/install personal-api
Personal API — AI Identity Layer for Your Obsidian Vault
30-second elevator pitch: Stop re-onboarding every AI assistant. This skill scaffolds an "API documentation" for yourself inside your Obsidian vault —
ME.mdis your identity contract,AGENT.mdis your behavior contract. Any AI that reads these two files knows who you are, how you think, and how to work with you in under 30 seconds.
Agent-agnostic by design. This is not tied to any single agent runtime. Drop it next to Claude Code, Codex, Cursor, ChatGPT, Gemini, or your own custom LLM agent — it works the same way: a folder convention + two markdown contracts that any LLM can read.
Why This Exists
Every new chat, every new project, every new AI tool — you start from zero. You re-explain your preferences, your tech stack, your communication style, your constraints. By the time the AI is "calibrated," you've burned 10 minutes and a chunk of context window.
Personal API solves this with three primitives:
ME.md— Your single-page identity contract. Read once, AI knows you.AGENT.md— Your behavior contract. Defines the rules of engagement.- A vault navigation layer — When AI needs more depth, it knows exactly where to look.
This is built on a real, battle-tested second-brain system (Knowledge Palace v2) used daily by @beiyuii, not a toy demo.
Methodology — Standing on Six Shoulders
Personal API is not just two markdown templates. It is the entry point to a knowledge architecture that fuses six well-established methodologies:
| Methodology | Core Idea | How We Use It |
|---|---|---|
| PARA (Tiago Forte) | Sort by actionability, not topic | Lifecycle directories: capture → intel → research → notes → frameworks → outputs → archive |
| Johnny.Decimal | Numbered prefixes keep locations stable | 00 / 10 / 20 / … / 90 partitions; topics never need to be re-filed |
| Zettelkasten (Luhmann) | Atomic permanent notes that compound | 40.notes/permanent/ holds only ideas you have genuinely thought through |
| MOC / LYT (Nick Milo) | Maps over deep folders | 40.notes/moc/ gives semantic indexes, decoupled from file structure |
| LLM Wiki (Karpathy) | Strict separation of raw vs compiled | 10.capture/raw/ (raw material) ≠ 40.notes/literature/ (compiled) |
| Memory Palace | Spatial metaphor reduces lookup cost | Each top-level folder is a "room" — you know what is inside before opening |
The core formula:
Folders solve lifecycle. MOCs solve topic membership. Wikilinks solve relationships.
Don't make folders carry semantics. The deeper your folder tree, the harder it is to maintain.
Dual-Track Architecture
The vault has two tracks that don't interfere with each other — this is what makes AI collaboration safe:
| Track | Scope | Maintained By | AI Role |
|---|---|---|---|
| Track A: Identity Archive | ME.md, 00.context/, 10.identity/, 20.skills/, 40.memory-stream/, 50.maps/ |
100% human-curated | Read-only; can suggest but not rewrite |
| Track B: Knowledge Production | Everything under 30.knowledge/ |
AI-led organization, human review | Active librarian — compile, link, archive |
This separation is the contract. Identity is yours. Knowledge production scales with AI.
Directory Structure
your-vault/
│
├── ME.md # ⭐ Layer 0 — Identity entry. AI reads this first.
