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
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
ai_ecom_skills-0.1.5.tar.gz
(36.9 kB
view details)
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file ai_ecom_skills-0.1.5.tar.gz.
File metadata
- Download URL: ai_ecom_skills-0.1.5.tar.gz
- Upload date:
- Size: 36.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.11.15
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
850c2b0369b82f029304e79ca49303b5d29cc2ef383ca6d1d7f2aefe7f7db212
|
|
| MD5 |
bc7618c689f1c0ae83995aaaeecf4f62
|
|
| BLAKE2b-256 |
d13565ac5c9efb7687f086badc17f9b5ed0baa0b783edcde3832c629ad232216
|
File details
Details for the file ai_ecom_skills-0.1.5-py3-none-any.whl.
File metadata
- Download URL: ai_ecom_skills-0.1.5-py3-none-any.whl
- Upload date:
- Size: 63.1 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.11.15
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
7df595fe66958815e9188cbef21c9f092e07c1b6d7bd2cd26cf5b8b59993dfd3
|
|
| MD5 |
8261245dda26ddc56e0ca39ee8c5d7d6
|
|
| BLAKE2b-256 |
208454426ed3dd89aa735f264d2a4f69498bd018f320941848860c7ab2d0df23
|