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agentic-stack

Keep one portable memory-and-skills layer across coding-agent harnesses, so switching tools doesn't reset how your agent works.

A portable .agent/ folder (memory + skills + protocols) that plugs into Claude Code, Cursor, Windsurf, OpenCode, OpenClaw, GitHub Copilot CLI, Google Gemini CLI, Hermes, Pi Coding Agent, Codex, Antigravity, or a DIY Python loop — and keeps its knowledge when you switch.

It also includes a local data layer so you can monitor the whole suite of agents from one place: harness activity, cron runs, active agents, token/cost estimates, KPI summaries, user-defined resource categories, and screenshot-ready daily dashboards.

And it can turn approved, redacted runs into local flywheel artifacts: trace records, context cards, eval cases, training-ready JSONL, and readiness metrics without training a model or sending telemetry.

New in v0.18.0 — external Brain memory integration

Minor release. Adds an optional bridge to codejunkie99/brain, the external git-backed long-term memory CLI/TUI/MCP server, without vendoring Brain's Rust workspace into agentic-stack.

agentic-stack brain .... Check Brain status, onboard a project, search global memory, write durable notes, run Brain doctor/TUI, or print the MCP stdio command from the normal agentic-stack CLI.
Project bridge. Installed .agent/ projects now include .agent/tools/brain_bridge.py, so host agents can call Brain explicitly when a task needs cross-project recall.
Brain seed skill. A new brain skill teaches agents when to query or write Brain memory, and keeps secret handling explicit.

See CHANGELOG.md for the full list.

v0.17.0 — adapters, Mission Control, and lesson retraction

Minor release. Clears the open PR queue and ships the combined production surface from Copilot CLI, Gemini, Mission Control, and semantic lesson retraction work.

v0.16.1 — getting-started refresh

Patch release. Ships the production-ready getting-started guide from PR #49 and fixes onboarding version drift in the first-run banner.

v0.16.0 — safe project upgrades

Minor release. Adds agentic-stack upgrade and agentic-stack sync-manifest so installed projects can pick up new .agent infrastructure and skill metadata without clobbering adapter settings or user memory.

Safe upgrade command. Run agentic-stack upgrade --dry-run to preview skeleton-owned .agent file updates, then agentic-stack upgrade --yes to apply them.
Manifest repair. Run agentic-stack sync-manifest to rebuild .agent/skills/_manifest.jsonl from installed SKILL.md frontmatter.
No config overwrite. Upgrade leaves CLAUDE.md, .claude/settings.json, personal/semantic/episodic/working memory, candidates, and existing skill directories untouched.
Stricter doctor. agentic-stack doctor now warns when Claude Code hook commands point to missing .agent files or hook scripts are present but unwired.

v0.12.0 — tldraw visual canvas

Minor release. Adds an opt-in tldraw seed skill for live canvas diagrams and a skill-local snapshot store. It is beta and off by default.

tldraw seed skill. Draw, diagram, sketch, wireframe, flowchart, and whiteboard on a live canvas at http://localhost:3030 through an MCP server.
Skill-local snapshots. Save worthwhile canvases with .agent/skills/tldraw/store.py snapshot; list, load, and archive them later without treating them as a fifth memory layer.
Opt-in beta. Onboarding writes tldraw.enabled: false by default. After enabling it, users manually merge adapters/_shared/tldraw-mcp.json into their harness MCP config.

v0.11.0 — data layer + data flywheel

Added two local-first data capabilities for teams running multiple agent harnesses against the same .agent/ brain.

data-layer seed skill. Generate local dashboard exports across Claude Code, Hermes, OpenClaw, Codex, Cursor, OpenCode, and custom loops: harness events, cron timelines, KPI summaries, token/cost estimates, categories, dashboard.html, and daily-report.md. The skill also acts as the injected natural-language surface for showing the terminal dashboard.
data-flywheel seed skill. Export approved, redacted runs into trace records, context cards, eval cases, training-ready JSONL, and flywheel metrics. It is local-only and model-agnostic; it prepares artifacts but does not train models or call external APIs.

v0.10.0 — design-md skill + Python 3.9 fix

Added the design-md seed skill for root DESIGN.md / Google Stitch workflows, and fixed the Python 3.9 crash that hit macOS-default brew users on first run.

v0.9.1 — pi adapter fixes + tz correctness

Closed the gap between v0.9.0 and a working pi adapter, plus a timezone sweep across every Python writer/reader so the dream cycle stops drifting against the UTC decay window.

v0.9.0 — harness manager

Manifest-driven adapter system: every harness is now declared by an adapter.json, applied by a shared Python backend, and managed via verb subcommands or an interactive TUI. Cross-platform (POSIX + Windows) with concurrent-write protection, pre-v0.9 migration via ./install.sh doctor, and shared-file ownership tracking so removing one adapter never orphans another.

