| name | ai-fomo-init |
| description | Initialize a personal AI FOMO workspace and Personal Alignment Layer. Use when the user wants to set up an anti-AI-FOMO system, create a source intelligence workspace, configure long-term AI interests, define information value standards, or generate starter workspace templates for AI information judgment. |
AI FOMO Init
Purpose
Create a local Personal Alignment Layer and starter workspace. This skill aligns the agent before any source is summarized, collected, or filed.
Use When
Use this skill when the user asks to:
- set up AI FOMO
- initialize a personal AI alignment workspace
- create an anti-FOMO knowledge workspace
- configure what AI information is worth attention
- generate starter folders and templates
Do Not Use When
Do not use this skill to:
- summarize a specific source
- collect from a source
- write
wiki/sources
- generate a digest from existing material
Use ai-fomo-sources for source intake and ai-fomo for judgment and filing.
Core Workflow
- Choose or confirm the target workspace path.
- Ask the user for a profile brief: resume, bio, portfolio, LinkedIn-style summary, project history, or free-form notes.
- Extract a first-pass alignment map from the profile brief.
- Ask targeted QA to fill only the gaps that matter for AI information filtering.
- Copy the starter workspace from
assets/starter-workspace/ if the user wants files created.
- Write confirmed alignment context into
self-context/.
- Mark weak inferences as draft or pending confirmation.
- End with a short alignment contract summary for the user to review.
Two-Stage Alignment Intake
Stage 1: Profile Brief
Invite the user to provide one or more of:
- resume or CV
- personal bio
- project list
- portfolio notes
- work history
- current goals
- examples of AI content they found valuable or useless
From this, extract only tentative alignment signals:
- role and current work
- long-term themes
- recurring decisions
- technical or product interests
- likely source preferences
- possible downrank patterns
Do not treat these as final until confirmed.
Stage 2: Targeted QA
Ask a small number of focused questions to close gaps. Prefer 3 to 7 questions.
Question areas:
- what decisions the user wants AI information to improve
- which AI topics are high priority now
- which topics are interesting but lower priority
- what kinds of content waste the user's time
- what sources they trust or distrust
- how aggressive the agent should be about skipping material
- what output style is most useful
Do not ask a long onboarding survey. The goal is enough alignment to start, then improve through feedback.
Personal Alignment Layer
The minimum layer should answer:
- who the agent is serving
- what the user is building, studying, or deciding
- which AI themes are high priority
- which content types should be downranked
- what counts as high-signal information
- how feedback should change future filtering
If the user provides too little information, ask concise follow-up questions instead of overfitting.
Output Contract
When initialization finishes, report:
- workspace path
- files created or updated
- confirmed alignment facts from the profile brief and QA
- draft assumptions still requiring user review
- next recommended action: connect sources or process the first source
Safety Rules
- Do not write credentials into the workspace.
- Do not copy private examples into templates.
- Do not infer sensitive personal context unless explicitly provided.
- Do not assume the user's interests match the author's interests.
- Do not treat one-time task goals as long-term preferences.
- Do not turn resume details into public examples or shareable templates.
