🥁 Baton — Pass your project, not your context.

Switch computers, switch AI, switch sessions — and keep working with one sentence.

中文 ｜ English

Baton is a project-relay collaboration system. It lets Claude Code, Codex, Cursor, and DeepSeek Harness take turns maintaining the same project across machines — progress, memory, design specs, tasks, and Git stay consistent. You talk normally; it does the rest.

Three core promises:

1. 🔄 Anyone can take over — switch AI tools or machines, say one command, and pick up exactly where you left off. No re-explaining the project.
2. 🎯 Do what was asked — task boundaries and protected paths are mechanically checked at closeout, and design facts are locked into specs; the rest is guarded by rules plus review — drift gets caught, not discovered hours later.
3. ✅ "Done" really means done — closeout auto-commits, pushes, and verifies the remote SHA — no more "committed locally but never on GitHub, yet told it's done."

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🚀 Quick start (DeepSeek Harness — one line)

Using DeepSeek Harness? This is everything you need.

dsh plugin --profile web add @kakadeka/dsh-baton

1. Install the DSH CLI once: npm i -g @deepseek-ai/dsh
2. Paste the line above, press Enter.
3. Restart dsh — done. All 16 baton_* tools are now active in your profile.

Also installable from GitHub: dsh plugin --profile web add github:kakadeka/Baton Using Codex / Claude Code / Cursor instead? Jump to install for other AI tools.

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📖 Scenarios (one per requirement, pain → Baton's answer)

#	Pain	Baton's answer
1	Every morning or new machine: which branch? what was done yesterday? is the remote updated?	Say clock in — auto git checks + safe sync + read handoff/todos → task table → reply a number
2	"Committed locally but not pushed"; manual PowerShell git at night	Say clock out — verify → docs/memory/metrics → commit → push → remote SHA == local HEAD before "done"
3	Finishing a task and "end of day" got conflated	Say complete task — close the task, record results, suggest next. Task-done ≠ end-of-day
4	Confirmed designs get forgotten; AI free-styles	Say save design spec — lock design facts into long-term specs (conflicts keep history); UI tasks auto-reference them
5	Lost session, new conversation, re-explain everything	Say continue work — restore task/branch/blocker/handoff/next-step. One sentence, done
6	Multiple todos; AI shouldn't decide priority; typing full tasks is tedious	Task table with numbers — reply 1/2/3
7	Long project, history unreachable; re-reading everything burns tokens	Decisions/pitfalls/specs auto-indexed; query the index, read only the hit fragment
8	Codex/Claude/Cursor relay without knowing what the last one did	Unified handoff file — branch/HEAD/changes/constraints/next-step. Read the last entry, continue
9	Expensive model used for everything; weak model makes mistakes; manual switching is painful	Auto model routing by task difficulty — micro: main session, normal: flash, complex/review: pro, with fallback chains
10	"Which model actually ran?" bills don't match	recommended vs actual recorded separately, source labeled honestly (dispatch record / host descriptor / unknown)
11	AI drifts from prototype after hours of work	Frozen requirements + allowed/protected paths + mechanical scope checks + independent review + no dangerous git
12	Changing a button color took an hour	Micro fast path — no delegation, no reviewer, no irrelevant tests. Simple tasks take minutes
13	Complex tasks must not be written sloppily	Escalating gates: contract, strong model, independent reviewer, fidelity vs frozen spec, rollback plan
14	Office and home machines out of sync; fear of losing local work	Safe fetch + ff-only sync (never overwrites), auto commit/push, remote SHA verify; force/reset/clean forbidden
15	Picking models by feel, no real data	Every task records actual model and completion → monthly dashboard; success/failure/duration not yet collected are shown as "not recorded", never fabricated
16	Reuse/share the system with a new project	Framework and project instance fully separated; Baton init one-shot bootstrap; share via sanitizing pipeline (no keys/paths/private notes)
17	Other skills installed that bypass project rules	External skills may help, but project boundaries (paths, design specs, git discipline) are enforced by Baton, coordinated with AGENTS.md

✨ Features (8 capability blocks)

• Command automation — clock in / clock out / continue work / save design spec / complete task / update project docs / remember / Baton init / number confirm / git natural language
• Cross-AI & cross-machine — plain-text project truth + one-command thin adapters (Codex/Claude/Cursor) + handoff relay
• Long-term memory — decisions/pitfalls/specs auto-archived + lightweight index; progressive reads, no full re-reads
• Anti-drift — FROZEN constraints + allowed/protected path checks + forbidden-change list + independent review + no dangerous git
• Git truth loop — ff-only sync, auto commit/push, remote SHA == local HEAD, publish record (last_published_sha)
• Auto model routing — task tier × rule table (flash/pro + high/max + fallback); recommended vs actual recorded transparently
• Monthly dashboard — model rankings / hourly activity / daily detail / agent detail, from real execution data
• One-click acceptance — baton_accept: skeleton/state/security/volume checks → PASS/FAIL + blocking list

🗣️ Commands (when to use each)

Say any of these English phrases — the meaning is identical in every AI. Chinese speakers can use the same commands in Chinese (see the Chinese version via the link at the top).

