Jonggrang : Orchestrateur de flux de développement IA

VérifiéPrudence

Orchestrateur déterministe de flux de développement IA. Gère des tableaux de tâches, exécute des pipelines en 16 phases et coordonne cinq rôles d'agents spécialisés via npx jonggrang.

Spar Skills Guide Bot
DeveloppementAvancé
06/09/2026
Claude Code
#workflow-orchestration#task-board#multi-agent#pipeline#ai-coding

Recommandé pour

Synthèse automatique

Orchestrateur déterministe de workflows de développement IA qui gère un tableau de tâches, exécute des pipelines en 16 phases et coordonne cinq rôles spécialisés via npx.

Points forts

  • Pipelines déterministes en 16 phases adaptés à différentes tailles de tâche (BUGFIX, SMALL, MEDIUM, LARGE).
  • Tableau de tâches et fichier de progrès intégrés pour reprendre le travail entre contextes.
  • Coordination explicite des rôles Lead/Developer/Reviewer/TestLead/Tester.
  • Passerelle de skills permettant de charger des connaissances ciblées par domaine.

Limites

  • Nécessite Node.js et une structure .jonggrang initialisée, avec une surcharge pour les petites modifications.
  • Le support explicitement décrit vise Claude Code et OpenCode, pas l'ensemble des IDE listés.
  • Dépend des conventions projet dans AGENTS.md et de fichiers de configuration générés.
Quand l'utiliser

À utiliser pour planifier et exécuter des fonctionnalités ou corrections multi-étapes avec plusieurs agents et un suivi déterministe.

Quand l'éviter

À éviter pour une modification triviale ou dans un projet sans structure Jonggrang et sans volonté d'adopter son processus.

Analyse de sécurité

Prudence
Score qualité80/100

The content is a well-scoped development-workflow manual with no destructive commands (no rm -rf, curl|sh, base64 payloads, or secret exfiltration) and it explicitly warns against broad git staging and committing secrets. The residual risk is that it directs the agent to fetch/execute a third-party npm package and install agent lifecycle hooks, and to run local Node code and make git commits — all powerful but legitimate actions for a dev orchestrator, so it falls under caution rather than risky.

Points d'attention
  • •Instructs running a third-party npm package on every command via `npx jonggrang <command>`, which downloads and executes remote code from the npm registry (supply-chain trust required).
  • •Description notes the tool installs lifecycle hooks for Claude Code and OpenCode, which can modify agent configuration/behavior outside the project.
  • •Instructs executing local code via `node -e "require('./lib/gateway')..."`, which runs whatever the repository's gateway module contains.
  • •Performs state-changing git operations (git add / git commit), though it correctly forbids `git add .`/`-A` and committing secrets or node_modules.
  • •Primary workflow is `npx jonggrang <command>`, which downloads and executes an unpinned third-party npm package at runtime — a supply-chain exposure that grants that package the agent's full shell/file permissions.
  • •Description states the skill installs lifecycle hooks into Claude Code and OpenCode, i.e. persistent modifications to the agent's own runtime/config; the SKILL.md body does not document what those hooks do or how to inspect/remove them.
  • •Exposes an `--autonomy autonomous` flag ("Skip human pauses") that deliberately removes human checkpoints from a multi-agent pipeline — reduces oversight by design.
  • •Instructs the agent to execute project-controlled code paths: `node -e "...require('./lib/gateway')..."`, `npm test`, `npm run lint`, `npm run typecheck`, plus `git add`/`git commit`. Legitimate dev activity but broad shell/write authority.
  • •Role/phase prompts and completion-signal protocol amount to embedded instructions that reshape agent behavior when running in orchestrate mode; benign here, but such self-directing content should be reviewed by a human before adoption.
Comment cette analyse est faite

