agent-config

Contextual continuity infrastructure for AI agents. Every new AI session starts at zero — no memory of past conversations, no access to your knowledge base, no awareness of your tools. agent-config solves this: when you switch agents, sessions, or even models, the same human's memory, knowledge, and work context carries over.

What this is NOT: not a prompt collection, not a LangChain-style tool-calling automation layer, not a multi-agent orchestration framework. It is the infrastructure that makes any AI agent — regardless of provider — remember who you are and what you've been working on.

Companion repo. agent-config is the reference consumer of pi-shell-acp and the two ship as a pair. pi-shell-acp is the thin bridge: it borrows each backend's identity (Claude Code, Codex) and keeps the operating surface — tools, MCP, skills, permissions — under pi's control. agent-config is what fills that operating surface — extensions, skills, profile, themes, prompts — and proves the bridge against day-to-day work.

Why This Exists

The hardest problem in working with AI agents is not code generation — it's continuity. You build context over hours, then the session ends. Next session: blank slate. Switch from Claude to GPT: blank slate. Move from your laptop to your phone: blank slate.

agent-config attacks this with three layers:

1. Shared memory layer (andenken) — past conversations from every harness + 3,300+ personal notes in a semantically searchable index. Ask "보편 학문 관련 노트 찾아줘" and it finds universalism-tagged notes without being told the English word.

2. Shared skill set — the same capabilities (search notes, read bibliography, check git history, write to journal) available identically whether you're in pi, Claude Code, OpenCode, or OpenClaw.

3. Session continuity protocol — /new + recap + semantic search instead of expensive compact. Start a new session, recover full context in seconds for ~2K tokens instead of re-reading 50K.

The result: context survives across sessions, across harnesses, across models. One human's digital universe stays coherent no matter which AI is looking at it.

Part of the -config ecosystem by glg @junghan0611

The Profile Harness Concept

Claude, GPT, and Gemini are "graduates from different schools" — trained on different data with different philosophies. Trying to control them means writing hundreds of lines of system prompts per model. Instead, throw one being-profile at all of them equally. They keep their unique lenses while aligning around a single universe — this is the Profile Harness.

Multi-harness support is a means, not the goal. The goal is a single 1KB being-profile that exerts the same gravitational pull across any harness.

Harness Support

Session JSONL from all harnesses flows into andenken's unified index. Each chunk carries a source field ("pi" | "claude") so you can filter, compare, or roll back across harnesses.

What's Here

Semantic Memory → andenken

Semantic memory has graduated to its own repo: andenken — "recollective thinking" (Heidegger).

Agents call these autonomously. Ask "보편 학문 관련 노트 찾아줘" and knowledge_search fires with dictcli query expansion — finding universalism-tagged notes without being told the English word.

Pi loads andenken as a compiled pi package (pi install) — direct LanceDB access in-process. Claude Code, OpenCode, OpenClaw, and the pi-shell-acp Claude side use the CLI wrapper skill instead.

Pi Extensions (pi-extensions/)

Semantic memory extension lives in andenken (separate repo, loaded as a pi package).
Telegram bridge lives in entwurf (separate repo, loaded as a pi package).
Production Telegram bridge uses pi-telegram (pi install package).

Entwurf Orchestration → pi-shell-acp

entwurf (delegate/resume), cross-session messaging, and the pi-facing MCP bridge (pi-tools-bridge, session-bridge) all live in pi-shell-acp now. agent-config consumes the surface via pi/settings.json's piShellAcpProvider.mcpServers entry.

Spec, verification harnesses, and the sync/async contract are in pi-shell-acp AGENTS.md § Entwurf Orchestration.

Skills (skills/)

Categories: data access (denotecli, bibcli, gitcli, lifetract, gogcli, ghcli, day-query), agent memory (session-recap, dictcli, semantic-memory, improve-agent), writing (botlog, botment, agenda, punchout), communication (slack-latest, jiracli, telegram), web/media (brave-search, browser-tools, youtube-transcript, medium-extractor, summarize, transcribe), release hygiene (commit, update-changelog), tools (emacs, tmux, diskspace).

