/install disinto
Disinto Factory Skill
Disinto is an autonomous code factory with nine agents that implement issues, review PRs, plan from a vision, predict risks, groom the backlog, gate actions, and assist the founder — all driven by cron and Claude.
Required environment
| Variable | Purpose |
|---|---|
FORGE_TOKEN |
Forgejo/Gitea API token with repo scope |
FORGE_API |
Base API URL, e.g. https://forge.example/api/v1/repos/owner/repo |
PROJECT_REPO_ROOT |
Absolute path to the checked-out disinto repository |
Optional:
| Variable | Purpose |
|---|---|
WOODPECKER_SERVER |
Woodpecker CI base URL (for pipeline queries) |
WOODPECKER_TOKEN |
Woodpecker API bearer token |
WOODPECKER_REPO_ID |
Numeric repo ID in Woodpecker |
The nine agents
| Agent | Role | Runs via |
|---|---|---|
| Dev | Picks backlog issues, implements in worktrees, opens PRs | dev/dev-poll.sh (cron) |
| Review | Reviews PRs against conventions, approves or requests changes | review/review-poll.sh (cron) |
| Gardener | Grooms backlog: dedup, quality gates, dust bundling, stale cleanup | gardener/gardener-run.sh (cron 0,6,12,18 UTC) |
| Planner | Tracks vision progress, maintains prerequisite tree, files constraint issues | planner/planner-run.sh (cron daily 07:00 UTC) |
| Predictor | Challenges claims, detects structural risks, files predictions | predictor/predictor-run.sh (cron daily 06:00 UTC) |
| Supervisor | Monitors health (RAM, disk, CI, agents), auto-fixes, escalates | supervisor/supervisor-run.sh (cron */20) |
| Action | Executes operational tasks dispatched by planner via formulas | action/action-poll.sh (cron) |
| Vault | Gates dangerous actions, manages resource procurement | vault/vault-poll.sh (cron) |
| Exec | Interactive executive assistant reachable via Matrix | exec/exec-session.sh |
How agents interact
Planner ──creates-issues──▶ Backlog ◀──grooms── Gardener
│ │
│ ▼
│ Dev (implements)
│ │
│ ▼
│ Review (approves/rejects)
│ │
│ ▼
▼ Merged
Predictor ──challenges──▶ Planner (triages predictions)
Supervisor ──monitors──▶ All agents (health, escalation)
Vault ──gates──▶ Action, Dev (dangerous operations)
Exec ──delegates──▶ Issues (never writes code directly)
Issue lifecycle
backlog → in-progress → PR → CI → review → merge → closed.
Key labels: backlog, priority, in-progress, blocked, underspecified,
tech-debt, vision, action, prediction/unreviewed.
Issues declare dependencies in a ## Dependencies section listing #N
references. Dev-poll only picks issues whose dependencies are all closed.
Available scripts
scripts/factory-status.sh— Show agent status, open issues, and CI pipeline state. Pass--agents,--issues, or--cifor specific sections.scripts/file-issue.sh— Create an issue on the forge with proper labels and formatting. Pass--title,--body, and optionally--labels.scripts/read-journal.sh— Read agent journal entries. Pass agent name (planner,supervisor,exec) and optional--date YYYY-MM-DD.
Common workflows
1. Check factory health
bash scripts/factory-status.sh
This shows: which agents are active, recent open issues, and CI pipeline
status. Use --agents for just the agent status section.
2. Read what the planner decided today
bash scripts/read-journal.sh planner
Returns today's planner journal: predictions triaged, prerequisite tree updates, top constraints, issues created, and observations.
3. File a new issue
bash scripts/file-issue.sh --title "fix: broken auth flow" \
--body "$(cat scripts/../templates/issue-template.md)" \
--labels backlog
Or generate the body inline — the template shows the expected format with acceptance criteria and affected files sections.
4. Check the dependency graph
python3 "${PROJECT_REPO_ROOT}/lib/build-graph.py" \
--project-root "${PROJECT_REPO_ROOT}" \
--output /tmp/graph-report.json
cat /tmp/graph-report.json | jq '.analyses'
The graph builder parses VISION.md, the prerequisite tree, formulas, and open issues. It detects: orphan issues (not referenced), dependency cycles, disconnected clusters, bottleneck nodes, and thin objectives.
5. Query a specific CI pipeline
bash scripts/factory-status.sh --ci
Or query Woodpecker directly:
curl -s -H "Authorization: Bearer ${WOODPECKER_TOKEN}" \
"${WOODPECKER_SERVER}/api/repos/${WOODPECKER_REPO_ID}/pipelines?per_page=5" \
| jq '.[] | {number, status, commit: .commit[:8], branch}'
6. Read and interpret VISION.md progress
Read VISION.md at the repo root for the full vision. Then cross-reference
with the prerequisite tree:
cat "${PROJECT_REPO_ROOT}/planner/prerequisite-tree.md"
The prerequisite tree maps vision objectives to concrete issues. Items marked
[x] are complete; items marked [ ] show what blocks progress. The planner
updates this daily.
Gotchas
- Single-threaded pipeline: only one issue is in-progress per project at a time. Don't file issues expecting parallel work.
- Secrets via env vars only: never embed secrets in issue bodies, PR
descriptions, or comments. Use
$VAR_NAMEreferences. - Formulas are not skills: formulas in
formulas/are TOML issue templates for multi-step agent tasks. Skills teach assistants; formulas drive agents. - Predictor journals: the predictor does not write journal files. Its memory
lives in
prediction/unreviewedandprediction/actionedissues. - State files: agent activity is tracked via
state/.{agent}-activefiles. These are presence files, not logs. - ShellCheck required: all
.shfiles must pass ShellCheck. CI enforces this.
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install disinto - 安装完成后,直接呼叫该 Skill 的名称或使用
/disinto触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
Disinto Factory 是什么?
Operate the disinto autonomous code factory. Use when managing factory agents, filing issues on the forge, reading agent journals, querying CI pipelines, che... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 113 次。
如何安装 Disinto Factory?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install disinto」即可一键安装,无需额外配置。
Disinto Factory 是免费的吗?
是的,Disinto Factory 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Disinto Factory 支持哪些平台?
Disinto Factory 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 Disinto Factory?
由 johba37(@johba37)开发并维护,当前版本 v0.1.1。