Exemples

Plan a medium feature
Use Jonggrang to plan and execute a MEDIUM feature: add OAuth login to the Express API. Create the task board, run the MEDIUM pipeline, and coordinate the Developer, Reviewer, and TestLead roles.
Run a bugfix pipeline
Run the Jonggrang BUGFIX pipeline for issue #142 where the checkout total is off by one cent. Have the Tester verify a regression test before closing the task.
Initialize workflow hooks
Initialize Jonggrang in this repository, install the Claude Code lifecycle hooks, and generate a task board for refactoring the payment module.

name: jonggrang description: Deterministic AI development workflow orchestrator. Manages task boards (.jonggrang/jonggrang-tasks.json), runs 16-phase pipelines (BUGFIX/SMALL/MEDIUM/LARGE), installs lifecycle hooks for Claude Code and OpenCode, and coordinates five specialist roles (Lead/Developer/Reviewer/TestLead/Tester). Use when planning features, executing multi-step development workflows, or orchestrating AI coding agents. Run via npx jonggrang. metadata: {"clawdbot":{"emoji":"🎭","os":["darwin","linux","win32"],"requires":{"runtime":"node","install":"npx jonggrang"}}}

Jonggrang — AI Agent Instructions

You are working inside a project managed by Jonggrang, a deterministic AI development workflow orchestrator. This file is your operating manual. Read it completely before doing anything.


How to Run Jonggrang

Use npx — no global installation required:

npx jonggrang <command>

If Jonggrang is already installed globally, you can also use jonggrang <command> directly. To check:

npx jonggrang version

Your Role in This Project

Jonggrang runs in two modes. Know which one you are in:

Mode 1 — Work Loop

You are a single agent executing tasks from .jonggrang/jonggrang-tasks.json one at a time. Each invocation is stateless — a fresh context window per task.

Mode 2 — Orchestrate (16-Phase Pipeline)

You are a specialist agent assigned to a specific phase and role. You receive a crafted prompt that tells you your role, the current phase, and what the previous agent produced. You must emit a completion signal at the end of your output.

Check .jonggrang/jonggrang-tasks.json for your current task's "role" field, or look for role instructions in your prompt.


Context Files — Read These First

| File | Purpose | Action | |------|---------|--------| | AGENTS.md | Project conventions, patterns, gotchas | Read first. Follow all conventions. | | .jonggrang/progress.txt | Learnings from previous iterations | Read. Avoid repeating mistakes. | | .jonggrang/jonggrang-tasks.json | Task board with current state | Read. Find your assigned task. | | .jonggrang/jonggrang.json | Project config (stack, testing, tool) | Read. Know your test command and stack. | | skills/core/<name>/SKILL.md | Core skill for your task type | Read if task has "skill" field. | | .jonggrang/.output/features/<id>/MANIFEST.yaml | Orchestration phase state | Read in orchestrate mode. |


Skill System — Two Tiers

Skills are prompt templates that encode expert knowledge. There are two tiers:

Tier 1: Core Skills (skills/core/)

Always available. Loaded into your prompt for every task. Contains foundational patterns:

  • How to orchestrate a feature
  • How to dispatch parallel agents
  • How to invoke the Gateway
  • Domain gateway pointers (backend, frontend, api, testing, database)
  • Scaffold templates (scaffold-api, scaffold-webapp, component, migration, auth, etc.)

Tier 2: Library Skills (skills/library/)

Loaded on demand via the Gateway when you need deep domain knowledge.

| Domain | Available Skills | |--------|-----------------| | backend | developing-with-tdd, debugging-systematically, error-handling-patterns | | frontend | debugging-react-hooks, optimizing-react-performance | | testing | unit-testing-patterns, fixing-flaky-tests | | database | safe-migrations | | api | input-validation | | security | rate-limiting |

Using the Gateway

Before implementing, resolve the right library skill for your task:

node -e "
const gw = require('./lib/gateway');
const r = gw.buildGatewayResponse('YOUR TASK DESCRIPTION HERE', './skills');
console.log(r);
"

The Gateway returns { domain, skill_paths, instruction }. Read each file in skill_paths before implementing.


