kind enum), and side-effect-free behavior, providing enough context for an agent to decide when and how to invoke the tool.

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 useful clarification for the 'artifact' parameter by specifying it is an inline JSON object and that MCP mode does not read a file path, which helps prevent misuse. This pushes it above baseline.

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 validates an inline JSON artifact against a bundled CheckYourself schema subset and returns validation errors. It names the specific verb, object, and scope, and lists supported kinds, making the purpose unambiguous even without reference to siblings.

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

Usage Guidelines3/5

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

The description explains what the tool does but does not explicitly state when to use it versus alternatives. Sibling tools like 'schema' or 'scan' are not referenced or contrasted, so guidance on selection is only implicit from the tool's described purpose.

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

Deploy Server

Other Tools