planner

Generate staged project plans from design through deployment. Use when planning App Platform projects, breaking complex deployments into resumable stages, or tracking multi-step infrastructure setup.

16 stars

Best use case

planner is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Generate staged project plans from design through deployment. Use when planning App Platform projects, breaking complex deployments into resumable stages, or tracking multi-step infrastructure setup.

Teams using planner should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/planner/SKILL.md --create-dirs "https://raw.githubusercontent.com/diegosouzapw/awesome-omni-skill/main/skills/backend/planner/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/planner/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How planner Compares

Feature / AgentplannerStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Generate staged project plans from design through deployment. Use when planning App Platform projects, breaking complex deployments into resumable stages, or tracking multi-step infrastructure setup.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Planner Skill

Generate staged project plans that break complex projects into manageable, resumable steps - from initial design through coding, testing, to cloud deployment.

> **Tip**: For a complete overview of all available skills, see the [root SKILL.md](../../SKILL.md).

---

## Greenfield vs Brownfield Detection

| Scenario | Detection | Behavior |
|----------|-----------|----------|
| **Greenfield** | No Dockerfiles, no `.do/app.yaml` | Create artifacts from scratch |
| **Brownfield** | Dockerfiles and/or `.do/app.yaml` exist | Review, validate, enhance existing |

The AI assistant automatically detects the project state. Don't recreate valid artifacts. The critical validation gate is `doctl app dev build` — if that passes, artifacts are correct.

---

## Why Staged Deployment?

Complex App Platform deployments fail when executed monolithically:

1. **Blind deployment fails** - Deploying without infrastructure prep results in cryptic errors
2. **Context is lost** - Credentials, cluster IDs, and progress are forgotten between sessions
3. **Debugging is harder** - When everything deploys at once, it's unclear which component failed
4. **Resumability is poor** - Starting over wastes time; partial progress isn't tracked

---

## Build Locally First

**CRITICAL**: Always validate builds locally before cloud deployment.

```bash
doctl app dev build                    # Build using local app spec
doctl app dev build --app <APP_ID>     # Build using existing deployed app
doctl app dev build --env-file .env    # Build with environment overrides
```

| Build Location | Feedback Time | Cost of Failure |
|----------------|---------------|-----------------|
| Cloud | 5-10 minutes | Wasted cycle, confusing logs |
| Local | 30-60 seconds | Immediate fix, clear errors |

**Full details**: See [build-local-first.md](reference/build-local-first.md)

---

## Tier Classification

### Detection from User Description

| User Mentions | Tier |
|--------------|------|
| "static", "frontend only", "no database", "SPA" | Tier 1 |
| "PostgreSQL", "MySQL", "database", "API + frontend" | Tier 2 |
| "Kafka", "OpenSearch", "workers", "event-driven", "microservices" | Tier 3 |

### Decision Tree

```
Does user mention Kafka, OpenSearch, workers, or "event-driven"?
  YES → Tier 3 (Complex)
  NO → Does user mention database (PostgreSQL, MySQL, MongoDB)?
         YES → Tier 2 (Database-backed)
         NO → Tier 1 (Simple)
```

### Detection from app.yaml (Fallback)

If `.do/app.yaml` exists:
- `workers` present → Tier 3
- `databases` with `KAFKA` or `OPENSEARCH` → Tier 3
- `databases` present → Tier 2
- Neither → Tier 1

---

## Tier Structures

### Tier 1: Simple (5 stages)

**Criteria**: Static sites, single service, no database

```
Plan/
├── 01-local-design.md
├── 02-local-coding.md
├── 03-local-testing.md
├── 04-cloud-deploy.md
└── 05-cloud-validate.md
```

**Examples**: Next.js static export, React SPA, Hugo site, Astro

### Tier 2: Database-Backed (7 stages)

**Criteria**: 1-2 services, single database (PostgreSQL/MySQL)

```
Plan/
├── 01-local-design.md
├── 02-local-coding.md
├── 03-local-testing.md
├── 04-cloud-database.md
├── 05-cloud-config.md
├── 06-cloud-deploy.md
└── 07-cloud-validate.md
```

