autonomous-mode
Skill0 starsChanged 52 days agoMITView on GitHub
Running ArcheFlow unattended (overnight, batches of tasks): self-organization, progress logging, safe stopping.
4 other projects use a version of this.
Adopted by
Most recently taken up by
- axiomantic/spellbooktheir own version, first seen Nov 1, 2026
- satoh-y-0323/claude-code-conductortheir own version, first seen Oct 31, 2026
- BrOrlandi/my-claude-skillstheir own version, first seen Sep 22, 2026
- orkait/hyperstacktheir own version, first seen Jun 14, 2026
Other versions4 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 4
- BrOrlandi/my-claude-skills★ 22same name
- axiomantic/spellbook★ 11same name
- orkait/hyperstack★ 1same name
- satoh-y-0323/claude-code-conductor★ 1same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository29 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- .cursor/rules/archeflow.mdcCursor rule
- archeflow-reviewSkill
- archeflow-runSkill
- archeflow-sprintSkill
- act-phaseSkill
- check-phaseSkill
- cost-trackingSkill
- custom-archetypesSkill
- dagSkill
- domainsSkill
- git-integrationSkill
- initSkill
- memorySkill
- multi-projectSkill
- presenceSkill
- progressSkill
- replaySkill
- reportSkill
- reviewSkill
- runSkill
- scanSkill
- scoreSkill
- shadow-detectionSkill
- sprintSkill
- statusSkill
- templatesSkill
- using-archeflowSkill
- workflow-designSkill
The file
We split this skill into the rules it gives an agent
4 rules. 0 are common, 2 are distinctive, and 2 are very specific to this project.
0
Common
Most of the 3 edited versions we read keep these.
2
Distinctive
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 49
Budget exceeded: Stop at limit
- Distinctive: line 62
Pause: Stop after current task, resume later
- Very specific: line 64
Review: Read .archeflow/session-log.md for progress
- Very specific: line 68
Every session writes to .archeflow/session-log.md with per-task entries:
“Common” is measured: kept by at least 6 in 10 of the 3 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Autonomous Mode
ArcheFlow runs can work through several tasks without a person watching each step. The quality gates are LLM reviewers, so two settings stay with the user:
- Permission mode. Agents inherit the session's permission mode. The skill never asks for a bypass mode; if the user wants fewer prompts, they choose that when starting the session.
- Merging. A run merges into the base branch only with the user's yes, or when
git.auto_merge: trueis set in.archeflow/config.yamland the user confirmed it once in this session (the file can come with the repository; seearcheflow:run, Merge). Without either, an unattended run ends with statusawaiting_mergeand the reviewed work waits on its branch. - Tasks from files. Tasks in
.archeflow/queue.mdcan come with the repository. Before the first task, show the user every task line from the file (full text, includingdone:conditions) and get a yes for the list; a task or line added later needs a new yes. Adone:condition that names a command (load_test.sh passes) is run only if the user approved that exact command in this session; otherwise treat the condition as unmet and report it.
Task Queue Formats
Inline:
1. "Fix the login bug" (fast)
2. "Add user profile page" (standard)From file (.archeflow/queue.md):
- [ ] Fix the login bug | fast
- [ ] Add user profile page | standard | depends: fix login
- [ ] Security audit | thorough | done: Guardian approves AND load_test.sh passesTasks with depends: wait for the named task to complete. Tasks with done: have completion criteria checked in the Act phase.
Safety Mechanisms
Automatic Stop Conditions
- 3 consecutive failures: Something systemic is wrong
- Test suite broken:
archeflow-rollback.shreverts the run's merge commit; halt - Budget exceeded: Stop at limit
- Shadow escalation: Same shadow detected 3+ times across tasks
- Destructive action detected: Force push, branch deletion, schema drop
Everything is Reversible
- Code lives on run branches until merged (with confirmation or
git.auto_merge: true) - Merges are
--no-ffby default (one revertable merge commit per run) - Failed tasks leave branches intact for inspection
User Controls
- Cancel: Kill session, incomplete work stays on branches
- Pause: Stop after current task, resume later
- Skip: Move to next task
- Review: Read
.archeflow/session-log.mdfor progress
Session Log
Every session writes to .archeflow/session-log.md with per-task entries:
- Workflow, status, cycles, reviewer verdicts
- Files changed, tests added
- Branch and commit info
- Duration and timestamps
- Session summary at the end
Budget-Aware Scheduling
| Budget Remaining | Action |
| > 50% | Run at selected workflow level |
| 25-50% | Downgrade thorough to standard, standard to fast |
| < 25% | All tasks as fast only |
| Exhausted | Stop, log remaining as skipped |
Auto-Resume
On interruption the state is on disk: the event log (.archeflow/events/<run_id>.jsonl), the artifacts, and the run branch (archeflow-git.sh status <run_id>). On the next session, offer to resume with /archeflow:run --start-from <phase> or to start fresh.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