├── AGENT.md # AI behavior contract
├── README.md # Vault description (for humans)
├── CLAUDE.md # Claude Code instructions (auto-loaded)
├── AGENTS.md # Codex / OpenAI Agent instructions
│
├── 00.context/ # 🟡 Layer 1 — current state (changes fastest)
│ ├── now.md # What I'm working on right now
│ ├── open-questions.md # Unresolved questions
│ └── projects/
│ ├── project-overview.md
│ ├── active/
│ └── archived/
│
├── 10.identity/ # 🔵 Layer 2 — deep identity (rarely changes)
│ ├── values.md # Values & principles
│ ├── vision.md # Long-term vision
│ ├── thinking-models.md # Mental models
│ └── strengths-gaps.md # Strengths & blind spots
│
├── 20.skills/ # 🔵 Layer 2 — capability map
│ └── [skill-name].md # One file per core skill
│
├── 30.knowledge/ # 🟢 Knowledge production (AI-led)
│ ├── 00.system/ # 🏛️ Methodology & rules (this skill installs methodology.md here)
│ ├── 10.capture/ # 📥 Inbox — unprocessed material
│ │ ├── inbox/ # Raw thoughts, links to triage
│ │ └── raw/ # Source material (papers, articles)
│ ├── 20.intelligence/ # 📡 Time-sensitive industry signals
│ │ ├── ai/
│ │ └── business/
│ ├── 30.research/ # 🔬 Long-form research projects
│ ├── 40.notes/ # 🗃️ Note core asset
│ │ ├── literature/ # Compiled literature notes (AI-compiled, human-reviewed)
│ │ ├── permanent/ # Atomic Zettelkasten cards
│ │ └── moc/ # Maps of Content
│ ├── 50.frameworks/ # 🔧 Reusable methods & SOPs
│ │ ├── technical/
│ │ └── operation/
│ ├── 60.projects/ # 📁 Project-bound knowledge
│ ├── 70.outputs/ # 📢 Publishable content
│ └── 90.archive/ # 🗄️ Read-only archives
│
├── 40.memory-stream/ # 📓 Daily logs, reflections, milestones
│ ├── daily/
│ ├── reflections/
│ └── milestones.md
│
└── 50.maps/ # 🗺️ Global navigation
├── index.md # Global hub
└── skills-map.md # Skills overview
Knowledge flow
Capture → Intelligence/Research → Literature notes → Permanent cards/Frameworks → Projects/Outputs → Archive
↕ ↕ ↕ ↕ ↕ ↕
10.capture 20/30 40.literature 40.permanent 60/70 90.archive
50.frameworks
Installation
One-command setup (recommended)
# 1. Point at your vault
export OBSIDIAN_VAULT_PATH="/path/to/your/vault"
# 2. Run the scaffolder
bash scripts/setup.sh
# 3. Open your vault and fill in the [PLACEHOLDER]s in ME.md and AGENT.md
This creates the full Knowledge Palace v2 directory tree, copies the identity templates, and drops a methodology.md into 30.knowledge/00.system/ so AI agents know the rules immediately.
Manual install
cp templates/ME.md "$OBSIDIAN_VAULT_PATH/ME.md"
cp templates/AGENT.md "$OBSIDIAN_VAULT_PATH/AGENT.md"
cp templates/methodology.md "$OBSIDIAN_VAULT_PATH/30.knowledge/00.system/methodology.md"
Usage
After scaffolding, the standard read order for any AI agent is:
ME.md— Layer 0, identity (always)00.context/now.md— Layer 1, current focus50.maps/index.md— Global navigation30.knowledge/00.system/methodology.md— Rules of the knowledge production track
Tell your AI assistant:
"Read my ME.md and AGENT.md to understand my context. Then proceed."
Or, with Claude Code, the rules in CLAUDE.md auto-load — no prompt needed.
Prompt examples
| You say | AI does |
|---|---|
| "Help me file this article." | Reads methodology.md → puts raw material in 10.capture/raw/ → compiles to 40.notes/literature/YYYY-MM-DD-topic.md → proposes permanent-card candidates |
| "What's on my plate?" | Reads 00.context/now.md → returns active projects + open questions |
| "Draft a reply for me." | Reads ME.md + AGENT.md → matches your tone (e.g. terse, structured, opinionated) |
| "Weekly review." | Scans 40.memory-stream/daily/ for the past 7 days → summarizes wins, blockers, lessons |
AI Operation Boundaries
This is the contract. Pin it.
