Add a sample-app-generator skill: scaffold runnable starter apps against an Azure DocumentDB cluster
Nadie ha tomado este issue todavía.
Evaluación
- Dificultad
- 5/5
- Tiempo estimado
- Más de una semana
- Aptitud para principiantes
- 35/100
- Tipo de issue
- Nueva funcionalidad
- Claridad
- Bastante claro
- Estado de actividad
- Tranquilo
Línea de trabajo
Lee primero el patrón existente de skills//SKILL.md, docs/SKILLS.md y scripts/validate-skills.ps1; después, inspecciona las skills referenciadas de security, high-availability y full-text-search. Resuelve las preguntas abiertas sobre generation y Java-framework, añade las reglas y plantillas de Node.js/Python propuestas, y valida la skill. La tarea estará terminada cuando se cumplan los criterios de aceptación, incluida la verificación del maintainer contra un clúster activo.
Escrito por el modelo de indexación a partir del texto del issue.
Descripción
Summary
Add a new skill — sample-app-generator — that scaffolds a runnable starter application against an Azure DocumentDB cluster. The skill should let an agent generate a minimal but production-shaped sample app for a target language/framework, wire it up to a user-provided cluster, and verify the connection works end-to-end.
Motivation
Every developer onboarding to Azure DocumentDB writes essentially the same first hundred lines: connection-string handling, TLS, retry, a minimal CRUD path, and a way to confirm "yes, I'm actually connected." Today there is no canonical scaffold and the existing skills (security, storage, HA, full-text-search) all assume the developer has already got a working client.
A sample-app-generator skill closes that gap and gives the rest of the agent-kit a concrete launch surface: "generate the starter, then ask me about indexing / FTS / RBAC."
Proposed scope
In scope (v1)
- Language / framework matrix — minimum viable set:
- Node.js + native
mongodbdriver - Python +
pymongo - C# +
MongoDB.Driver - Java +
mongodb-driver-sync
- Node.js + native
- Generated app shape (same across languages):
README.mdwith run instructions- Config via environment variables (
DOCUMENTDB_CONNECTION_STRING,DOCUMENTDB_DATABASE) - TLS-enabled client construction (matches
security-tls-requiredrule) - One
database+ onecollection - CRUD endpoints / functions: insert, find-by-id, update, delete, list-paged
- A
/healthz-style probe that does apingagainst the cluster - Basic retry with backoff on transient errors
- Dockerfile (where it makes sense) +
.env.example
- Auth modes — the generator should support choosing one at scaffold time:
- Connection-string + native admin user (default, easiest)
- Microsoft Entra ID via managed identity (matches
security-entra-rbacrule) — generated samples show theMONGODB-OIDCmechanism wired in
- Optional add-on flags:
--with-fts→ add a vector / full-text search example collection and a search endpoint (links into the existingfull-text-searchskill)--with-private-endpoint→ emit a Bicep snippet alongside the app for cluster + PE provisioning (links intosecurity-private-endpoint)
- Validation step — the skill should be able to run the generated app's
/healthzprobe to confirm the connection string works before handing off to the user.
Out of scope (v1)
- Migrating from MongoDB Atlas / CosmosDB-Mongo-vCore — that's a separate "migration" skill.
- Multi-region or read-replica wiring — covered by HA skill; the generator may reference it but not duplicate it.
- ORM-style abstractions (Mongoose, EF Core mappings) — keep v1 driver-native to stay close to the wire.
- Web UI / front-end — the sample is API/CLI only.
Proposed skill layout
Following the existing agent-kit pattern (skills/<name>/SKILL.md + rule files):
skills/sample-app-generator/
├── SKILL.md
├── rules/
│ ├── generator-language-matrix.md # which langs/frameworks are supported and why
│ ├── generator-connection-config.md # env-var contract, TLS, retry defaults
│ ├── generator-auth-mode-selection.md # native-user vs Entra OIDC; when to choose which
│ ├── generator-crud-shape.md # canonical CRUD endpoint/function signatures
│ ├── generator-healthz-probe.md # what a working probe looks like; failure modes
│ ├── generator-fts-addon.md # how the --with-fts flag composes with full-text-search skill
│ └── generator-private-endpoint-addon.md# how --with-private-endpoint composes with security skill
└── templates/
├── node/
├── python/
├── csharp/
└── java/
Templates live under templates/ and are rendered by the agent (or a small helper script in scripts/) given the user's choices.
Cross-references with existing skills
The generator deliberately doesn't re-state guidance that other skills own — it links to them:
| Generator concern | Owning skill |
|---|---|
| TLS on the client | security/security-tls-required |
| Auth mode (Entra OIDC) | security/security-entra-rbac, security/security-database-roles |
| Connection-string handling, admin password rotation | security/security-admin-password-and-identity-separation |
| Retry / replica behavior | high-availability/ |
Search / vector endpoints (--with-fts) |
full-text-search/ |
Private endpoint Bicep (--with-private-endpoint) |
security/security-private-endpoint |
Open questions
- Generation mechanism — pure-text templating with the agent doing the substitution, or a
cookiecutter-style helper script invoked by the skill? My instinct: start with text templates that the agent renders, ship a script later if it pays off. - Which Java framework — bare main + driver, Spring Boot, or both? Start with bare main and add Spring Boot in v1.1 unless feedback says otherwise.
- Versioning of generated apps — do we pin driver versions or use
latest? Pin, with a quarterly bump cadence. - Telemetry — should the generated app emit OpenTelemetry traces by default? Probably yes for production-shaped, but it bulks up the sample. Maybe behind a
--with-otelflag. - Test scaffolding — include a smoke-test file (one assertion per CRUD path) or leave it to the developer? Recommend yes, one per language, using each ecosystem's default runner.
Acceptance criteria
-
skills/sample-app-generator/SKILL.mdexists with frontmatter and is registered indocs/SKILLS.md. - All rule files listed in "Proposed skill layout" are present and pass
scripts/validate-skills.ps1. - Templates for at least Node.js and Python compile / run end-to-end against a live cluster (manual verification by a maintainer).
- A generated app's
/healthzprobe returns success against a real cluster using the default connection-string flow and the Entra-OIDC flow. - Cross-links to
security/,high-availability/,full-text-search/resolve.
Suggested follow-ups (not blockers)
- C# and Java templates if v1 lands with Node + Python first.
- IaC bundle: Bicep +
azd upintegration so--with-private-endpointcan provision a fully working cluster + PE in one shot. - Aspire-style local dev story (containerized DocumentDB emulator if/when available).
- Lenguaje dominante
- Python
- Estrellas
- 6
- Forks
- 11
- Merge medio
- 3 d 2 h
- PR fusionados (30 d)
- 1
Preparar el entorno
- Sin Dockerfile ni archivo de Docker Compose
- Sin plantilla de pull request
- Leer la guía de contribución
Primeros pasos
- Lee el issue completo y luego la guía de contribución del proyecto.
- Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
- Haz un fork del repositorio y trabaja en una rama.
- Abre un pull request que haga referencia al número del issue.
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