Skill doc principle (LSP pattern): Agents don't read full docs. Each SKILL.md has a single API table at the top — function/command + args + example. English body, Korean description only. Target: <100 lines, <4KB. Like LSP autocomplete: see the signature, call immediately.

Pi Config (pi/)

pi-shell-acp Skill Plugin (~/.pi/agent/claude-plugin/)

pi-shell-acp runs Claude with settingSources: [] (SDK isolation), so ~/.claude/skills/ is not auto-discovered. Skills must be injected through the SDK's plugins:[{type:"local", path}] channel — pi-shell-acp exposes this as piShellAcpProvider.skillPlugins.

run.sh setup builds the plugin layout under ~/.pi/agent/claude-plugin/ (manifest + per-skill symlinks back to agent-config/skills/). One operator step per machine: register the plugin root in ~/.pi/agent/settings.json:

"piShellAcpProvider": {
  "skillPlugins": ["/home/junghan/.pi/agent/claude-plugin"]
}

Adding a new skill: drop it into agent-config/skills/<name>/SKILL.md and re-run ./run.sh setup. All four farms — ~/.claude/skills/, ~/.pi/agent/skills/pi-skills/, ~/.pi/agent/claude-plugin/skills/, ~/.codex/skills/ — refresh from the same SSOT.

Themes (pi-themes/)

glg-dark (custom, Ghostty Dracula compatible).

Commands (commands/)

One-Command Setup

git clone https://github.com/junghan0611/agent-config.git
cd agent-config
./run.sh setup    # clone/pull + build CLIs + symlink everything + pnpm install
./run.sh env      # verify: system, API keys, links, binaries, memory index

./run.sh setup performs:

• Clone or fast-forward pull every tracked repo (including andenken and pi-shell-acp)
• Build native CLI binaries (Go + GraalVM)
• Symlink pi extensions, skills (semantic-memory excluded — covered by extension), themes, settings, keybindings
• Install andenken as a pi package (compiled extension)
• Symlink Claude Code / OpenCode / Codex skills + prompts
• Symlink ~/.local/bin PATH binaries
• pnpm install for extensions and skills
• Hand off pi-shell-acp validation (typecheck, MCP, dual-backend smoke, persisted-bootstrap continuity, cancel-cleanup) to pi-shell-acp's own run.sh

Session Management — No Compact

We don't use compact. Compact = AI reads entire conversation and summarizes = expensive + slow.

Instead:

1. When conversation gets long, /new to start fresh
2. /new auto-indexes the current session + the last 24h
3. In the new session, recover context with:
   • session-recap -p <repo> -m 15 → 4KB summary (instant)
   • session_search → semantic search across all sessions
   • knowledge_search → 3-layer expansion over the org knowledge base

Public Verification — Sessions as Evidence

This repo also owns the resident-side policy for publishing session artifacts when GLG wants public verification of harness behavior.

• pi-shell-acp owns bridge mechanism and invariants.
• agent-config owns export/review/upload workflow and publication criteria.
• Goal: long-term trust through evidence — raw-session publication, reject history, and later failure/drift analysis.
• Minimum publication gates: secret redaction, deny patterns, secret scanning (e.g. TruffleHog), semantic privacy review, small-batch dry-run.
• pi-share-hf is a strong reference shape for this pipeline.

Persistent Agent — pi-entwurf

A persistent pi session on Oracle VM, accessible via Telegram @glg_entwurf_bot. The always-on presence agent — a 분신(Entwurf) that carries context across days. tmux session pi-entwurf, model claude-opus-4-6, full skill set.

Two Telegram bridges coexist:

Shell Aliases (~/.bashrc.local)

# Claude Code + Telegram bridge
alias claude-tg='claude --channels plugin:telegram@claude-plugins-official'
alias claude-tgd='claude --channels plugin:telegram@claude-plugins-official --dangerously-skip-permissions'

# pi: --session-control default (async entwurf notifications + inter-session RPC)
alias pi='command pi --session-control'
alias pi-home='command pi --session-control --telegram'

The -config Ecosystem

Skill Source Repos

Changelog

See CHANGELOG.md.

License

MIT