Prompt Generator

Generate agent-ready prompts from existing task specification files in tasks/.

CRITICAL: Prompt Template Requirements

Every generated prompt file MUST include ALL of these sections (see Step 4 for full template):

Section	Purpose	Required
`=== CONTEXT ===`	Shared project context	YES
`=== OBJECTIVE ===`	Task goal	YES
`=== CONTRACTS ===`	Contract file references	YES
`=== FILES TO CREATE ===`	Scope CREATE	YES
`=== FILES TO MODIFY ===`	Scope MODIFY	YES
`=== DO NOT MODIFY ===`	Scope BOUNDARY	YES
`=== IMPLEMENTATION REQUIREMENTS ===`	Requirements	YES
`=== ACCEPTANCE CRITERIA ===`	Checklist	YES
`=== EXECUTION INSTRUCTIONS ===`	How to implement	MANDATORY
`=== IMPORTANT RULES ===`	Constraints	MANDATORY
`=== OUTPUT FORMAT (REQUIRED) ===`	JSON output block	MANDATORY
`=== COMPLETION SIGNAL ===`	touch .claude-task-complete	MANDATORY

DO NOT generate prompts without the EXECUTION INSTRUCTIONS, IMPORTANT RULES, OUTPUT FORMAT, and COMPLETION SIGNAL sections.

When to Use

After editing task files in tasks/
To regenerate prompts with updated template
Before running cpo run if prompts are missing
To test different prompt formats

Input Requirements

The parallel directory must have:

parallel/TS-XXXX-slug/
  manifest.json       # Required: wave structure, agents
  context.md          # Required: shared context
  contracts/          # Required: types.py, api-schema.yaml
  tasks/              # Required: task-*.md files
    task-001-users.md
    task-002-products.md

Output

Generates:

parallel/TS-XXXX-slug/
  prompts/
    agent-prompts.md   # Wave summary and launch commands
    task-001.txt       # Individual agent prompt
    task-002.txt
    ...

Workflow

mermaid

flowchart TB
    Start[("tasks/ folder")]
    Read["1. Read manifest.json"]
    Context["2. Load context.md"]
    Parse["3. Parse each task file"]
    Generate["4. Generate task-NNN.txt"]
    Summary["5. Create agent-prompts.md"]
    Done[("prompts/ ready")]

    Start --> Read
    Read --> Context
    Context --> Parse
    Parse --> Generate
    Generate --> Summary
    Summary --> Done

Step 1: Read manifest.json

Extract:

Wave structure and task ordering
Agent assignments per task
Tech spec reference
Technology stack

Step 2: Load context.md

The shared context is injected into every prompt for efficiency.

Step 3: Parse Task Files

For each tasks/task-NNN-*.md:

Extract YAML frontmatter:

yaml

id: task-001
component: users
wave: 1
deps: []
agent: python-experts:django-expert
contracts: [contracts/types.py, contracts/api-schema.yaml]

Extract Markdown sections:
- ## Scope -> CREATE, MODIFY, BOUNDARY
- ## Requirements -> Implementation requirements
- ## Checklist -> Acceptance criteria

Note: The Output Format section is not in task files. It's a static template that the prompt generator always includes in generated prompts.

Step 4: Generate Individual Prompts

Create prompts/task-NNN.txt using this template:

TASK-{id}: {title}
Agent: {agent}
Wave: {wave}
Dependencies: {deps or "None"}

=== CONTEXT ===
{contents of context.md}

=== OBJECTIVE ===
{First line of task description or component name}

=== CONTRACTS ===
Reference these contract files before implementing:
{list of contract files with full paths}

=== FILES TO CREATE ===
{CREATE section from Scope}

=== FILES TO MODIFY ===
{MODIFY section from Scope}

=== DO NOT MODIFY ===
{BOUNDARY section from Scope}

=== IMPLEMENTATION REQUIREMENTS ===
{Requirements section content}

=== ACCEPTANCE CRITERIA ===
{Checklist section content}

=== EXECUTION INSTRUCTIONS ===

You MUST write code, not just describe it. Follow these steps:

1. **Read contracts first**: Read all files in contracts/ to understand interfaces
2. **Read existing code**: If modifying files, read them first
3. **Implement**: Use Write/Edit tools to create/modify code
4. **Test**: Run tests to verify implementation
5. **Lint**: Run linters (ruff, mypy, eslint as appropriate)
6. **Commit**: Create atomic commit with conventional format

=== IMPORTANT RULES ===

- Do NOT ask for confirmation - proceed immediately with implementation
- Do NOT modify files listed in DO NOT MODIFY section
- Do NOT skip writing tests
- Do NOT deviate from contract interfaces
- STOP if you encounter blocking issues and report in output