Work Loop — Task Execution Protocol

Step 1: Understand

  • Read all context files listed above
  • Read the task description carefully — it contains acceptance criteria
  • If the task has "skill": "scaffold-api", read skills/core/scaffold-api/SKILL.md
  • Check blocked_by — dependencies must already be completed

Step 2: Invoke Gateway

Resolve the right library skills for your task domain:

node -e "
const gw = require('./lib/gateway');
const r = gw.buildGatewayResponse('<task description>', './skills');
r.skill_paths.forEach(p => console.log('Read:', p));
"

Read each returned skill file before proceeding.

Step 3: Plan

  • Identify which files to create or modify
  • Check existing code patterns before writing new code
  • Follow conventions in AGENTS.md
  • Keep changes atomic — only touch files relevant to this task

Step 4: Implement

  • Write clean, working code
  • Follow existing patterns in the codebase
  • Use the project's existing dependencies (don't add unnecessary packages)
  • Include proper types (no any in TypeScript)

Step 5: Validate

# Typecheck
npm run typecheck    # or: tsc --noEmit, go vet, mypy, etc.

# Tests
npm test             # or: the command in .jonggrang/jonggrang.json -> testing.command

# Lint (if configured)
npm run lint

If validation fails: read the error, fix it, re-run. If stuck after 2 attempts, stop and report clearly.

Step 6: Update State

Update .jonggrang/jonggrang-tasks.json — mark task completed:

{
  "status": "completed",
  "passes": true,
  "completed_at": "<ISO timestamp>"
}

Append to .jonggrang/progress.txt — log learnings:

## task-XXX: Task Title
- What was implemented
- What was surprising or non-obvious
- Patterns discovered in the codebase
- Gotchas for future iterations

Step 7: Commit

git add <specific files only>
git commit -m "type(scope): description"

Types: feat, fix, refactor, test, docs, chore

Never: git add . or git add -A, commit node_modules/ or .env, amend previous commits.


Orchestrate Mode — Role-Specific Instructions

In orchestrate mode you are assigned one of five roles. Your role determines what tools you have and what signal you must emit.

Role Summary

| Role | Can Edit Files | Can Spawn Agents | Completion Signal | |------|:-:|:-:|-------------------| | Lead | no | YES (Task tool) | ARCHITECTURE_PLAN_COMPLETE | | Developer | YES | no | IMPLEMENTATION_COMPLETE | | Reviewer | no (read-only) | no | REVIEW_COMPLETE | | TestLead | no | YES (Task tool) | TEST_PLAN_COMPLETE | | Tester | YES | no | ALL_TESTS_PASSING |

Phase → Role Mapping

| Phases | Role | What You Do | |--------|------|-------------| | 1–4 | (orchestrator) | Setup, triage, discovery — handled automatically | | 5–7, 16 | Lead | Assess complexity, brainstorm, architect, finalise | | 8 | Developer | Implement the feature end-to-end | | 9–11, 15 | Reviewer | Verify design, compliance, quality, test quality | | 12 | TestLead | Write the test plan | | 13–14 | Tester | Execute tests, verify coverage |

Completion Signal Protocol

Your last output line must be your role's completion signal. The orchestration engine waits for this signal before advancing to the next phase.

# Developer — after all code is written, typechecked, and tests pass:
IMPLEMENTATION_COMPLETE

# Tester — after all tests pass and coverage threshold met:
ALL_TESTS_PASSING

# Reviewer — after completing your review:
REVIEW_COMPLETE

# Lead — after producing architecture plan:
ARCHITECTURE_PLAN_COMPLETE

# TestLead — after producing test plan:
TEST_PLAN_COMPLETE

Reading the MANIFEST

In orchestrate mode, the MANIFEST tracks phase state. Read it to understand context:

cat .jonggrang/.output/features/<feature-id>/MANIFEST.yaml

Key fields: work_type, current_phase, phases (per-phase status and output), validation.


