iso-score

@agent-pattern-labs/iso-score

Deterministic weighted rubric scoring for AI-agent workflows.

iso-score turns structured dimension scores into a local, verifiable score artifact. It owns the arithmetic, bands, gate decisions, result ids, and integrity checks. Domain packages still own the rubric and the evidence.

Install

npm install @agent-pattern-labs/iso-score

CLI

iso-score compute --config score.json --input evaluation.json --out score-result.json
iso-score verify --score score-result.json
iso-score check --config score.json --input evaluation.json
iso-score gate --config score.json --input evaluation.json --gate apply
iso-score compare --config score.json --left evaluation.json --right evaluation-alt.json
iso-score explain --config score.json

Config

{
  "version": 1,
  "profiles": [
    {
      "name": "jobfit",
      "scale": { "min": 0, "max": 5, "precision": 2 },
      "dimensions": [
        { "id": "role_fit", "label": "Role fit", "weight": 0.35, "required": true, "minEvidence": 1 },
        { "id": "company_fit", "label": "Company fit", "weight": 0.2, "required": true, "minEvidence": 1 },
        { "id": "comp", "label": "Compensation", "weight": 0.15 }
      ],
      "bands": [
        { "id": "strong", "label": "Strong", "min": 4 },
        { "id": "apply", "label": "Apply", "min": 3 },
        { "id": "skip", "label": "Skip", "min": 0 }
      ],
      "gates": [
        { "id": "apply", "min": 3, "blockOnMissingRequired": true, "blockOnIssues": true }
      ]
    }
  ]
}

Input

{
  "subject": "Example Labs Staff Agent Engineer",
  "profile": "jobfit",
  "dimensions": {
    "role_fit": {
      "score": 4.5,
      "evidence": ["reports/812-example-labs.md:12"]
    },
    "company_fit": {
      "score": 4,
      "evidence": ["reports/812-example-labs.md:18"]
    },
    "comp": {
      "score": 3.5,
      "evidence": ["reports/812-example-labs.md:23"]
    }
  }
}

Result

compute writes a deterministic result with a content-derived id:

{
  "schemaVersion": 1,
  "id": "score:...",
  "profile": "jobfit",
  "subject": "Example Labs Staff Agent Engineer",
  "minScore": 0,
  "maxScore": 5,
  "score": 4.05,
  "normalized": 0.81,
  "band": { "id": "apply", "label": "Apply", "min": 3 },
  "dimensions": [],
  "gates": [
    { "id": "apply", "label": "apply", "pass": true, "reason": "score 4.05 >= 3" }
  ],
  "issues": []
}

The score is computed from normalized dimension scores and normalized weights. Missing optional dimensions are ignored. Missing required dimensions or required evidence produce error issues, and gates can fail closed on those issues.

Library

import {
  checkScore,
  computeScore,
  evaluateGate,
  loadScoreConfig,
  verifyScoreResult,
} from "@agent-pattern-labs/iso-score";

const config = loadScoreConfig(JSON.parse(await fs.readFile("score.json", "utf8")));
const input = JSON.parse(await fs.readFile("evaluation.json", "utf8"));

const result = computeScore(config, input);
console.log(result.score, result.band, result.gates);
console.log(checkScore(config, input));
console.log(evaluateGate(config, input, { gate: "apply" }));
console.log(verifyScoreResult(result));

Boundaries

iso-score does not decide whether a score is true, fair, fresh, or complete. It makes local scoring math deterministic after a domain package has already selected source-backed inputs.

• Use iso-facts to materialize evidence-backed values.
• Use iso-contract to validate the shape of scoring inputs/results.
• Use iso-preflight to consume gate output before dispatch.
• Use iso-ledger to record score events as operational truth.
• Use iso-guard to audit whether scored gates were followed in real runs.