Install
$ agentstack add skill-kangise-ecommerce-ai-skills-ecom-social ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Social Media Skill
When to Use
Create and optimize e-commerce social media content and advertising across platforms. Use for content creation (Reels, Shorts, Stories, Carousel, Pin, 种草笔记), posting strategy, hashtag research, ad copy, influencer collaboration, community management, or cross-channel repurposing.
Method
Step 1: Read Platform Constraints
Read references/constraints.md for platform-level rules. Social media has no numeric constraints in the ontology yet — platform-specific best practices live in each chapter's prompt templates in the playbook.
Step 2: Review Boundaries
Read references/boundaries.md to know when this skill should NOT be used (e.g. no visual story, no local-language capacity, chasing this-month conversion, mechanical reposting).
Step 3: Pick the Prompt
Pick the appropriate prompt from references/playbook.md for your platform and scenario:
- e1 — Instagram/Facebook: Reels, Stories, Carousel, Shopping, Meta Ads, hashtags, influencer collaboration
- e2 — YouTube: SEO keywords, titles, scripts, Shorts, thumbnails, affiliate descriptions
- e3 — 小红书: 种草笔记, SEO, 达人合作, 算法优化, 数据分析
- e4 — Pinterest: SEO, Pins, Idea Pins, Shopping, seasonal calendar, Shopping Ads
- e5 — WhatsApp: 客服 AI, chatbot flows, 复购营销, sales assistant
- e6 — Reddit: community participation, Ads, reputation monitoring, GEO
- e7 — Cross-channel: content adaptation, weekly repurposing, cross-platform analytics, attribution
Step 4: Execute and Verify
Execute the prompt with your data. Use the // self-check block in each prompt to verify output quality before delivering results.
References
- [Constraints](references/constraints.md) — Platform rules and limits
- [Playbook](references/playbook.md) — Prompt collection (54 prompts, e1–e7)
- [Boundaries](references/boundaries.md) — When not to use
Templates
Copy-ready prompt templates (in assets/templates/):
- [Instagram Reels Scripts](assets/templates/template-1-instagram-reels-scripts.md)
- [YouTube Video Description](assets/templates/template-2-youtube-video-description.md)
- [小红书种草笔记](assets/templates/template-3-xiaohongshu-seeding-note.md)
- [Cross-Channel Content Adaptation](assets/templates/template-4-cross-channel-adaptation.md)
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: kangise
- Source: kangise/ecommerce-ai-skills
- License: CC0-1.0
- Homepage: https://kangise.github.io/ecommerce-ai-skills/
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.