ai-assist-dockerize-website
Guide the user through containerizing and serving a simple website or documentation folder with Docker — inspects the project to detect what to serve (ready-to-serve static HTML, a buildable site that emits static output, or a raw markdown/docs folder that needs rendering), gener
Profil de l’actif
Recherche et travail de connaissance
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scénario
Agents de recherche
I need my agent to research a topic, compare sources, and produce a concise report.
Adéquation Agent
Claude Code + Browser agents + CLI
Compatible avec Codex, Claude Code, Cursor, CLI ou des Agents personnalisés.
Installer
Prêt
npx skills add jparkerweb/ai-assist-skills --skill ai-assist-dockerize-website
Maintenance
À jour
Mis à jour aujourd’hui
Risque
Revue nécessaire
La licence est ambiguë
Qualité GitHub
88
61/100 Qualité · 62/100 Confiance
Tags de couverture
Notes de revue
La licence est ambiguë · Dependency or permission surface needs review
Carte d’adoption Agent
Confiance, audit et préparation à l’installation en un coup d’œil
Ces scores combinent les métadonnées publiques du dépôt, les signaux de revue OpenAgentSkill, la fraîcheur de maintenance et la préparation à l’installation. Ils servent à présélectionner et ne remplacent pas la revue humaine.
Qualité
PrometteurUseful candidate, but compare it with alternatives before adopting.
Confiance
Do not auto-installTrust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
Audit
Revue nécessaireRevue lisible par machine de la préparation à l’installation, des métadonnées de sécurité, de la maintenance et du risque d’adoption.
Trust Score OpenAgentSkill v5
Revue humaine avant installation
Choose a stronger alternative or inspect the source manually before any install attempt.
Stars
88 stars GitHub
Activité du dépôt
88 stars et 12 forks
Maintenance
Mis à jour aujourd’hui
Licence
Inconnu
Installer
npx skills add jparkerweb/ai-assist-skills --skill ai-assist-dockerize-website
Sécurité d’installation
Chemin d’installation standard de package ou runtime
Surface de permissions
secrets or environment access, shell or command execution
Résultats Agent
Pas encore de données de résultats Agent
Documentation
Contexte README/SKILL.md solide
Résumé des risques
Revoir avant production
- Repository license is unknown, which creates ambiguity about the legal terms for reuse.
- Financial research output is not financial advice; require human review before any live investment decision.
- La licence est ambiguë
- Quality score needs review
Préparation à l’installation
Chemin d’installation disponible
- Le chemin d’installation est disponible
- La preuve du dépôt est disponible
- La licence est ambiguë
- Pas encore de preuve de résultat Agent-Proven
Métadonnées lisibles par Agent
Données de décision lisibles par machine pour ce skill.
Utilisez ce bloc ou le JSON intégré pour décider si un Agent doit installer ce skill, choisir une alternative ou demander d’abord une revue humaine.
Tâches adaptées
- Workflows d’Agents de recherche
- Équipes Claude Code
- builders willing to evaluate younger projects
- Sources de recherche
Agents adaptés
Décision d’installation
- Commande
- npx skills add jparkerweb/ai-assist-skills --skill ai-assist-dockerize-website
- Politique
- Bloquer
- Revue humaine
- Oui
Confiance et risque
- Confiance
- 54/100
- Audit
- 70/100
- Niveau de risque
- Revue nécessaire
Boucle de résultat
- Endpoint
- /api/agent/outcome
- ID d’événement
- resolve
- Résultats
- 5
Commande d’installation
npx skills add jparkerweb/ai-assist-skills --skill ai-assist-dockerize-websiteNe pas utiliser quand
- Équipes qui nécessitent un SLA soutenu par le fournisseur
- production agents without a repository review
- Repository license is unknown, which creates ambiguity about the legal terms for reuse.
- Indices de permissions à haut risque : Shell or command execution, Secrets or environment access
- La licence est ambiguë
Skill alternatif
Last30days Skill
53.5K Stars
npx skills add mvanhorn/last30days-skill -g
Skill alternatif
Academic Research Skills
38.4K Stars
npx skills add Imbad0202/academic-research-skills
Skill alternatif
GPT Researcher
28.0K Stars
npx skills add assafelovic/gpt-researcher
Skill alternatif
DeepResearch
19.8K Stars
npx skills add Alibaba-NLP/DeepResearch
Sécurité Agent v2
26/100 · Éviter l’installation automatique
This skill should not be selected by an agent without explicit human security review.