=== OUTPUT FORMAT (REQUIRED) ===

You MUST end your response with this JSON summary block:

```json
{
  "task_completed": boolean,
  "validation_passed": boolean,
  "files_created": [string],
  "files_modified": [string],
  "tests_run": integer,
  "tests_passed": integer,
  "tests_failed": integer,
  "summary": string,
  "full_log": string,
  "error_message": string | null
}

Set validation_passed: true ONLY if ALL acceptance criteria are met.

=== COMPLETION SIGNAL ===

Upon successful completion, run: touch .claude-task-complete


## Step 5: Create agent-prompts.md

Summary file with launch commands:

```markdown
# Agent Prompts for {name}

Generated: {timestamp}
Tech Spec: {tech_spec_id}
Total Tasks: {count}

## Wave Execution Order

### Wave 1 (Parallel)
| Task | Agent | Component |
|------|-------|-----------|
| task-001 | python-experts:django-expert | users |
| task-002 | python-experts:django-expert | products |

### Wave 2 (Parallel, depends on Wave 1)
| Task | Agent | Component |
|------|-------|-----------|
| task-003 | python-experts:django-expert | orders |

## Launch Commands

### Using cpo (Recommended)
```bash
cpo run parallel/{slug}/

Manual Execution (Wave 1)

bash

# Run in parallel terminals or with &
claude --prompt-file prompts/task-001.txt --agent python-experts:django-expert &
claude --prompt-file prompts/task-002.txt --agent python-experts:django-expert &
wait

Manual Execution (Wave 2)

bash

# After Wave 1 completes
claude --prompt-file prompts/task-003.txt --agent python-experts:django-expert

Prompt Files

File	Task	Lines
prompts/task-001.txt	task-001-users	~150
prompts/task-002.txt	task-002-products	~145
prompts/task-003.txt	task-003-orders	~160


## Validation Before Generation

Check these conditions:

- [ ] `manifest.json` exists and is valid JSON
- [ ] `context.md` exists
- [ ] `contracts/` directory exists with at least one file
- [ ] `tasks/` directory has at least one task file
- [ ] All tasks referenced in manifest exist in `tasks/`

## Error Handling

### Task Not in Manifest

WARNING: task-005-api.md exists but not in manifest.json -> Skipping prompt generation (add to manifest first)


### Missing Contract Reference

WARNING: task-001 references contracts/types.py but file doesn't exist -> Generate prompt with warning comment


## Regeneration Mode

When prompts already exist:

1. **Backup existing**: Move to `prompts.backup-{timestamp}/`
2. **Generate fresh**: Create new prompts from current tasks
3. **Report diff**: Show what changed

```bash
# Command triggers regeneration
/parallel-generate-prompts parallel/TS-0042-inventory/ --force

Token Optimization

The generated prompts are optimized for token efficiency:

Context is included once (not repeated per section)
Contract paths reference files (agent reads them)
Scope uses compact CREATE/MODIFY/BOUNDARY notation
Checklist is actionable, not verbose

Integration with cpo

The cpo run command expects:

manifest.json with wave structure
prompts/task-NNN.txt for each task in manifest

This skill ensures prompts match what cpo expects.

Post-Generation Validation

After generating prompts, verify EACH prompt file contains:

bash

# Quick validation - each prompt should have these markers
for f in prompts/task-*.txt; do
  echo "=== $f ==="
  grep -c "=== OUTPUT FORMAT" "$f" || echo "MISSING: OUTPUT FORMAT"
  grep -c "=== EXECUTION INSTRUCTIONS" "$f" || echo "MISSING: EXECUTION INSTRUCTIONS"
  grep -c "=== COMPLETION SIGNAL" "$f" || echo "MISSING: COMPLETION SIGNAL"
  grep -c '"task_completed"' "$f" || echo "MISSING: JSON block"
done

If any prompt is missing these sections, regenerate it using the exact template from Step 4.

Related Skills

Skill	Relationship
`parallel-decompose`	Creates tasks/ that this skill reads
`parallel-task-format`	Defines the task YAML format parsed here
`parallel-execution`	Consumes the prompts/ this skill generates
`parallel-agents`	Overall workflow context

Search AI Tools

parallel-prompt-generator

Install this agent skill to your Project

SKILL.md

Prompt Generator

CRITICAL: Prompt Template Requirements

When to Use

Input Requirements

Output

Workflow

Step 1: Read manifest.json

Step 2: Load context.md

Step 3: Parse Task Files

Step 4: Generate Individual Prompts

Manual Execution (Wave 1)

Manual Execution (Wave 2)

Prompt Files

Token Optimization

Integration with cpo

Post-Generation Validation

Related Skills