| Action | Allowed? |
|---|---|
| Read any markdown file | ✅ |
Create new files under 30.knowledge/ |
✅ |
Reorganize 30.knowledge/ content |
✅ |
Update 50.maps/index.md links |
✅ |
Update 00.context/now.md (factually) |
✅ (carefully) |
Modify ME.md core identity |
❌ |
Modify 10.identity/ values/vision |
❌ |
| Bulk delete files | ❌ (requires explicit user confirmation) |
Fill in [PLACEHOLDER]s in ME.md |
❌ (the user must answer those) |
Frontmatter Spec
Every meaningful note should have:
---
aliases: [Alias 1, Alias 2] # Obsidian search aliases
updated: YYYY-MM-DD # Last update — critical for freshness signals
layer: 0/1/2 # Identity tracks only (0=core, 1=current, 2=deep)
tags: [tag1, tag2] # Status & type tags
description: One-line summary # AI-readable file purpose
---
Suggested status & type tags:
| Tag | Meaning |
|---|---|
#status/raw |
Unprocessed source material |
#status/compiled |
Literature note (AI-compiled, reviewed) |
#status/permanent |
Permanent atomic note |
#status/published |
External output |
#type/intelligence |
Time-sensitive signal |
#type/research |
Long-form research |
#type/framework |
Reusable method or SOP |
#type/output |
Publication |
Maintenance — Monthly Health Check
Once a month, ask your AI:
"Run a vault health check."
It should scan for:
- Items in
10.capture/inbox/older than 7 days (stale triage) 00.context/files with outdated project status- Orphan notes (no backlinks)
- Missing connections (notes that should link but don't)
- Files with
updated:older than 3 months on important paths
FAQ
Q: How do I migrate my existing notes in?
A: Don't bulk-migrate. Scaffold the structure first, move only what you actively use. Park the rest in 30.knowledge/90.archive/ for traceability.
Q: Do I need frontmatter on every note?
A: Important notes — yes (at least updated: and description:). Captures and quick logs — no, until they get promoted.
Q: Can AI write my ME.md for me? A: No. AI can explain each field, but the answers must be yours. This is your digital twin — fake answers fake the twin.
Q: How is this different from plain PARA? A: PARA is action-oriented. Personal API + Knowledge Palace v2 layers Zettelkasten atomic notes, MOC semantic maps, LLM Wiki raw/compiled separation, and the dual-track contract specifically designed for AI collaboration on top of PARA.
Q: What if my AI ignores the rules?
A: Use a CLAUDE.md / AGENTS.md at the vault root with hard rules ("Track A is read-only"). Most modern AI tools auto-load these.
Q: Privacy?
A: Your filled-in ME.md and AGENT.md contain personal context. Do not commit them to public repos. Add them to .gitignore if your vault is versioned. The skill itself ships only templates, never your data.
Customization
After running setup.sh, edit the templates in your vault. The [PLACEHOLDER] markers show exactly what to fill in. Each field has a comment explaining the intent.
- Update
ME.mdmonthly — identity evolves - Keep
AGENT.mdstable — consistency helps AI assistants - Use
[[wikilinks]]to connect related notes - The
layer:frontmatter helps AI prioritize what to read
Tips
- Don't deepen folders. Three levels max. Use MOCs for topical depth.
- Every capture has a half-life. If
inbox/rots for >7 days, you are capturing too much. - Permanent notes earn their place. A note becomes permanent when it has been linked to twice.
- AI > you at compiling. You > AI at deciding. Let AI drive the literature track. You drive the permanent track.
Related Skills
personal-knowledge-vault— Cross-project entry skill that lets other AI projects pull context from this vaultknowledge-palace-builder— Full step-by-step vault construction guide (the original methodology document)
Credits
Designed and battle-tested daily by @beiyuii. Methodology synthesizes work from Tiago Forte, Niklas Luhmann, Nick Milo, Andrej Karpathy, and Johnny Decimal.
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install personal-api - 安装完成后,直接呼叫该 Skill 的名称或使用
/personal-api触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
Personal API 是什么?
Turn your Obsidian vault into a personal identity layer for AI. Any agent reads ME.md and AGENT.md and instantly knows who you are, how you think, and how to... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 40 次。
如何安装 Personal API?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install personal-api」即可一键安装,无需额外配置。
Personal API 是免费的吗?
是的,Personal API 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Personal API 支持哪些平台?
Personal API 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 Personal API?
由 beiyuii(@beiyuii)开发并维护,当前版本 v2.0.0。