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checkyourself

by KyaniteLabs
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Score Findings

score
Read-onlyIdempotent

Compute a deterministic production-readiness rating from findings and optional coverage evidence, revealing severity counts, penalties, and evidence gaps to guide fixes.

Instructions

Compute a deterministic Production Reality Score from inline findings and optional coverage evidence. Returns score, raw score, confidence, score mode, severity counts, caps applied, per-category penalties, and manual evidence still needed. MCP mode does not write score history. 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
claimNoOptional accepted completion claim. This records the claim but does not execute an independent challenge runner.
coverageNoOptional filled coverage object. Provide this for coverage-backed scoring; omit for scan-derived or finding-only estimates.
findingsYesScan result object, CheckYourself report object, object with findings/remediation_backlog, or a plain list of finding objects to normalize and score.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed7 schema fields changedv0.1.2
    • addedInput schema / additionalProperties
      Added value: +false
    • addedInput schema / properties / claim
      Added value: +{
+  "description": "Optional accepted completion claim. This records the claim but does not execute an independent challenge runner.",
+  "type": "string"
+}
    • addedInput schema / properties / coverage / description
      Added value: +"Optional filled coverage object. Provide this for coverage-backed scoring; omit for scan-derived or finding-only estimates."
    • changedInput schema / properties / coverage / type
      Previous value: -"object"New value: +[
+  "object",
+  "null"
+]
    • addedInput schema / properties / findings / description
      Added value: +"Scan result object, CheckYourself report object, object with findings/remediation_backlog, or a plain list of finding objects to normalize and score."
    • changedInput schema / properties / findings / type
      Previous value: -"object"New value: +[
+  "object",
+  "array"
+]
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "description": "Score result using schema checkyourself-score/1.",
+  "type": "object"
+}
  2. First observedv0.1.0

TDQS

A4.2/5.0
Behavior5/5

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

The description discloses key behavioral traits beyond the annotations, including determinism, no score history writes in MCP mode, no network calls, no file modifications, and no external rate limits. These details align with the readOnly and idempotent hints, providing concrete assurance of side-effect-free operation.

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?

The description is well-structured with a clear purpose statement, a list of return values, and a separate paragraph for behavioral constraints. It is slightly verbose with some redundancy (e.g., 'reads local inputs only' and 'does not make network calls') but remains efficient overall.

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?

The description provides sufficient context for an agent to understand the tool's inputs, outputs, and side effects. Since an output schema is present, the return value list is supplemental. All relevant information is covered, making it complete for safe invocation.

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?

The schema already provides descriptions for all three parameters, so the baseline is met. The tool description adds context that coverage is optional and findings are the primary input, but does not significantly enhance the parameter meaning beyond the schema.

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 function: computing a deterministic Production Reality Score from findings and optional coverage. The verb 'compute' and specific resource 'Production Reality Score' make it distinct from sibling tools like scan or coverage_check.

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 specifies the input conditions (findings required, coverage optional) but does not explicitly mention any alternative tools or when not to use this tool. It implies usage when a score is needed from provided findings, but lacks direct comparison with sibling tools.

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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