Shadow is you, one step down. You shape intent; Shadow does what you'd otherwise type at an AI agent — opens the board, picks the row, builds the prompt, writes the proof. It survives what loses work: a chat dying, a machine change, ten conversations at once.
git clone https://github.com/firstbitelabsllc/shadow.git && cd shadow
bash install.sh && shadow doctorGit, Bash, Python 3.10+, one native host (Claude Code, Codex, or Cursor). No Node, no npm — the
clone is the install, git pull is the update. Then paste the standing goal from
host integration into your hosts' instruction files.
shadow status # the board — same list from any directory, any machine
shadow amp # one goal block that POINTS at the plan, ≤4k chars
shadow throw --task '~ab12' # claim a row before handing it to another seat
shadow accept --row '~ab12' # rerun the proof in a clean checkout, then flip the rowAlso init --here, lint, browse, host run, doctor.
One plan, in git. Each project's truth is its own PLAN.md, so Shadow opens the same board
anywhere — an empty directory falls back to your portfolio instead of pretending nothing exists.
Chat is a projection; the plan is the memory.
The goal is a pointer. No prompt carries ten projects in 4,000 characters, so amp doesn't
try: authority ref, one resume row, its proof, and the rule that when block and plan disagree,
the plan wins.
No proof, no completed. Every task carries a proof: that can refuse bad work — cmd, read,
or gate <owner>. accept reruns it in a clean checkout and is the only path that flips a task.
No database, daemon, scheduler, or transcript memory — a surface that could mutate a row outside
PLAN.md is banned. Native hosts keep auth and model choice. host run runs one sealed task and
never launches work itself. accept reruns only cmd proofs; read and gate are judgments a
person re-observes. A receipt is evidence, not acceptance.
scripts/shadow-python.sh -m unittest discover -s tests -p 'test_*.py' — the method is one page,
AGENT.md, enforced by the grammar.
Quick start · Commands · Amp · Privacy · MIT.