**Examples**: Rails + PostgreSQL, Django + MySQL, Node.js API + Postgres

### Tier 3: Complex (9 stages)

**Criteria**: Multi-service, workers, Kafka/OpenSearch, VPC networking

```
Plan/
├── 01-local-design.md
├── 02-local-coding.md
├── 03-local-testing.md
├── 04-cloud-database-clusters.md
├── 05-cloud-config-users-topics.md
├── 06-cloud-debug-validation.md
├── 07-cloud-secrets-cicd.md
├── 08-cloud-deploy-production.md
└── 09-cloud-end-to-end.md
```

**Examples**: Event-driven microservices, ML pipelines, real-time analytics

> **CRITICAL: Tier 3 apps MUST use GitHub Actions for deployment**
>
> Tier 3 apps have `${SECRET_NAME}` placeholders only resolved by `digitalocean/app_action/deploy@v2`.
> - Set `deploy_on_push: false` in `.do/app.yaml`
> - Deploy via `git push` (triggers GitHub Actions), NOT `doctl apps create`

---

## Stage Templates

Stage templates are provided in the `templates/` directory:

| Directory | Purpose |
|-----------|---------|
| `templates/local/` | Local stages 1-3 (all tiers) |
| `templates/tier-1-simple/` | Tier 1 cloud stages |
| `templates/tier-2-database/` | Tier 2 cloud stages |
| `templates/tier-3-complex/` | Tier 3 cloud stages |

Each stage file follows this structure:

```markdown
# Stage N: [Stage Name]

**Status**: TODO
**Prerequisites**: Stage N-1 complete

## Tasks
- [ ] Task description
- [ ] Expected outcome

## Verification
[Commands to verify completion]

## Next Steps
Proceed to Stage N+1
```

**Key validation gate**: Stage 3 includes `doctl app dev build` and health check validation.

---

## Usage Examples

### Example 1: Simple Static Site

**User**: "Deploy a Next.js static site"

1. Detect Tier 1 (no database)
2. Generate 5 stage files in Plan/
3. Return: "Created 5-stage plan. Start with Stage 1: Local Design."

### Example 2: API with Database

**User**: "Node.js API with PostgreSQL"

1. Detect Tier 2 (PostgreSQL)
2. Generate 7 stage files in Plan/
3. Return: "Created 7-stage plan. Database cluster created in Stage 4."

### Example 3: Event-Driven Microservices

**User**: "Event-driven app with Kafka and OpenSearch"

1. Detect Tier 3 (Kafka + OpenSearch)
2. Generate 9 stage files in Plan/
3. Return: "Created 9-stage plan with debug container validation."

---

## Key Features

### Session Resumability
- Stage files persist in git (status tracking only)
- All captured values stored in `.env.secrets` (gitignored)
- AI assistants read `.env.secrets` to resume from any stage

### Artifact Storage
- Plan files contain **status only**, not secrets
- All IDs, passwords, URLs stored in `.env.secrets`
- See [artifact-storage.md](reference/artifact-storage.md) for philosophy

### Pause Points
- Each stage ends with verification checklist
- Explicit "proceed to Stage N+1" guidance
- Troubleshooting sections for common failures

---

## Reference Files

- **[build-local-first.md](reference/build-local-first.md)** — Full `doctl app dev build` workflow
- **[artifact-storage.md](reference/artifact-storage.md)** — Storage philosophy, AI instructions

---

## Integration with Other Skills

- **← designer**: Uses `.do/app.yaml` for complexity detection if exists
- **→ deployment**: Plan/ files provide context; Stage 7 creates GitHub Actions workflow
- **→ troubleshooting**: Plan/ stages help identify where failure occurred
- **→ devcontainers**: Local development setup for testing

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