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social-app/.opencode/commands/trellis/start.md
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# Start Session
Initialize your AI development session and begin working on tasks.
---
## Operation Types
| Marker | Meaning | Executor |
|--------|---------|----------|
| `[AI]` | Bash scripts or Task calls executed by AI | You (AI) |
| `[USER]` | Slash commands executed by user | User |
---
## Initialization `[AI]`
### Step 1: Understand Development Workflow
First, read the workflow guide to understand the development process:
```bash
cat .trellis/workflow.md
```
**Follow the instructions in workflow.md** - it contains:
- Core principles (Read Before Write, Follow Standards, etc.)
- File system structure
- Development process
- Best practices
### Step 2: Get Current Context
```bash
python3 ./.trellis/scripts/get_context.py
```
This shows: developer identity, git status, current task (if any), active tasks.
### Step 3: Read Guidelines Index
```bash
cat .trellis/spec/frontend/index.md # Frontend guidelines
cat .trellis/spec/backend/index.md # Backend guidelines
cat .trellis/spec/guides/index.md # Thinking guides
```
> **Important**: The index files are navigation — they list the actual guideline files (e.g., `error-handling.md`, `conventions.md`, `mock-strategies.md`).
> At this step, just read the indexes to understand what's available.
> When you start actual development, you MUST go back and read the specific guideline files relevant to your task, as listed in the index's Pre-Development Checklist.
### Step 4: Report and Ask
Report what you learned and ask: "What would you like to work on?"
---
## Task Classification
When user describes a task, classify it:
| Type | Criteria | Workflow |
|------|----------|----------|
| **Question** | User asks about code, architecture, or how something works | Answer directly |
| **Trivial Fix** | Typo fix, comment update, single-line change, < 5 minutes | Direct Edit |
| **Simple Task** | Clear goal, 1-2 files, well-defined scope | Quick confirm → Task Workflow |
| **Complex Task** | Vague goal, multiple files, architectural decisions | **Brainstorm → Task Workflow** |
### Decision Rule
> **If in doubt, use Brainstorm + Task Workflow.**
>
> Task Workflow ensures code-spec context is injected to agents, resulting in higher quality code.
> The overhead is minimal, but the benefit is significant.
---
## Question / Trivial Fix
For questions or trivial fixes, work directly:
1. Answer question or make the fix
2. If code was changed, remind user to run `/trellis:finish-work`
---
## Complex Task - Brainstorm First
For complex or vague tasks, **automatically start the brainstorm process** — do NOT skip directly to implementation.
See `/trellis:brainstorm` for the full process. Summary:
1. **Acknowledge and classify** - State your understanding
2. **Create task directory** - Track evolving requirements in `prd.md`
3. **Ask questions one at a time** - Update PRD after each answer
4. **Propose approaches** - For architectural decisions
5. **Confirm final requirements** - Get explicit approval
6. **Proceed to Task Workflow** - With clear requirements in PRD
> **Subtask Decomposition**: If brainstorm reveals multiple independent work items,
> consider creating subtasks using `--parent` flag or `add-subtask` command.
> See `/trellis:brainstorm` Step 8 for details.
---
## Task Workflow (Development Tasks)
**Why this workflow?**
- Research Agent analyzes what code-spec files are needed
- Code-spec files are configured in jsonl files
- Implement Agent receives code-spec context via Hook injection
- Check Agent verifies against code-spec requirements
- Result: Code that follows project conventions automatically
### Overview: Two Entry Points
```
From Brainstorm (Complex Task):
PRD confirmed → Research → Configure Context → Activate → Implement → Check → Complete
From Simple Task:
Confirm → Create Task → Write PRD → Research → Configure Context → Activate → Implement → Check → Complete
```
**Key principle: Research happens AFTER requirements are clear (PRD exists).**
---
### Phase 1: Establish Requirements
#### Path A: From Brainstorm (skip to Phase 2)
PRD and task directory already exist from brainstorm. Skip directly to Phase 2.
#### Path B: From Simple Task
**Step 1: Confirm Understanding** `[AI]`
Quick confirm:
- What is the goal?
- What type of development? (frontend / backend / fullstack)
- Any specific requirements or constraints?
**Step 2: Create Task Directory** `[AI]`
```bash
TASK_DIR=$(python3 ./.trellis/scripts/task.py create "<title>" --slug <name>)
```
**Step 3: Write PRD** `[AI]`
Create `prd.md` in the task directory with:
```markdown
# <Task Title>
## Goal
<What we're trying to achieve>
## Requirements
- <Requirement 1>
- <Requirement 2>
## Acceptance Criteria
- [ ] <Criterion 1>
- [ ] <Criterion 2>
## Technical Notes
<Any technical decisions or constraints>
```
---
### Phase 2: Prepare for Implementation (shared)
> Both paths converge here. PRD and task directory must exist before proceeding.