Rules

DO

  • Read all context files before starting
  • Follow conventions in AGENTS.md exactly
  • Invoke the Gateway to load the right library skill
  • Keep changes minimal and focused on the task
  • Write tests when the task requires them
  • Run validation before committing
  • Log learnings in .jonggrang/progress.txt
  • Emit your completion signal as the final output line (orchestrate mode)

DO NOT

  • Modify files not related to your task
  • Add dependencies without clear justification
  • Change AGENTS.md directly — propose changes in .jonggrang/progress.txt instead
  • Skip validation steps
  • Make multiple commits per task (one atomic commit per task)
  • Ignore errors — fix them or report them clearly
  • Write .md files outside .jonggrang/, AGENTS.md, .jonggrang/progress.txt, README.md, CHANGELOG.md, or docs/

File Ownership

Each task in .jonggrang/jonggrang-tasks.json has a "files" array listing the files it owns. Do not modify files owned by other tasks — this prevents merge conflicts in team mode.


Jonggrang Commands Reference

# Setup
npx jonggrang init                               # Interactive setup wizard
npx jonggrang init --name x --type api --tool claude --autonomy balanced --force

# Work Loop
npx jonggrang plan "feature description"         # Decompose feature into tasks
npx jonggrang work                               # Run all pending tasks
npx jonggrang work --max-iterations 1            # Run one task only
npx jonggrang work --task task-003               # Run a specific task
npx jonggrang work --tool claude                 # Override AI tool
npx jonggrang work --dry-run                     # Preview prompt, no execution
npx jonggrang work --mode supervised             # Override autonomy

# Orchestrate (16-phase deterministic pipeline)
npx jonggrang orchestrate "description"          # Start full pipeline
npx jonggrang orchestrate --resume               # Resume interrupted pipeline
npx jonggrang orchestrate "..." --dry-run        # Preview all phase prompts
npx jonggrang orchestrate "..." --autonomy autonomous  # Skip human pauses

# Utilities
npx jonggrang status                             # Show task board
npx jonggrang review                             # Run code review
npx jonggrang version                            # Show version
npx jonggrang help                               # All commands and flags

Example: Completing a Work Loop Task

Given this task in .jonggrang/jonggrang-tasks.json:

{
  "id": "task-002",
  "title": "Add Todo CRUD endpoints",
  "description": "Create GET/POST/PUT/DELETE endpoints for /api/todos with in-memory storage",
  "skill": "scaffold-api",
  "files": ["src/routes/todos.ts", "src/types/todo.ts"],
  "blocked_by": ["task-001"]
}

Execution:

  1. Read AGENTS.md, .jonggrang/progress.txt, .jonggrang/jonggrang-tasks.json, .jonggrang/jonggrang.json
  2. Read skills/core/scaffold-api/SKILL.md
  3. Run Gateway to resolve library skills for this task type
  4. Read existing code (src/app.ts, other routes) to understand patterns
  5. Create src/types/todo.ts with the Todo interface
  6. Create src/routes/todos.ts with CRUD handlers
  7. Register routes in src/app.ts
  8. Run npm run typecheck && npm test
  9. Update .jonggrang/jonggrang-tasks.json (status: completed, passes: true)
  10. Append learnings to .jonggrang/progress.txt
  11. git add src/routes/todos.ts src/types/todo.ts src/app.ts .jonggrang/jonggrang-tasks.json .jonggrang/progress.txt
  12. git commit -m "feat(todos): add CRUD endpoints with in-memory storage"

Du fichier au premier essai

Le téléchargement contient exactement le contenu affiché sur cette fiche. Cette copie peut différer de la dernière version du dépôt source.

Consulter la source et ses fichiers annexes

Ce téléchargement contient uniquement SKILL.md. Les scripts, références, modèles et dépendances éventuels ne sont pas inclus. Récupérez les fichiers nécessaires depuis la source en conservant leur arborescence avant de poursuivre.

1. Télécharger le fichier

Télécharger SKILL.md

Depuis la racine d’un projet de test, enregistrez le fichier sous .skill-downloads/jonggrang-ai-development-workflow-orchestrator-mtpag75v/SKILL.md, ou utilisez la commande suivante. Ce dossier sert à examiner la skill avant son installation.