Do not auto-install. Inspect the source, dependencies, and permission surface first.
Élevé
Exécution shell ou de commande
Les métadonnées de la skill font référence à des workflows de terminal, CLI, shell, sous-processus ou exécution de commande.
Moyen
Browser automation
Skill may drive a browser or interact with web pages.
Moyen
Accès réseau
La skill récupère probablement des pages distantes, API, dépôts ou services externes.
Moyen
Accès au système de fichiers
La skill peut lire ou écrire des fichiers de projet, documents, artefacts générés ou l’état local de l’espace de travail.
- Indices de permissions à haut risque : Shell or command execution, Secrets or environment access
- La licence est ambiguë
Cibles d’installation
Installer ce skill dans votre workflow Agent
Utilisez le point de terminaison public pour récupérer la commande, la checklist, les prompts et les liens canoniques.
OpenAgentSkill CLI
Resolve policy, run the source installer safely, and report a verified install receipt.
$ npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install jparkerweb-ai-assist-dockerize-websitePlan de résolution Agent
Laissez un Agent vérifier la pertinence avant l’installation.
L’API Resolve renvoie la skill sélectionnée, des alternatives, la politique de sécurité, les notes d’audit, la cible d’installation et un prompt prêt à l’emploi.
Ouvrir JSON
/api/agent/resolve?task=Use%20ai-assist-dockerize-website%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Texte Resolve
/api/agent/resolve?task=Use%20ai-assist-dockerize-website%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Relais d’installation
/api/skills/jparkerweb-ai-assist-dockerize-website/install
L’Agent doit vérifier
- Task fit and alternatives from Resolve API.
- Audit score, trust score, and safety policy warnings.
- Install target compatibility for Codex, Claude Code, Cursor, or CLI.
Copier le prompt
Task: Use ai-assist-dockerize-website in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20ai-assist-dockerize-website%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/jparkerweb-ai-assist-dockerize-website/install
Install command: npx skills add jparkerweb/ai-assist-skills --skill ai-assist-dockerize-website
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Relais Agent
Donnez à l’Agent le chemin d’installation, pas un autre annuaire.
Utilisez le point de terminaison public pour récupérer la commande, la checklist, les prompts et les liens canoniques.
Relais d’installation
/api/skills/jparkerweb-ai-assist-dockerize-website/install
Format texte LLM
/api/skills/jparkerweb-ai-assist-dockerize-website/install?format=text
Trouver des alternatives
/api/skills/search?q=ai-assist-dockerize-website&limit=3
Prompt Agent
Use ai-assist-dockerize-website for this task. Review https://www.openagentskill.com/api/skills/jparkerweb-ai-assist-dockerize-website/install, then install with: npx skills add jparkerweb/ai-assist-skills --skill ai-assist-dockerize-websiteMétadonnées Registry
Profil lisible par Agent pour la sélection automatique de skills.
L’API Registry fournit les signaux de décision, confiance, audit, cas d’usage et installation sans analyser l’interface.
Manifest
/api/registry/manifest/jparkerweb-ai-assist-dockerize-website
Texte LLM
/api/registry/manifest/jparkerweb-ai-assist-dockerize-website?format=text
Alias d’installation
/api/registry/install/jparkerweb-ai-assist-dockerize-website
Recommander
/api/registry/recommend?task=Use%20ai-assist-dockerize-website%20in%20an%20agent%20workflow&limit=3
Adéquation Agent
Agents de recherche
Tags de cas d’usage
Plateformes
Claude Code, Browser agents
Rapport d’audit
Revue nécessaire · 70/100
Revue lisible par machine de la préparation à l’installation, des métadonnées de sécurité, de la maintenance et du risque d’adoption.
Panneau de décision Agent
Fallback candidate for Research agents
Prototype with this skill first; keep a fallback candidate ready.
Rôle dans la pile
Candidate de secours
Pertinence principale
Agents de recherche
Libellé de confiance
Prototyper d’abord
Chemin d’installation
Commande prête
À utiliser lorsque
- Workflows d’Agents de recherche
- Équipes Claude Code
- builders willing to evaluate younger projects
Preuves
- recent repository activity
- install command or GitHub repo available
- profil qualité 61/100
- 10 événements OpenAgentSkill
revoir d’abord
- Repository license is unknown, which creates ambiguity about the legal terms for reuse.
