AI e-commerce skills for Qianchuan advertising operations, compatible with Codex/OpenClaw/Cursor
Project description
ai-ecom-skills
AI e-commerce skills for Qianchuan (巨量千川) advertising operations.
Compatible with Codex, OpenClaw, and Cursor.
Installation
pip install ai-ecom-skills
Quick Start
# Install skill to all platforms (Codex/OpenClaw/Cursor)
python -m ai_ecom_skills.cli install
# Set backend API URL
export BACKEND_API_BASE_URL=http://localhost:8080 # macOS/Linux
set BACKEND_API_BASE_URL=http://localhost:8080 # Windows
# Restart your agent (Codex/OpenClaw/Cursor)
CLI Commands
python -m ai_ecom_skills.cli install # Install to all platforms
python -m ai_ecom_skills.cli install codex # Install to Codex only
python -m ai_ecom_skills.cli install openclaw # Install to OpenClaw only
python -m ai_ecom_skills.cli uninstall # Uninstall from all platforms
python -m ai_ecom_skills.cli list # Show installation status
python -m ai_ecom_skills.cli info # Show skill information
Features
Analysis Skills
- ReviewSummarySkill - Summarize execution results (before/after comparison)
- RiskGuardrailSkill - Check risk policies (kill_switch, budget limits)
- ActionProposalDraftSkill - Generate optimization proposals
Fetch Skills
- FetchPlanCoreContextSkill - Fetch plan basic info
- FetchPlanMetricsSkill - Fetch daily metrics (ROI/cost/GMV)
- FetchPlanHourlyMetricsSkill - Fetch hourly metrics
Execute Skills
- ExecuteAdjustBudgetSkill - Adjust plan budget
- ExecuteAdjustBidSkill - Adjust plan bid
- ExecutePausePlanSkill - Pause an ad plan
Python Usage
from ai_ecom_skills.skills.review_summary import ReviewSummarySkill
from ai_ecom_skills.schemas.agent import AgentTaskRequest
skill = ReviewSummarySkill()
request = AgentTaskRequest(
targetId="plan-001",
context={
"metrics_before": {"roi": 2.5, "cost": 100.0},
"metrics_after": {"roi": 3.8, "cost": 120.0},
"execution_label": "提高预算 20%",
},
)
suggestion = skill.run(request)
print(suggestion.summary)
Requirements
- Python >= 3.11
- Backend API service running (for Fetch/Execute skills)
License
MIT
Project details
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