Commande pour macOS/Linux ou WSL : un shell POSIX et curl sont nécessaires. Sous Windows sans WSL, utilisez le bouton de téléchargement et créez le dossier manuellement.

mkdir -p '.skill-downloads/jonggrang-ai-development-workflow-orchestrator-mtpag75v' && curl --fail --show-error --location 'https://skills-guides.com/api/skills/jonggrang-ai-development-workflow-orchestrator-mtpag75v/download' --output '.skill-downloads/jonggrang-ai-development-workflow-orchestrator-mtpag75v/SKILL.md.part' && mv '.skill-downloads/jonggrang-ai-development-workflow-orchestrator-mtpag75v/SKILL.md.part' '.skill-downloads/jonggrang-ai-development-workflow-orchestrator-mtpag75v/SKILL.md'

2. Vérifier les prérequis

Lisez SKILL.md avant de l’utiliser. Si le fichier cite des scripts ou services externes, examinez-les et préparez les accès nécessaires dans votre environnement de test.

Aucune section de prérequis reconnue dans ce fichier. Cela ne signifie pas qu’il est autonome : les bibliothèques, outils et accès peuvent être cités ailleurs dans le contenu ou dans le dépôt source.

Les plateformes de la fiche sont des indications du catalogue. Les chemins ci-dessous suivent la documentation des outils ; ils ne prouvent pas que cette skill y a été exécutée. Aucune version minimale de ces outils n’est attestée pour cette fiche.

3. Charger la skill

Après vérification, copiez le dossier complet dans le projet avec l’une des commandes ci-dessous, puis ouvrez une nouvelle session de l’outil. La commande s’arrête si un dossier du même nom existe déjà : comparez les fichiers avant de le remplacer.

Claude Code
test -f '.skill-downloads/jonggrang-ai-development-workflow-orchestrator-mtpag75v/SKILL.md' && test -s '.skill-downloads/jonggrang-ai-development-workflow-orchestrator-mtpag75v/SKILL.md' && mkdir -p '.claude/skills' && test ! -e '.claude/skills/jonggrang' && cp -R '.skill-downloads/jonggrang-ai-development-workflow-orchestrator-mtpag75v' '.claude/skills/jonggrang'

OpenSkills

OpenSkills doit déjà être installé. La procédure locale install/read est contrôlée avec OpenSkills 1.5.0, qui exige Node.js ≥ 20.6.0. Aucun slug du catalogue n’est résolu automatiquement.

Installation officielle d’OpenSkills
openskills install './.skill-downloads/jonggrang-ai-development-workflow-orchestrator-mtpag75v'

openskills read 'jonggrang-ai-development-workflow-orchestrator-mtpag75v'

La lecture doit afficher le contenu du fichier installé et son dossier de base. Elle ne lance ni la skill ni ses dépendances.

Pour un agent qui lit AGENTS.md, synchronisez ensuite l’index. Cette commande modifie AGENTS.md : relisez le diff avant de l’utiliser.

openskills sync

Mode manuel ou autre outil : joignez SKILL.md à une conversation, ou ouvrez-le dans un agent capable de lire les fichiers. Ajoutez les ressources annexes nécessaires. Il n’existe pas de dossier universel reconnu par tous les outils.

4. Faire un premier essai

Utilisez une entrée courte et fictive : un endpoint d’API, un petit document ou un brief d’interface. Dans une nouvelle conversation, joignez le fichier ou donnez son chemin à l’agent, puis adaptez cette demande :

Lis .skill-downloads/jonggrang-ai-development-workflow-orchestrator-mtpag75v/SKILL.md et applique ses instructions à cet exemple : [décrire une entrée de test]. Indique les fichiers, dépendances ou accès qui manquent. Produis le résultat demandé par la skill sans inventer de données ni exécuter de script non examiné.

Résultat attendu : une sortie correspondant aux instructions de la skill, ou une liste précise des prérequis manquants. Une simple confirmation de lecture ne valide pas le premier usage. Si une ressource externe est indisponible, ce parcours reste à tester.

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