Made by https://x.com/Av1dlive

Quickstart

macOS / Linux

# tap + install (one-time — both lines required)
brew tap codejunkie99/agentic-stack https://github.com/codejunkie99/agentic-stack
brew install agentic-stack

# drop the brain into any project — the onboarding wizard runs automatically
cd your-project
agentic-stack claude-code
# or: cursor | windsurf | opencode | openclaw | copilot-cli | gemini | hermes | pi | codex | standalone-python | antigravity

Windows (PowerShell)

# clone + run the native installer
git clone https://github.com/codejunkie99/agentic-stack.git
cd agentic-stack
.\install.ps1 claude-code C:\path\to\your-project

Already installed?

brew update && brew upgrade agentic-stack
agentic-stack dashboard

Clone instead?

git clone https://github.com/codejunkie99/agentic-stack.git
cd agentic-stack && ./install.sh claude-code         # mac / linux / git-bash
# or on Windows PowerShell: .\install.ps1 claude-code
# adapters: claude-code | cursor | windsurf | opencode | openclaw | copilot-cli | gemini | hermes | pi | codex | standalone-python | antigravity

Once installed: manage what's wired

After the first ./install.sh <adapter>, manage your project with verb-style subcommands (works with both install.sh and install.ps1):

./install.sh dashboard           # TUI dashboard: health, verify, memory, team, skills, instances
./install.sh mission-control     # beta local web dashboard; Ctrl-C turns it off
./install.sh brain status        # optional external Brain CLI integration
./install.sh add cursor          # add a second adapter (Claude Code + Cursor in same repo)
./install.sh status              # one-screen view: which adapters, brain stats
./install.sh doctor              # read-only audit; green / yellow / red per adapter
./install.sh manage              # interactive TUI: header pane + menu loop for add/remove/audit
./install.sh transfer            # onboarding-style wizard: export/import memory as a curl bridge
./install.sh upgrade --dry-run   # preview safe .agent infrastructure refresh
./install.sh upgrade --yes       # copy latest harness/memory/tools + new skills
./install.sh sync-manifest       # rebuild .agent/skills/_manifest.jsonl from SKILL.md frontmatter
./install.sh remove cursor       # confirm prompt + delete; no quarantine, no undo

PowerShell uses the same verbs, for example .\install.ps1 dashboard.

Optional: external Brain integration

codejunkie99/brain is the git-backed long-term memory binary and MCP server. agentic-stack now treats it as an optional external memory layer instead of vendoring its Rust workspace.

Install Brain first:

brew install codejunkie99/tap/brain

Then check or wire it from a project:

agentic-stack brain status
agentic-stack brain onboard --agents codex,cursor --yes
agentic-stack brain ask "auth decisions"
agentic-stack brain note "Use PKCE for local OAuth flows."
agentic-stack brain mcp-command

Installed .agent/ projects also get python3 .agent/tools/brain_bridge.py and a brain seed skill so host agents can query or write Brain memory when a task needs cross-harness long-term recall.

Bare ./install.sh (no arguments) opens a multi-select wizard on a fresh project — check every harness you actually use, hit enter, each one gets installed. The wizard auto-detects harnesses already on disk and pre-checks them. On a project that already has an install.json, bare interactive ./install.sh opens the dashboard. In non-TTY shells (CI), it stays script-safe and prints the available subcommands instead of opening a TUI.

Upgrading from pre-v0.9? Run ./install.sh doctor first — it synthesizes install.json from on-disk adapter signals so the new backend can track them. Installing on top without migration would orphan the prior installs.

Upgrading an already-installed project after brew upgrade? Run agentic-stack upgrade --dry-run in the project first, then agentic-stack upgrade --yes to refresh only skeleton-owned .agent infrastructure (harness/**/*.py, top-level memory/*.py, tools/*.py, the generated skill index, and new skill directories). It does not rewrite CLAUDE.md, .claude/settings.json, personal/semantic/episodic/working memory, candidates, or existing skill directories. agentic-stack sync-manifest is available as a repair command if _manifest.jsonl drifts from installed SKILL.md files.

Onboarding wizard

If you ran bare ./install.sh (no adapter name), the wizard starts with a multi-select harness step: it lists all 12 adapters, pre- checks any it detects on disk, and installs each one you confirm with space + enter. After the install(s), the preferences flow runs.

If you ran ./install.sh <adapter> directly, only the preferences flow runs.

Either way, the preferences step populates .agent/memory/personal/PREFERENCES.md — the first file your AI reads at the start of every session — and writes a feature-toggle file at .agent/memory/.features.json.

Six preference questions (each skippable with Enter):

Question	Default
What should I call you?	(skip)
Primary language(s)?	`unspecified`
Explanation style?	`concise`
Test strategy?	`test-after`
Commit message style?	`conventional commits`
Code review depth?	`critical issues only`

Plus one Optional features step (opt-in, off by default):

Feature	Default
Enable FTS memory search `[BETA]`	`no`
Enable tldraw visual canvas `[BETA]`	`no`

Flags:

agentic-stack claude-code --yes          # accept all defaults, beta off (CI/scripted)
agentic-stack claude-code --reconfigure  # re-run the wizard on an existing project

Edit .agent/memory/personal/PREFERENCES.md any time to refine your conventions, or `.agent/mem

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agentic-stack

Live repository statistics

README preview

agentic-stack

New in v0.18.0 — external Brain memory integration

v0.17.0 — adapters, Mission Control, and lesson retraction

v0.16.1 — getting-started refresh

v0.16.0 — safe project upgrades

v0.12.0 — tldraw visual canvas

v0.11.0 — data layer + data flywheel

v0.10.0 — design-md skill + Python 3.9 fix

v0.9.1 — pi adapter fixes + tz correctness

v0.9.0 — harness manager

Quickstart

macOS / Linux

Windows (PowerShell)

Already installed?

Clone instead?

Once installed: manage what's wired

Optional: external Brain integration

Onboarding wizard

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