Chemin d’implémentation
- 1Installez-le dans un Agent en sandbox et exécutez une tâche de Agents de recherche de bout en bout.
- 2Compare output quality, latency, and failure behavior against at least one alternative.
- 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.
Profil de confiance
Do not auto-install
Trust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
Adoption GitHub
Vérifier88 stars GitHub
Activité stars/forks
Vérifier88 stars et 12 forks; l’activité des issues n’est pas disponible dans les métadonnées actuelles
Maintenance récente
ValidéMis à jour aujourd’hui
Clarté de licence
VérifierInconnu
Signaux positifs
- Revue IA approuvée
- Le chemin d’installation est disponible
- La preuve du dépôt est disponible
- Dépôt maintenu récemment
- La commande d’installation ne présente aucun motif de haut risque évident
- La boucle de résultats est prête mais nécessite la première exécution réelle de l’Agent
Réviser avant installation
- Repository license is unknown, which creates ambiguity about the legal terms for reuse.
- Financial research output is not financial advice; require human review before any live investment decision.
- La licence est ambiguë
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- GitHub adoption: 88 GitHub stars
- Stars/forks activity: 88 stars, 12 forks; issue activity unavailable in current metadata
- License clarity: Unknown
- Dependency/runtime risk: command execution surface, credential or environment access
- Permission surface: secrets or environment access, shell or command execution
- Pas encore de rapports de résultats Agent réels
- Une revue humaine est requise avant une installation sans surveillance
Action recommandée
Choose a stronger alternative or inspect the source manually before any install attempt.
Profil qualité
Prometteur candidat pour les workflows Agent
Useful candidate, but compare it with alternatives before adopting.
Adéquation au workflow
Utilisez cette skill dans ces scénarios
Investigate faster
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Operate local tools
Local desktop
I need my agent to operate local files and desktop apps in a repeatable workflow.
Operate web apps
Browser automation
I need my agent to control a browser, fill forms, and verify web app workflows.
Adéquation au workflow
Ajouter à un workflow complet
Find, compare, and synthesize
Research report agent
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Operate and verify web apps
Browser QA agent
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Scrape, clean, and reuse web data
Web data pipeline
A practical workflow for agents that crawl public pages, extract clean content, normalize data, and hand it to downstream research or RAG workflows.
Liste d’alternatives
Comparer avant installation
Similar skills that may fit this task.
Last30days Skill
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
Academic Research Skills
Academic Research Skills for Claude Code: research → write → review → revise → finalize
GPT Researcher
Run autonomous deep research over web and local sources
DeepResearch
Tongyi Deep Research, the Leading Open-source Deep Research Agent
Vue d’ensemble
--- name: ai-assist-dockerize-website description: "Guide the user through containerizing and serving a simple website or documentation folder with Docker — inspects the project to detect what to serve (ready-to-serve static HTML, a buildable site that emits static output, or a raw markdown/docs folder that needs rendering), generates a Dockerfile, .dockerignore, docker-compose.yml, helper run/build commands, and a 'Running with Docker' README section, then offers to build and smoke-test the container and publish the image to Docker Hub or GHCR. Uses nginx:alpine for static content and a multi-stage build when the site must be generated. Only invoke when the user explicitly types /ai-assist-dockerize-website. Never auto-trigger from general conversation about Docker, containers, websites, or Dockerfiles." argument-hint: "[path-to-site-or-docs-folder] [--port <port>]" ---
# Dockerize a Website
This skill is invoked **manually** — only when the user explicitly runs `/ai-assist-dockerize-website`. Don't auto-trigger it from general talk about Docker, containers, or websites.
Guide the user from a project folder to a working Docker container that serves their site or documentation. The skill is **interactive and guided**, not a one-shot script: inspect the project, propose a sensible plan, confirm a few details, generate the files, then offer to build/test and publish.
The spine is: **detect → confirm → generate → offer to test → offer to publish.** Lead with a good default at every step so the user is confirming, not configuring from scratch.
## When to use
Use this whenever the user wants to serve a *static* website or a *documentation* folder out of a container — loose HTML/CSS/JS, the build output of a site generator, or a folder of markdown docs. The "project with a docs folder" case is the bullseye.
