dingdawg-compliance

Colorado SB 205 AI Act compliance scanner. Run it in 60 seconds. Get your score. Know your gaps before June 30, 2026.

pip install dingdawg-compliance
python3 -m dingdawg_compliance scan

What it does

Colorado SB 205 requires any company using AI for consequential decisions (employment, housing, credit, insurance, healthcare, education) to:

• Conduct impact assessments before deployment
• Disclose AI use to consumers at point of decision
• Provide appeal and human review mechanisms
• Designate a Responsible AI Officer
• Test for discriminatory bias
• Maintain a 3-year audit trail

This tool scores your readiness across all 25 SB 205 controls. Free. No signup. Runs locally.

Install

pip install dingdawg-compliance

Requires Python 3.9+. No external dependencies — stdlib only.

Usage

Interactive scan (recommended)

python3 -m dingdawg_compliance scan

Walk through all 25 controls. Answer y/n/skip for each. Get your score at the end.

Example output:

──────────────────────────────────────────────────────
  Overall Score: 44/100  [████████░░░░░░░░░░░░]  NEEDS WORK
──────────────────────────────────────────────────────

  Category Scores:
    ~ scope                  100%
    ✗ impact_assessment        0%
    ✗ transparency            33%
    ✗ appeal                   0%
    ~ governance              50%
    ✗ bias_testing             0%
    ✗ data_governance          0%
    ✗ incident_response       50%
    ✓ audit                  100%

  ⚠ Critical gaps (2) — mandatory under SB 205:
    • CO-3   Pre-Deployment Impact Assessment
    • CO-6   Consumer Disclosure at Point of Decision

  Need the full remediation report?
  → dingdawg.com/compliance  (CO SB 205 gap report — $199)

Score from a JSON file

python3 -m dingdawg_compliance score responses.json

Format for responses.json:

{
  "CO-1": true,
  "CO-2": true,
  "CO-3": false,
  "CO-4": null
}

true = implemented, false = not implemented, null = unknown (scored as not implemented).

List all 25 controls

python3 -m dingdawg_compliance controls

Use as a library

from dingdawg_compliance import calculate_co_sb205_score, CO_SB_205_CONTROLS

# Score a self-assessment
responses = {
    "CO-1": True,   # scope: identified consequential decisions
    "CO-3": False,  # impact_assessment: no pre-deployment assessment yet
    "CO-6": True,   # transparency: consumer disclosure implemented
    # ... rest of controls
}

result = calculate_co_sb205_score(responses)
print(result["score"])           # 0-100
print(result["gaps"])            # list of unimplemented controls
print(result["critical_gaps"])   # CO-3, CO-6, CO-10, CO-14 if missing

Track assessments in SQLite

from dingdawg_compliance import ComplianceStore, ComplianceScorer, ComplianceFramework

store = ComplianceStore()  # stored at ~/.dingdawg/compliance/compliance.db

# Register and assess a control
store.assess_control("CO-3", status="COMPLIANT", assessor="legal-team", notes="Completed Q1 2026")

# Score
scorer = ComplianceScorer(store)
print(scorer.overall_posture_score())   # e.g. 72.0
print(scorer.per_framework_score())     # per-framework breakdown
print(scorer.gap_analysis())            # prioritized gap list

Automated checks (read-only)

from dingdawg_compliance import AutoAssessor
from pathlib import Path

assessor = AutoAssessor(
    base_dir=Path("./src"),
    db_paths=[Path("./data/app.db")]
)

results = assessor.run_all_checks()
print(results["checks"]["access_controls"]["summary"])
print(results["checks"]["audit_logging"]["summary"])

The 25 CO SB 205 Controls

... View full README on GitHub