**Step 4: Code-Spec Depth Check** `[AI]`
If the task touches infra or cross-layer contracts, do not start implementation until code-spec depth is defined.
Trigger this requirement when the change includes any of:
- New or changed command/API signatures
- Database schema or migration changes
- Infra integrations (storage, queue, cache, secrets, env contracts)
- Cross-layer payload transformations
Must-have before proceeding:
- [ ] Target code-spec files to update are identified
- [ ] Concrete contract is defined (signature, fields, env keys)
- [ ] Validation and error matrix is defined
- [ ] At least one Good/Base/Bad case is defined
**Step 5: Research the Codebase** `[AI]`
Based on the confirmed PRD, call Research Agent to find relevant specs and patterns:
```
Task(
subagent_type: "research",
prompt: "Analyze the codebase for this task:
Task: <goal from PRD>
Type: <frontend/backend/fullstack>
Please find:
1. Relevant code-spec files in .trellis/spec/
2. Existing code patterns to follow (find 2-3 examples)
3. Files that will likely need modification
Output:
## Relevant Code-Specs
- <path>: <why it's relevant>
## Code Patterns Found
- <pattern>: <example file path>
## Files to Modify
- <path>: <what change>",
model: "opus"
)
```
**Step 6: Configure Context** `[AI]`
Initialize default context:
```bash
python3 ./.trellis/scripts/task.py init-context "$TASK_DIR" <type>
# type: backend | frontend | fullstack
```
Add code-spec files found by Research Agent:
```bash
# For each relevant code-spec and code pattern:
python3 ./.trellis/scripts/task.py add-context "$TASK_DIR" implement "<path>" "<reason>"
python3 ./.trellis/scripts/task.py add-context "$TASK_DIR" check "<path>" "<reason>"
```
**Step 7: Activate Task** `[AI]`
```bash
python3 ./.trellis/scripts/task.py start "$TASK_DIR"
```
This sets `.current-task` so hooks can inject context.
---
### Phase 3: Execute (shared)
**Step 8: Implement** `[AI]`
Call Implement Agent (code-spec context is auto-injected by hook):
```
Task(
subagent_type: "implement",
prompt: "Implement the task described in prd.md.
Follow all code-spec files that have been injected into your context.
Run lint and typecheck before finishing.",
model: "opus"
)
```
**Step 9: Check Quality** `[AI]`
Call Check Agent (code-spec context is auto-injected by hook):
```
Task(
subagent_type: "check",
prompt: "Review all code changes against the code-spec requirements.
Fix any issues you find directly.
Ensure lint and typecheck pass.",
model: "opus"
)
```
**Step 10: Complete** `[AI]`
1. Verify lint and typecheck pass
2. Report what was implemented
3. Remind user to:
- Test the changes
- Commit when ready
- Run `/trellis:record-session` to record this session
---
## Continuing Existing Task
If `get_context.py` shows a current task:
1. Read the task's `prd.md` to understand the goal
2. Check `task.json` for current status and phase
3. Ask user: "Continue working on <task-name>?"
If yes, resume from the appropriate step (usually Step 7 or 8).
---
## Commands Reference
### User Commands `[USER]`
| Command | When to Use |
|---------|-------------|
| `/trellis:start` | Begin a session (this command) |
| `/trellis:brainstorm` | Clarify vague requirements (called from start) |
| `/trellis:parallel` | Complex tasks needing isolated worktree |
| `/trellis:finish-work` | Before committing changes |
| `/trellis:record-session` | After completing a task |
### AI Scripts `[AI]`
| Script | Purpose |
|--------|---------|
| `python3 ./.trellis/scripts/get_context.py` | Get session context |
| `python3 ./.trellis/scripts/task.py create` | Create task directory |
| `python3 ./.trellis/scripts/task.py init-context` | Initialize jsonl files |
| `python3 ./.trellis/scripts/task.py add-context` | Add code-spec/context file to jsonl |
| `python3 ./.trellis/scripts/task.py start` | Set current task |
| `python3 ./.trellis/scripts/task.py finish` | Clear current task |
| `python3 ./.trellis/scripts/task.py archive` | Archive completed task |
### Sub Agents `[AI]`
| Agent | Purpose | Hook Injection |
|-------|---------|----------------|
| research | Analyze codebase | No (reads directly) |
| implement | Write code | Yes (implement.jsonl) |
| check | Review & fix | Yes (check.jsonl) |
| debug | Fix specific issues | Yes (debug.jsonl) |
---
## Key Principle
> **Code-spec context is injected, not remembered.**
>
> The Task Workflow ensures agents receive relevant code-spec context automatically.
> This is more reliable than hoping the AI "remembers" conventions.