disinto

Operate the disinto autonomous code factory. Use when managing factory agents, filing issues on the forge, reading agent journals, querying CI pipelines, checking the dependency graph, or inspecting factory health.

Safety Notice

This listing is from the official public ClawHub registry. Review SKILL.md and referenced scripts before running.

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Install skill "disinto" with this command: npx skills add johba/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

VariablePurpose
FORGE_TOKENForgejo/Gitea API token with repo scope
FORGE_APIBase API URL, e.g. https://forge.example/api/v1/repos/owner/repo
PROJECT_REPO_ROOTAbsolute path to the checked-out disinto repository

Optional:

VariablePurpose
WOODPECKER_SERVERWoodpecker CI base URL (for pipeline queries)
WOODPECKER_TOKENWoodpecker API bearer token
WOODPECKER_REPO_IDNumeric repo ID in Woodpecker

The nine agents

AgentRoleRuns via
DevPicks backlog issues, implements in worktrees, opens PRsdev/dev-poll.sh (cron)
ReviewReviews PRs against conventions, approves or requests changesreview/review-poll.sh (cron)
GardenerGrooms backlog: dedup, quality gates, dust bundling, stale cleanupgardener/gardener-run.sh (cron 0,6,12,18 UTC)
PlannerTracks vision progress, maintains prerequisite tree, files constraint issuesplanner/planner-run.sh (cron daily 07:00 UTC)
PredictorChallenges claims, detects structural risks, files predictionspredictor/predictor-run.sh (cron daily 06:00 UTC)
SupervisorMonitors health (RAM, disk, CI, agents), auto-fixes, escalatessupervisor/supervisor-run.sh (cron */20)
ActionExecutes operational tasks dispatched by planner via formulasaction/action-poll.sh (cron)
VaultGates dangerous actions, manages resource procurementvault/vault-poll.sh (cron)
ExecInteractive executive assistant reachable via Matrixexec/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

backlogin-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 --ci for 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_NAME references.
  • 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/unreviewed and prediction/actioned issues.
  • State files: agent activity is tracked via state/.{agent}-active files. These are presence files, not logs.
  • ShellCheck required: all .sh files must pass ShellCheck. CI enforces this.

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

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