using-archeflow
Skill0 starsChanged 52 days agoMITView on GitHub
Overview of ArcheFlow's commands and when to use which. The session-start hook injects the short version (ACTIVATION.md in this directory).
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
- autonomous-modeSkill
- 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
- workflow-designSkill
The file
Files
Using ArcheFlow
Commands
| Command | What it does |
/archeflow:review | Review uncommitted changes, a branch or a commit range with Guardian (plus Skeptic, Sage, Trickster on request). Any git repository, no setup. |
/archeflow:run <task> | Plan, Do, Check, Act for one task on its own branch; merges after approval and your confirmation. Flags: --workflow, --dry-run, --start-from, --lens, --pattern. |
/archeflow:init [bundle] | Create .archeflow/ from a bundle (quick-fix, backend-feature, security-review). |
/archeflow:sprint | Work through docs/orchestra/queue.json across the repositories of a workspace. |
/archeflow:scan | Propose new queue items and flag stale ones (new items need your approval). |
/archeflow:status | Current or last run, its branch, memory and config. |
/archeflow:report [run_id] | Full process report of a run. |
/archeflow:dag [run_id] | Event DAG of a run. |
/archeflow:replay <run_id> | Decision timeline and weighted what-if. |
/archeflow:score | Usefulness of each reviewer role across runs. |
/archeflow:memory | List, add or forget cross-run lessons. |
When to use what
| Need | Use |
| Check work that already exists | /archeflow:review |
| Security-sensitive or multi-file change, public API, complex refactor | /archeflow:run |
| Clear, small change | do it directly, no orchestration |
| Many queued tasks across repositories | /archeflow:sprint |
| Zero cloud tokens | models.provider: ollama (see the run skill's reference.md) |
Workflows
| Signal | Workflow | Roles |
| small fix, low risk | fast | Creator -> Maker -> Guardian |
| feature, several files, moderate risk | standard | Explorer + Creator -> Maker -> Guardian + Skeptic + Sage |
| security, breaking change, public API | thorough | Explorer + Creator -> Maker -> all four reviewers |
Without ArcheFlow
For a non-trivial change made directly: restate what you are changing, name one assumption, and check what it could break.
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.