mirror of
https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools.git
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b13cb389cc
- API routers, ACA modules, integrations (draft operators) - Docs, landing pages, scripts (launch readiness, scorecard) - Tests and CI workflow updates for Dealix Co-authored-by: Cursor <cursoragent@cursor.com>
110 lines
3.5 KiB
Python
110 lines
3.5 KiB
Python
"""Per-service feature tiers — deterministic."""
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from __future__ import annotations
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from typing import Any
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from auto_client_acquisition.service_tower.service_catalog import get_service_by_id
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_BASE_FEATURES: list[dict[str, Any]] = [
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{
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"id": "intake_self_serve",
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"name_ar": "استقبال ذاتي",
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"tier": "must_have",
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"value_ar": "يبدأ العميل بدون احتكاك.",
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"complexity": "low",
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"risk": "low",
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"proof_metric": "completion_rate",
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"launch_priority": 1,
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},
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{
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"id": "contactability_gate",
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"name_ar": "بوابة contactability",
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"tier": "must_have",
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"value_ar": "يمنع التواصل الخطر.",
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"complexity": "medium",
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"risk": "low",
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"proof_metric": "blocked_risk_count",
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"launch_priority": 1,
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},
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{
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"id": "approval_cards",
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"name_ar": "كروت موافقة",
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"tier": "must_have",
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"value_ar": "لا إرسال خارجي بدون قرار بشري.",
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"complexity": "low",
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"risk": "low",
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"proof_metric": "approval_rate",
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"launch_priority": 1,
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},
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{
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"id": "proof_pack",
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"name_ar": "Proof Pack",
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"tier": "must_have",
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"value_ar": "يثبت العائد أسبوعياً.",
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"complexity": "medium",
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"risk": "low",
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"proof_metric": "revenue_influenced_sar",
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"launch_priority": 2,
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},
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{
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"id": "channel_mix",
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"name_ar": "مزج قنوات آمن",
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"tier": "advanced",
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"value_ar": "إيميل أولاً، واتساب بموافقة/opt-in.",
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"complexity": "high",
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"risk": "medium",
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"proof_metric": "meetings_booked",
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"launch_priority": 3,
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},
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{
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"id": "research_lab_hook",
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"name_ar": "ربط مختبر تحسين",
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"tier": "premium",
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"value_ar": "backlog تحسين أسبوعي.",
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"complexity": "medium",
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"risk": "low",
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"proof_metric": "experiment_win_rate",
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"launch_priority": 4,
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},
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]
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def build_feature_matrix(service_id: str) -> dict[str, Any]:
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svc = get_service_by_id(service_id)
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feats = list(_BASE_FEATURES)
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if svc and svc.get("risk_level") == "high":
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feats.append(
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{
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"id": "extra_compliance_review",
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"name_ar": "مراجعة امتثال إضافية",
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"tier": "must_have",
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"value_ar": "خدمة عالية المخاطر.",
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"complexity": "medium",
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"risk": "high",
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"proof_metric": "compliance_checks",
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"launch_priority": 1,
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}
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)
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return {"service_id": service_id, "features": feats, "demo": True}
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def classify_features(service_id: str) -> dict[str, list[str]]:
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fm = build_feature_matrix(service_id)
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buckets: dict[str, list[str]] = {"must_have": [], "advanced": [], "premium": [], "future": []}
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for f in fm.get("features") or []:
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tier = str(f.get("tier") or "must_have")
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if tier not in buckets:
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tier = "must_have"
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buckets[tier].append(str(f.get("id")))
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return buckets
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def recommend_missing_features(service_id: str) -> list[str]:
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"""Stub: suggest future items."""
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return ["connector_webhooks", "durable_workflows"] if service_id == "growth_os" else []
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def prioritize_features(features: list[dict[str, Any]]) -> list[dict[str, Any]]:
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return sorted(features or [], key=lambda f: int(f.get("launch_priority", 99)))
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