Initier un projet

VérifiéSûr

Initialiseur de projet greenfield. Transforme une idée en un dépôt structuré en composant des compétences existantes, avec des portes de déclenchement et de valeur, enregistrement ADR et remise à la boucle de construction.

Spar Skills Guide Bot
DeveloppementIntermédiaire
23/07/2026
Claude Code
#greenfield#project-scaffolding#spec-driven#adr#workflow-orchestration

Recommandé pour

Synthèse automatique

Transforme l'idée d'un nouveau projet en dépôt structuré : filtre les cas qui méritent le processus, consigne un socle (ADR + reference.md) et délègue la spécification du walking skeleton à la boucle de construction.

Points forts

  • Un trigger gate explicite qui écarte scripts, spikes et jetables pour éviter la cérémonie inutile
  • Compose les skills existants (new-spec, work-loop, receive-brief) par référence sans réécrire leurs procédures
  • Cadre les cinq phases comme des allers-retours fluides plutôt qu'un waterfall rigide
  • Symétrie assumée avec adapt-to-project : les deux chemins convergent vers la même boucle brief → reference.md → spec → design → work-loop

Limites

  • La documentation fournie s'interrompt au milieu de la phase 2 (value gate), laissant le déroulé complet non spécifié
  • Le skill ne fonctionne que si les skills compagnons sont installés ; il n'effectue lui-même aucune découverte ni génération de code
  • Ce n'est pas un générateur autonome : l'humain doit rester dans la boucle et fournir une discovery en entrée
Quand l'utiliser

À utiliser au démarrage d'un dépôt vierge issu d'une idée, quand de vraies décisions de stack, de structure ou d'outillage restent à prendre.

Quand l'éviter

À ne pas utiliser dans un dépôt existant (préférer adapt-to-project), pour écrire une seule fonctionnalité (new-spec), ou pour un script jetable sans décision d'architecture.

Analyse de sécurité

Sûr
Score qualité80/100

This is a pure process-methodology document that orchestrates other named skills; it declares no tools, executes no commands, touches no network or filesystem directly, and contains no instructions to exfiltrate data, disable safeguards, or run destructive operations. The only notable characteristic is repeated admonitions to stay human-in-the-loop and to hand off to other skills, which is a governance posture rather than an execution risk.

Aucun point d'attention détecté

Comment cette analyse est faite

Exemples

Bootstrap a service idea
Start a new project: a webhook ingestion service with a queue, a worker, and a datastore. Take me through init-project so we end up with a repo, an ADR and a first walking skeleton.
Greenfield from a brief
Here's the brief we received — greenfield init this into a new repo, record the foundation decisions, and hand the walking skeleton to the build loop.
Gate check
I want to write a small script that renames files in a folder — should I run init-project, or just scaffold it directly?

name: init-project description: Use this skill to turn an idea into a structured new repo. It runs a trigger gate (throwaways and single scripts skip it), a value gate over fed-in discovery, records a foundation (an ADR plus a reference.md golden path), authors a walking-skeleton spec via new-spec and hands the build to work-loop, then hands off to the normal build loop. Triggers on "start a new project", "greenfield init", "idea to repo", "bootstrap a new codebase". Do NOT use inside an existing repo (use adapt-to-project) or to author one feature (use new-spec).

Skill: init-project

The greenfield front door. An idea arrives and there is no repo yet — no foundation recorded, no first slice built. The temptation is to yolo a throwaway prototype, get it sort-of working, then retrofit structure and lose the rationale. This skill gives that path a home: it turns an idea into a structured repo by composing the skills the repo already owns. It orchestrates; it does not reinvent, and it is not an autonomous code generator — the human stays in the loop and the existing skills do the work.

It is the twin of adapt-to-project (the brownfield front door, for an existing repo). Both converge on the same downstream loop: brief → reference.md → spec → low-level design → work-loop.

When to invoke

Invoke when the unit of work is a brand-new repo from an idea and there are real stack / structure / tooling decisions ahead — a service, a library, a multi-component app someone will maintain. The tells: "start a new project", "bootstrap this idea into a repo", "we're greenfielding X".

Do not use it when:

  • You are inside an existing codebase → adapt-to-project is the brownfield front door.
  • You want to author one feature from scratch → new-spec.
  • The thing ahead is a script, a spike, or a throwaway with no real structural decisions → the trigger gate (stage 1) sends it straight to scaffolding; don't force the flow onto it.

The flow — five phases, fluid not waterfall

The five stages below are fluid phases of attention, not a waterfall. You revisit them as understanding firms up — authoring the walking skeleton routinely sends you back to amend the foundation, and that's the flow working, not failing. Each phase practises a scoped handoff: it passes the next phase only the artifacts that phase needs, nothing more.

The skill composes existing skills and assets by reference — it names them and hands off to them; it never restates their procedures and never imports their code.

1. Trigger gate — run this first

Before any other work, decide whether the flow even applies:

  • Real stack / structure / tooling decisions ahead? (Which runtime? How is it partitioned? What's the persistence and transport story?) → continue to stage 2.
  • A script, a spike, or a throwaway? → scaffold it directly and skip the rest of this skill. The flow's ceremony is wasted on code nobody will maintain.

Worked example. "A 40-line script to rename files in a folder" → no architecture decisions → skip the flow, just write the script. "A webhook ingestion service with a queue, a worker, and a datastore" → real decisions → continue.