## Out of scope — dynamic apps
This skill serves static content. If the project is a **dynamic app** that runs code per request — an Express/Fastify/Nest server, Next.js in SSR mode, Flask/Django/FastAPI, a Go/Rust web server, anything with a long-running `start`/`serve` process and a port it listens on — stop and say so plainly. Containerizing those means basing the image on the app's own runtime and running its start command, which is a different job. Detect this case (see below), tell the user, and don't half-build a static image that won't actually run their app.
Don't leave them stranded, though. After declining, offer a real next step: a correct container for a dynamic app is based on the app's own runtime (e.g. `node:22-alpine`), installs its dependencies, runs the start command, and exposes the port the app listens on. Offer to hand-write that separately — it's just outside this skill's static-hosting scope.
## Step 1 — Inspect and classify the project
Before asking anything, look at what's there so the proposal is concrete. If the user named a folder (argument or in their message), focus on it; otherwise scan the working directory.
Classify into one of four strategies:
| Signals found | Strategy | |---|---| | An `index.html` ready to serve — at the project root, or in `dist/`, `build/`, `out/`, `public/`, `_site/`, `site/`, `www/` | **A · Ready static** — single-stage nginx, copy the folder in | | Site-generator tooling: `package.json` with a `build` script + a static framework (Vite, Astro, Eleventy, Docusaurus, Gatsby, SvelteKit static), or a config file (`mkdocs.yml`, `docusaurus.config.*`, `astro.config.*`, `_config.yml`, `hugo.toml`/`config.toml`, `.eleventy.js`) | **B · Buildable** — multi-stage build → nginx | | A folder of `.md` docs with **no** generator configured | **C · Raw docs** — offer to render (recommended) or serve as-is | | A long-running server: `package.json` `start` runs a server (`node server.js`), source calls `.listen()`, or a web framework (Express, Next SSR, Flask, Django, FastAPI, Go/Rust server) | **D · Dynamic app** — stop, explain, don't build |
State your finding in one line — e.g. *"Found a built site in `dist/` with an `index.html`, so I'll serve it directly with nginx (strategy A)."* — and let the user correct you if the detection is off.
For **strategy B and C**, the build/render details live in `references/recipes.md`. Read that file when you land on those paths — it has the multi-stage Dockerfiles per generator (Node SSGs, MkDocs, Hugo, Jekyll), the SPA fallback config, the raw-markdown render path, caching headers, the non-root variant, and a Caddy alternative.
## Step 2 — Confirm the details
Pre-fill every answer from Step 1 so these are quick confirmations, not an interrogation:
- **What to serve** — the folder (strategy A) or the build output directory (strategy B/C). Show the path you detected. - **Port** — what host port to expose. Default `8080` (avoids clashing with anything already on `80`). Honor `--port` if given. - **Image / container name** — propose one lowercase-hyphenated name for both. Default to the **project folder** name, but prefer a more meaningful name when one is obvious — a `package.json` `name`, or a clear title in the README — e.g. favor `marketing-site` over a generic folder like `app` or `vite-app`. Always let the user override. - **Compose?** — yes by default (one-command up/down). Mention they can skip it. - For **strategy C**, confirm they want the docs *rendered* (recommended — browsers download raw `.md` instead of displaying it) versus served as raw files.
Skip questions whose answers are obvious or already given. The user invited a guided flow, not a form.
## Step 3 — Generate the artifacts
Generate all of these, tailored to the chosen strategy. Substitute the real folder, port, and names — don't leave placeholders in the files you write.
### Dockerfile (strategy A — ready static)
```dockerfile # syntax=docker/dockerfile:1 FROM nginx:1.27-alpine
# Copy the site into nginx's web root. COPY <SITE_DIR>/ /usr/share/nginx/html/
EXPOSE 80
# Fail the container's health check if nginx stops serving. # busybox wget ships in the alpine image, so no extra install is needed. HEALTHCHECK --interval=30s --timeout=3s --start-period=5s \ CMD wget -q --spider http://localhost/ || exit 1 ```
Pin the base image to a real minor tag (e.g. `nginx:1.27-alpine`) rather than the floating `nginx:alpine`, so a rebuild months from now doesn't silently pull a different nginx. Mention this so the user knows to bump it deliberately.
The build context is the project root (compose uses `build: .`), so `COPY` paths are relative to it: copy the served folder by its path from the root — `COPY public/ …` when the site lives in `public/`, or `COPY . …` when the site *is* the project root (then lean on `.dockerignore` to keep junk out).
