Hsiang-Tang

Canopus — AI skill for Claude Code

AI community

Canopus keeps long-running AI coding agents locked on their goal: frozen acceptance envelopes, deterministic circuit breakers for drift and loops, durable task state, and a Claude Code Stop-hook foote.

How to install Canopus

This entry records only its repository, not the path inside it, so there is no exact command to give. Open Hsiang-Tang/canopus and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

What Canopus does

Canopus keeps long-running AI coding agents locked on their goal: frozen acceptance envelopes, deterministic circuit breakers for drift and loops, durable task state, and a Claude Code Stop-hook footer latch. Stdlib-only, adoptable in 15 minutes.

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README

Canopus — keep long-running AI agents locked on their goal

Spacecraft on multi-year missions used a *Canopus star tracker* to lock onto one bright star and hold their orientation. **Canopus** does the same for AI coding agents such as Claude Code and Codex: a small, complete framework for running them with engineering discipline. It turns an ambiguous request into a frozen, acceptance-checkable goal; lets replaceable agents push that goal forward across sessions, engines, and machines; and **stops them deterministically when they drift, loop, or over-engineer** — while every project's data stays in its own repository.

It is plain standard-library Python and Markdown that you can adopt in about 15 minutes.

[`docs/EVIDENCE.md`](docs/EVIDENCE.md) maps every behavior to the test that proves it.

The continuation loop: owner intent becomes a frozen envelope; a Brain and an Executor work against it; a convergence gate either records progress in a Task Footer or moves the task to COMPLETE, REALIGN, or CIRCUIT_BREAK; the Agent Handoff lets the next session resume, and the Owner Footer shows the human the state.

Why it exists

AI agents are productive inside one chat and unreliable across many. The failures are predictable:

Failure What Canopus does instead
Chat becomes the database; a new session forgets what was accepted Task state lives in the task's Issue and Task Footer; every session resumes from it
Commits, tests, and reviews look like progress Only closed acceptance items and resolved blockers count as progress
Every "reasonable" finding grows the scope The envelope is frozen; out-of-scope findings are deferred, widening needs re-admission
Review/fix loops never end Finite allowances that never replenish, and a circuit breaker on stagnati