2. Value gate — over fed-in discovery

Discovery is fed in, never performed here (see anti-patterns). Consume a discovery shape from one of four upstream sources:

  • the research skill's output (when the research pack is installed),
  • an intent shaped by frame-intent (when the product-engineering pack is installed) — its frame → de-risk → decompose loop hands its leaf in here: at app scale a feature-level leaf intent is a core brief,
  • a provided PRD, or
  • a brief produced by receive-brief.

The product-engineering source is optional upstream, named the same way the research source is — "when the pack is installed". A core-only adopter has the other three and reads this one as a clearly-optional source, not a dangling reference.

From that input, derive the business value and the MVP: what outcome this serves and the smallest thing that delivers it. Gate on it — if you cannot state the business value plainly, pause and send discovery back upstream rather than guessing. Don't paper over a thin idea with a plausible mission.

The phase's output is the first brief (docs/product/briefs/<slug>.md, the artifact receive-brief owns) — the what / why that the rest of the flow and the downstream loop read. Hand that brief forward; nothing else.

3. Foundation — decide the stack, record the rationale

Choose the stack and architecture, and record the decision with its rationale — a foundation you can hold later work to. Two artifacts:

  • An ADR capturing what you chose, why, the alternatives weighed, and a re-evaluation date. A stack chosen with no recorded rationale is the thing to stop and fix before going further.
  • docs/architecture/reference.md — the normative golden path (constraints, solution strategy, building blocks, cross-cutting standards). Instantiate it from the arc42 reference.md template the adapt-to-project skill bundles (the same golden-path template its reference-architecture harvest fills) — here you fill it forward from a decision rather than harvesting it from existing code. The core methodology stays stack-neutral; the chosen stack is yours, recorded in your ADR and your reference.md. If the project will deploy, this is also the moment to record the deployment platform and where verification tooling will live in the reference.md slots (and the matching one-liners in the AGENTS.md infra block) — optional grounding the work-loop infra preflight reads if present, never a prerequisite.

Hand the foundation forward as the steering every later design conforms to.

4. Walking skeleton — author the spec, hand the build to work-loop

Author a walking skeleton: a thin, end-to-end slice that links the main architectural components — the smallest thing that exercises the real wiring (an inbound request reaching a real datastore through the real transport, say), not a sketch and not a throwaway. It is kept and minimal, held to a real feature contract.

  • Author it as a single spec via new-spec — one thin slice, with its own acceptance criteria and Shape:.
  • Hand the build to work-loop. This skill orchestrates; work-loop executes. Do not build the skeleton here — that would duplicate the loop the repo already owns.

If building the skeleton reveals the foundation was wrong, go back to stage 3 and amend it — that's the fluid-phase posture, not a failure.

5. Handoff — into the normal build loop

From the skeleton onward, the project runs the ordinary loop: brief → spec → low-level design → work-loop, with reference.md in place for every feature's low-level design to conform to. The greenfield front door has done its job: a recorded foundation, a validated walking skeleton, and the normal loop running — instead of a throwaway someone has to clean up later.

Anti-patterns to refuse

  • Performing discovery / research yourself. Discovery is fed in (stage 2) from the research pack, an intent from frame-intent (when product-engineering is installed), a PRD, or a receive-brief brief. This skill consumes a discovery shape; it does not own the research phase and does not shape product intent itself.
  • Building an autonomous multi-agent "software company" generator. The human stays in the loop and the existing skills do the work. The wins of a swarm of agents auto-generating a codebase are survivorship-bias stories; the boring, composed, human-in-the-loop path is the one that ships maintainable code.
  • Forcing the flow onto throwaways. The trigger gate exists to keep scripts and spikes on the fast path. A flow that adds ceremony to a 40-line script is friction, not discipline.
  • Producing a throwaway prototype in place of the walking skeleton. The skeleton is kept and minimal, authored as a real spec and built through work-loop — not a sketch you'll discard.
  • Choosing a stack with no recorded rationale. The foundation's ADR comes before the skeleton is authored, so the why survives.
  • Adding a new top-level directory, or importing another pack's code. This skill lives beside the other core skills and composes the rest by reference, not import — it names research, receive-brief, the arc42 reference.md template, new-spec, and work-loop, and hands off to them. The product-engineering seam is by reference too: frame-intent is named only as an upstream discovery shape this skill receives (when that pack is installed), never imported.
  • Restating what a composed skill already documents. Reference new-spec, work-loop, and the brief; don't copy their procedures into this file.

When this skill is wrong

If you're inside an existing repo, this is the wrong door — use adapt-to-project. If the idea is a one-off script, the trigger gate should already have sent you to scaffold it directly. And if the flow ever feels like ceremony getting in the way of a genuinely small thing, trust the trigger gate over the procedure.

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/init-project-mrx3xwjv/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/init-project-mrx3xwjv' && curl --fail --show-error --location 'https://skills-guides.com/api/skills/init-project-mrx3xwjv/download' --output '.skill-downloads/init-project-mrx3xwjv/SKILL.md.part' && mv '.skill-downloads/init-project-mrx3xwjv/SKILL.md.part' '.skill-downloads/init-project-mrx3xwjv/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/init-project-mrx3xwjv/SKILL.md' && test -s '.skill-downloads/init-project-mrx3xwjv/SKILL.md' && mkdir -p '.claude/skills' && test ! -e '.claude/skills/init-project' && cp -R '.skill-downloads/init-project-mrx3xwjv' '.claude/skills/init-project'

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/init-project-mrx3xwjv'

openskills read 'init-project-mrx3xwjv'

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/init-project-mrx3xwjv/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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