For **strategy B/C**, use the matching multi-stage Dockerfile from `references/recipes.md` — a builder stage runs the generator, and only its static output is copied into the nginx stage, so build tooling never ships in the final image.
### .dockerignore
Keep the build context small and the image clean:
```gitignore .git .gitignore node_modules npm-debug.log* .env .env.* .DS_Store Thumbs.db Dockerfile* .dockerignore docker-compose*.yml ```
Tailor it to the project. For a multi-stage build (strategy B/C), also ignore the local build-output directory (`dist`, `build`, `_site`, `out`, `site`, …) — it's regenerated inside the image, and shipping a stale host copy into the build context only bloats it. The "don't ignore your content" rule is about *source* you serve directly (strategy A), not generated output.
### docker-compose.yml
```yaml services: web: build: . image: <IMAGE_NAME>:latest container_name: <CONTAINER_NAME> ports: - "<HOST_PORT>:80" restart: unless-stopped healthcheck: test: ["CMD", "wget", "-q", "--spider", "http://localhost/"] interval: 30s timeout: 3s retries: 3 start_period: 5s ```
No top-level `version:` key — it's obsolete in Compose v2 and prints a warning.
### Helper commands + README section
Append a "Running with Docker" section to the project's `README.md` (or create a short `DOCKER.md` if there's no README). The commands are identical in PowerShell and bash, so no per-shell variants are needed.
The block below is the template; its outer 4-backtick fence is only the boundary so the inner blocks display here. When you write the actual file, use normal **3-backtick** fences for the `bash` blocks — don't copy the 4-backtick wrapper.
````markdown ## Running with Docker
This site is served by nginx in a container.
### Quick start (Docker Compose)
```bash docker compose up -d --build # build the image and start in the background # open http://localhost:<HOST_PORT> docker compose logs -f # follow logs docker compose down # stop and remove ```
### Without Compose
```bash docker build -t <IMAGE_NAME> . docker run -d --name <CONTAINER_NAME> -p <HOST_PORT>:80 <IMAGE_NAME> docker stop <CONTAINER_NAME> && docker rm <CONTAINER_NAME> ``` ````
After writing the files, summarize what you created and the one command to run it.
## Step 4 — Offer to build and smoke-test
Don't build automatically — the user may not have Docker running, or may want to review the files first. Ask: *"Want me to build it and confirm it serves?"*
If yes:
1. Check the daemon is up first with `docker info`. If it fails, tell the user to start Docker Desktop and stop here — the files are already written and ready whenever they are. 2. Build and start: `docker compose up -d --build` (or `docker build` + `docker run` if they skipped compose). 3. Smoke-test the URL — request `http://localhost:<HOST_PORT>/` and confirm an HTTP 200 with non-empty HTML. On Windows use `curl.exe` or PowerShell's `Invoke-WebRequest`; give nginx a second to come up and retry once or twice before calling it a failure. 4. Report the result. Leave it running if they want to look at it, or tear down with `docker compose down`. If you started a throwaway container by hand, clean it up.
If the build or smoke-test fails, read the actual error (`docker compose logs`) and fix the real cause — a wrong output directory, a missing build step, a port already in use — rather than guessing.
## Step 5 — Offer to publish (optional)
Once it runs locally, offer to push the image to a registry so it can be shared or deployed. Only do this if the user wants it. Read `references/registry-publish.md` for the Docker Hub and GHCR walkthrough (login, tag, push, image naming, and the multi-arch `--platform` note for Apple-Silicon-built images headed to amd64 servers).
## Conventions and rationale
- **nginx:alpine for static** — tiny, battle-tested, zero app code to maintain. Reach for the Caddy alternative (in recipes) only when the user wants dead-simple config or automatic file serving. - **Multi-stage when building** — the final image carries only the rendered site, not Node/Python/Hugo and their caches. Smaller image, smaller attack surface. - **Pin the base image** to a minor tag so rebuilds are reproducible. - **Default to port 8080** on the host to avoid colliding with whatever already owns `80`. - **Non-root** is available via `nginxinc/nginx-unprivileged` (recipes) for stricter environments — note it as an option rather than forcing it. - **No secrets in the image** — static hosting rarely needs any; if the user mentions API keys or env config, that's a sign this is really a dynamic app (strategy D).
