Vibe Coding Conversation Writer
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Please install @user_8442eada/jeason2 according to https://skillhub.cn/install/skillhub.md.
About this skill
Many AI coding sessions leave decisions, debugging paths, tool calls, and deliverables scattered across chat history. This skill turns that session context into a structured article-writing workflow.
What it addresses
It focuses on turning a Vibe Coding session into publishable technical content while preserving real decisions and failures. It suits feature builds, debugging retrospectives, AI collaboration notes, or marketing case studies.
How it works
The skill first collects conversation context: initial goals, key technical choices, pitfalls, final artifacts, and noteworthy vibe moments. It may also infer project metadata such as tech stack, file count, turns, and tool usage. Then it selects a template based on the session shape: practical case study for delivered work, experience narrative for human-AI collaboration, methodology extraction for reusable patterns, or industry insight for broader positioning. Writing is expected to explain why a choice was made, cite concrete numbers where available, keep honest debugging details, and land in a suggested 3000~6000 word range. The output is a Markdown file.
Boundaries
It depends on the current session context and should not invent metrics. Sensitive items such as API keys or internal system names should be sanitized.
Use Cases
- After finishing a feature build, turn decisions, pitfalls, and artifacts into a blog post.
- After an AI coding session, write the collaboration experience and key choices as a narrative.
- When a dev case needs promotion, generate a marketing draft with trend-level framing.
- Turn weekly AI coding notes into publishable Markdown retrospectives using article templates.
Best For
- Independent developers who want to turn AI development sessions into publishable blogs.
- Product managers who need to convert dev case studies into promotional and insight drafts.
- Engineers sharing Vibe Coding workflows who want pitfall-to-breakthrough narratives.
- Tech leads in small teams who need project experience turned into case studies.
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