Command	When	What happens
clock in / start work	daily start / new machine / new AI	git checks → safe sync → handoff & todos → task table
clock out / end work	end of workday	verify → docs/memory/metrics → commit → push → remote SHA verify
continue work / resume	lost session / switched tool	restore task, branch, blocker, handoff tail, next step
save design spec	after you confirm a design	lock into long-term spec + index; UI tasks obey it
complete task	a task is done, more to do	close task, record result, suggest next (no full closeout)
update project docs	mid-work checkpoint	write progress + handoff checkpoint (workspace stays held)
remember this pitfall / record this decision	hit a pitfall / made a decision	write to long-term memory + auto-index
Baton init	first time in a new project	generate memory skeleton + config (never overwrites)
reply 1 / 2 / 3	task table shown	the number is persisted as the current task, then work starts
release workspace / I confirm the previous agent stopped	ownership conflict at clock in	unlock the single-writer lock + write a release note
pull github / sync github / check git status	manual git intent	lightweight git path, no contract/review ceremony

🛠️ Install for other AI tools (Codex / Claude / Cursor)

Installing = copy one command, press Enter, wait for it to finish, then verify one command. No manual folder creation, no manual file copying. DeepSeek Harness users can skip this — use the one-line Quick start above instead.

Step 0: Decide which install you need (10 seconds)

Your situation	Install this	After install
Multiple projects — you want Baton available in every project on this machine	User-level (once per machine)	Global on this machine; any project recognizes the commands
One specific project you want other machines/AIs to take over	Project-level (once per project)	The project carries its own memory skeleton + 3-tool adapters; git clone and continue
Both	User-level first, then project-level	Most complete

💡 Recommended: run user-level (30s), then project-level on your real project (30s).

Step 1: Download Baton (once)

Open PowerShell (press Win, type powershell, Enter), paste this line:

git clone https://github.com/kakadeka/Baton.git $HOME\Baton

No git? Install from https://git-scm.com/download/win, reopen PowerShell, paste again.

Step 2: Pick one install type and paste its command

Option A — User-level (once per machine, all projects)

pwsh -File $HOME\Baton\scripts\baton-install.ps1 -Scope User

You'll see ok: [Codex] ..., ok: [Claude Code] ..., ok: [Cursor] ... — the global skill for all three AI tools is installed.

Option B — Project-level (once per project, makes the project portable)

cd C:\your\project\path
pwsh -File $HOME\Baton\scripts\baton-install.ps1 -Scope Project

You'll see a success line (project-level install complete) plus the created list (memory skeleton docs/ai_memory, config .baton, three skill mirrors, and entries in AGENTS.md / CLAUDE.md / .cursorrules). If it says no .git, run the git init commands it prints.

Project-level install is fully automatic and works without the DeepSeek Harness plugin (plugin-free mode).

Step 3: Verify (the important one — one command)

In the project, tell your AI:

clock in

✅ Success: the AI acts per Baton and outputs a status report with the branch, HEAD, working-tree state, current task, and handoff summary, followed by a task table like —

Task table: 1) ...

❌ Nothing happens? Check in order:

1. Which AI are you using? Claude Code → ~\.claude\skills\baton\SKILL.md; Codex → ~\.agents\skills\baton\SKILL.md; Cursor → ~\.cursor\skills\baton\SKILL.md (user-level install creates all three)
2. Does the project have .git? (else git init + first commit)
3. Is the command exactly clock in with nothing else?
4. Does the project have docs/ai_memory/? (project-level install creates it)

Step 4: Joining an existing Baton project (new machine / new AI)

On the new machine: install git → git clone your project → tell your AI:

clock in  or  continue work

Memory, handoff, and tasks come with the code. Continue directly — nothing else to install.

What the one-click script does (transparent)

Mode	Automatically does
User-level	Copies SKILL.md into the global skill folders of all three AI tools (Codex / Claude Code / Cursor)
Project-level	① docs/ai_memory/ skeleton (with revision log + archive index) ② .baton/config.json ③ .gitignore append ④ three skill mirrors ⑤ three entry segments (AGENTS.md / CLAUDE.md / .cursorrules, never overwrites your rules)

Idempotent: re-running never overwrites your existing docs and rules; it only fills in what's missing.

📁 Where the truth lives

project/
├── docs/ai_memory/            ← long-term memory (Git-synced, AI-agnostic)
│   ├── index.md               ← read me first
│   ├── current.md             ← what's happening now
│   ├── handoff_current.md     ← handoff log (last entry = truth)
│   ├── state/                 ← tasks.json, archive_index.json, project_state.json
│   ├── knowledge/             ← tech_decision.md, pit_experience.md
│   ├── ui_spec/               ← design specs
│   ├── daily_log/             ← daily logs
│   └── agent_metrics/YYYY/MM/index.html  ← monthly dashboard
└── .baton/                    ← machine-local (gitignored): config, metrics, evidence

🛡️ Safety & design

• Dangerous git (force push / reset --hard / risky clean / unauthorized rebase) does not exist
• Syncs are ff-only; divergence stops and reports; never auto-resolves conflicts
• Credentials never enter Git / Memory / Metrics / logs
• History is append-only or marked "superseded" — never overwritten
• "Done" = mechanical evidence (remote SHA + publish record), not a claim
• Saving tokens is a first-class goal: index-first, risk-based models, bounded outputs, no redundant calls

📦 Repository & license

• Open-source: https://github.com/kakadeka/Baton (public package only, synced via a sanitizing pipeline — no private plans, session notes, or credentials)
• npm: @kakadeka/dsh-baton
• License: MIT
• History: formerly workday-knowledge-manager (V8.5) and EboWork; this is the rebuilt, Harness-native implementation