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Concept: Evaluation | Python: client.eval()

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Parameters

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content
string
required
The AI-generated text to evaluate. Must be 10–10,000 characters.
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mode
string
default:"basic"
Evaluation mode:
  • "basic" — RAIL’s core scoring models for fast, real-time scoring.
  • "deep" — a deeper, more detailed analysis that can also return per-dimension explanations and issue tags.
  • "auto" — runs basic, and automatically escalates to deep only when a real issue is detected (a low-scoring or low-confidence dimension, or a flagged signal). You get fast scoring on clean content and deep analysis exactly where it matters. The response result includes resolved_mode ("basic" or "deep" — which tier actually ran) and escalated (boolean). Billed at the tier that ran.
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dimensions
string[]
Subset of dimensions to score. Omit to score all 8. Options: fairness, safety, reliability, transparency, privacy, accountability, inclusivity, user_impact.
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weights
object
Custom dimension weights. Values must sum to 100. E.g. {"safety": 25, "reliability": 20, ...}.
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domain
string
Domain context hint: "general", "healthcare", "legal", "finance", "code". Improves scoring accuracy.
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include_explanations
boolean
default:"false"
Include per-dimension explanations (deep mode only).
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include_issues
boolean
default:"false"
Include detected issue tags per dimension (deep mode only).
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include_suggestions
boolean
default:"false"
Include improvement suggestions per dimension (deep mode only).

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Request

curl -X POST https://api.responsibleailabs.ai/railscore/v1/eval \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_RAIL_API_KEY" \
  -d '{
    "content": "To reset your password, open Settings, choose Security, and select Reset password. We will email you a secure link that expires in 30 minutes.",
    "mode": "basic"
  }'

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Response

{
  "result": {
    "rail_score": { "score": 7.6, "confidence": 0.51, "summary": "RAIL Score: 7.6/10 — Good" },
    "dimension_scores": {
      "fairness":       { "score": 7.7, "confidence": 0.84 },
      "safety":         { "score": 10.0, "confidence": 0.70 },
      "reliability":    { "score": 7.7, "confidence": 0.16 },
      "transparency":   { "score": 6.5, "confidence": 0.50 },
      "privacy":        { "score": 8.0, "confidence": 0.59 },
      "accountability": { "score": 6.6, "confidence": 0.97 },
      "inclusivity":    { "score": 6.6, "confidence": 0.74 },
      "user_impact":    { "score": 7.8, "confidence": 0.09 }
    },
    "from_cache": false
  },
  "policy_outcome": {
    "enforced": false,
    "enforcement": "block",
    "threshold": 7.0,
    "score": 7.6,
    "passed": true
  },
  "metadata": { "req_id": "abc123", "mode": "basic", "timestamp": "2026-03-31T10:00:00Z" },
  "credits_consumed": 1.0
}
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policy_outcome
object
How your application’s policy judged this result.
  • enforcement — the policy’s mode (log_only, block, or regenerate).
  • threshold — the overall score required to pass.
  • score — this result’s overall score.
  • passed — whether the score met the threshold.
  • enforced — whether the outcome was acted on. When false, the policy is in monitor mode: the verdict is reported but the response is not altered, so you can see what would be blocked. Check the live state with GET /config.
When enforcement is active and a result does not pass, a block policy returns 422 POLICY_BLOCKED and a regenerate policy attempts a safe rewrite before applying its fallback.
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result.rail_score.score
number
Overall RAIL score (0.0–10.0), weighted average of all evaluated dimensions.
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result.rail_score.confidence
number
Model confidence in the score (0.0–1.0).
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result.dimension_scores
object
Per-dimension scores. Each entry has score (0–10) and confidence (0–1). In deep mode: also explanation, issues, suggestions.
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result.from_cache
boolean
true if this result was returned from cache (0 credits charged).
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result.resolved_mode
string
For mode: "auto", the tier that actually ran — "basic" or "deep". Use result.escalated to tell whether the deeper analysis was invoked.
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credits_consumed
number
Credits charged for this request. 0 for cached responses.