Name: Dingdawg Compliance
Author: dingdawg

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

bash

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

bash

pip install dingdawg-compliance

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

Usage

Interactive scan (recommended)

bash

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

bash

python3 -m dingdawg_compliance score responses.json

Format for responses.json:

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

bash

python3 -m dingdawg_compliance controls

Use as a library

python

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

python

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)

python

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

ID	Category	Control	Critical
CO-1	scope	Consequential Decision Identification
CO-2	scope	High-Risk AI System Classification
CO-3	impact_assessment	Pre-Deployment Impact Assessment	★
CO-4	impact_assessment	Annual Impact Assessment Review
CO-5	impact_assessment	Impact Assessment Documentation
CO-6	transparency	Consumer Disclosure at Point of Decision	★
CO-7	transparency	Disclosure Timing
CO-8	transparency	Disclosure Content — AI Role
CO-9	transparency	Disclosure Content — Data Used
CO-10	appeal	Appeal Mechanism	★
CO-11	appeal	Human Review Option
CO-12	appeal	Opt-Out Mechanism
CO-13	appeal	Appeal Response Timeline
CO-14	governance	Responsible AI Officer Designation	★
CO-15	governance	AI Inventory
CO-16	governance	Vendor Due Diligence
CO-17	governance	Policy Documentation
CO-18	bias_testing	Pre-Deployment Bias Testing
CO-19	bias_testing	Ongoing Bias Monitoring
CO-20	bias_testing	Protected Class Analysis
CO-21	data_governance	Training Data Documentation
CO-22	data_governance	Data Minimization
CO-23	incident_response	AI Incident Response Plan
CO-24	incident_response	Error Notification
CO-25	audit	Third-Party Audit Trail

★ Critical — mandatory remediation required before June 30, 2026.

What this doesn't include

This scanner shows what to check and where your gaps are. It does not generate remediation plans, regulatory citations, evidence templates, or audit-ready documentation.

For the full gap report with remediation guidance → dingdawg.com/compliance