## Reference files
- `references/recipes.md` — multi-stage Dockerfiles per generator (Node SSGs, MkDocs, Hugo, Jekyll), the raw-markdown render path, SPA fallback, caching headers, non-root, and the Caddy alternative. Read it for strategy B or C. - `references/registry-publish.md` — pushing the image to Docker Hub or GHCR. Read it for Step 5.
Détails techniques
- Version
- 1.0.0
- Licence
- Unknown
- Dernière mise à jour
- 23 août 2026
- Publié
- 21 août 2026
Instantané de décision
Candidate de secours
recent repository activity
Audit
Revue d’installation
Revue d’installation et d’adoption
- Sécurité
- 63/100
- Maintenance
- 100/100
- Installer
- 92/100
Preuves validées par Agent
Preuves validées par Agent
Rapports après resolve, revue, installation et une exécution limitée.
- Taux de réussite
- —
- Échec récent
- —
- Résultats
- 0
- Qualité de sortie
- —
- Échecs
- 0
- Non pertinent
- 0
- Installations
- 0
- Bloqué par le risque
- 0
- Configuration requise
- 0
- Production
- 0
Aucune donnée de résultat Agent pour l’instant. La première exécution peut signaler succès, besoin de configuration, blocage de risque, échec ou non-pertinence via /api/agent/outcome.
Installer
Ajouter au workflow Agent
Gratuit et open source. Examinez le rapport avant l’installation dans des Agents de production.
Boucle de croissance
Kit de partage
Brouillon guidé par scénario pour ai-assist-dockerize-website, prêt pour une publication manuelle sur X.
ai-assist-dockerize-website: Guide the user through containerizing and serving a simple website or documentation folder wi... 88 stars https://www.openagentskill.com/skills/jparkerweb-ai-assist-dockerize-website?ref=x
Réponse facultative avec commande d’installation
Listing + install path for ai-assist-dockerize-website: https://www.openagentskill.com/skills/jparkerweb-ai-assist-dockerize-website?ref=x Install: npx skills add jparkerweb/ai-assist-skills --skill ai-assist-dockerize-website
Source de la fiche
Indexé par Registry
Cette fiche a été indexée à partir de sources publiques et n’est pas marquée officielle tant qu’une revendication de mainteneur n’est pas approuvée.
- Créateur
- jparkerweb
- Indexé par
- Index communautaire OpenAgentSkill
L’attribution renvoie au dépôt public ou au profil du créateur. Les créateurs peuvent revendiquer la fiche pour mettre à jour les signaux de propriété.
Revendiquer ce skillRevendication du propriétaire
Revendiquer cette fiche de skill
Cette fiche Indexé par Registry est attribuée à jparkerweb, mais n’est pas encore marquée officielle. Revendiquez-la pour ajouter un signal de propriétaire vérifié et rendre les futures mises à jour de lancement, d’installation et d’audit plus fiables.
Kit de backlinks créateur
Ajoutez les badges de preuve à votre README
Affichez la fiche canonique, les signaux actuels de confiance et d’audit, ainsi que de vraies preuves Agent-Proven là où les développeurs évaluent le dépôt.
[](https://www.openagentskill.com/skills/jparkerweb-ai-assist-dockerize-website)
[](https://www.openagentskill.com/skills/jparkerweb-ai-assist-dockerize-website)
[](https://www.openagentskill.com/skills/jparkerweb-ai-assist-dockerize-website/audit)
[](https://www.openagentskill.com/skills/jparkerweb-ai-assist-dockerize-website)Auteur
jparkerweb
@jparkerweb
Tags
Adéquation plateforme
Signaux de santé
- Stars GitHub
- 88
- Score de qualité
- 37/100
- Dernier push GitHub
- 22 août 2026
- Indications de framework
- Inconnu
- Vues OpenAgentSkill
- 10
- Copies d’installation
- 0
- Clics sortants
- 0
Signal de communauté
Indiquez si ce skill semble utile à votre workflow Agent. Les retours agrégés améliorent le classement au fil du temps.
Confiance et sécurité
Do not auto-install
- Adoption GitHub88 stars GitHubVérifier
- Activité stars/forks88 stars et 12 forks; l’activité des issues n’est pas disponible dans les métadonnées actuellesVérifier
- Maintenance récenteMis à jour aujourd’huiValidé
- Clarté de licenceInconnuVérifier
- Complétude README/SKILL.mdLes métadonnées incluent suffisamment de contexte d’usage et de workflowValidé
- Risque dépendances/runtimecommand execution surface, credential or environment accessCorriger
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