mirror of
https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools.git
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bf91167350
1. GTM API Routes: 12 endpoints at /api/v1/gtm/* - company-intelligence, score-target, outreach-pack - compliance-check, classify-reply, next-action - daily-command-pack, targets, approvals - approve-action, log-outcome All registered in router.py 2. Governance Module: 4 files - approval_queue.py: add/approve/reject/get_pending - action_policy.py: policy per action type - audit_log.py: log every proposed action - risk_flags.py: HIGH/LOW risk classification 3. Proof Module: 3 files - evidence.py: VERIFIED/INFERRED/UNVERIFIED/LOW_CONFIDENCE - claim_validator.py: blocks fake claims - source_quality.py: rates source reliability 4. Customer Delivery: 2 files - customer_workspace.py: Pydantic model with onboarding checklist - customer_delivery_pipeline.py: create workspace + weekly report 5. All verified: 9/9 new imports pass, 30/30 evals, dry-run works https://claude.ai/code/session_01W1rJthWDkasijTdXCfxVHs
20 lines
804 B
Python
20 lines
804 B
Python
"""Action policy — decides what requires approval vs auto-allowed."""
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POLICY = {
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"email_send": "semi_auto",
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"linkedin_dm": "manual_required",
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"linkedin_connect": "manual_required",
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"whatsapp_warm": "manual_required",
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"whatsapp_cold": "prohibited",
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"instagram_dm": "manual_required",
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"x_post": "auto_allowed",
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"x_reply": "manual_required",
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"payment_link": "manual_required",
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"partner_terms": "manual_required",
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"claim_result": "manual_required",
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"use_customer_name": "manual_required",
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}
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def check_action(action: str) -> dict:
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level = POLICY.get(action, "manual_required")
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return {"action": action, "level": level, "requires_approval": level in ("manual_required",), "prohibited": level == "prohibited", "reason": f"Policy: {action} is {level}"}
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