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mhyllemhylle/claude-skills-collection/skills/prompt-generator/SKILL.md

prompt-generator

Skill20 starsChanged 37 days agoMITView on GitHub

Generate implementation prompts for phase-based project execution using an orchestration pattern. Use when users request prompts for implementing project phases, need orchestration prompts for multi-step implementations, ask for "/prompt", "generate prompt", "create implementation prompt", or want to create structured implementation instructions for subagent delegation. Outputs the prompt to chat and saves to docs/prompts folder.

8 other projects use a version of this.

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The file

We split this skill into the rules it gives an agent

8 rules. 0 are common, 6 are distinctive, and 2 are very specific to this project.

  • 0

    Common

    Most of the 6 edited versions we read keep these.

  • 6

    Distinctive

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    When triggered, gather these inputs from the user:

    line 38
  2. Distinctive:

    Read any ADRs referenced in the plan before implementation

    line 50
  3. Distinctive:

    Create new ADRs when architectural decisions arise during implementation

    line 51
  4. Distinctive:

    Update the plan with ADR references when deviating from the original design

    line 52
  5. Distinctive:

    Ask the user for required variables.

    line 58
  6. Very specific:

    Read the template from references/implementation-prompt-template.md and substitute all {PLACEHOLDER} values with user-provided inputs.

    line 71
  7. Very specific:

    Save: Use scripts/save_prompt.py to save to <PROJECT_ROOT>/docs/prompts/

    line 76
  8. Distinctive:

    Plan updates: Update implementation plan with actual outcomes upon completion

    line 94

“Common” is measured: kept by at least 6 in 10 of the 6 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Prompt Generator

<!-- contents: generated by tests/skill_structure.py --write; edit headings, not this block -->

Contents

  • Quick Start
  • Workflow
    • 1. Gather User Input
    • 2. Generate the Prompt
    • 3. Output and Save
  • Template Features
    • Subagent Patterns Reference
  • Output Format
  • Integration with implement-plan/implement-phase
    • Workflow
    • Naming Convention
    • Directory Structure
    • Benefits
  • Resources
    • references/
    • scripts/

Reference files (open one when a step points to it):

  • references/implementation-prompt-template.md: Implementation Prompt Template: Phase {PHASE_NUMBER} - {PHASE_NAME}
<!-- /contents -->

Generate structured implementation prompts for phase-based project execution using an orchestrator/subagent pattern.

Quick Start

When triggered, gather these inputs from the user:

VariableDescriptionExample
PHASE_NUMBERPhase identifier"1", "2", "3"
PHASE_NAMEDescriptive phase name"Foundation", "Data Pipeline"
PHASE_DOC_PATHPath to phase plan document/project/docs/plans/01-foundation.md
PROJECT_ROOTProject root directory/home/user/myproject
GENERAL_PLAN_PATHPath to general plan (optional)/project/docs/plans/00-general-plan.md
ADR_PATHPath to ADR directory (optional)/project/docs/decisions/

ADR Integration: The generated prompt will instruct the orchestrator to:

  • Read any ADRs referenced in the plan before implementation
  • Create new ADRs when architectural decisions arise during implementation
  • Update the plan with ADR references when deviating from the original design

Workflow

1. Gather User Input

Ask the user for required variables. If context provides these values, confirm them:

To generate the implementation prompt, I need:
1. Phase number (e.g., 1, 2, 3)
2. Phase name (e.g., "Foundation", "Data Pipeline")
3. Path to the phase document
4. Project root directory
5. Path to general plan (optional)

2. Generate the Prompt

Read the template from references/implementation-prompt-template.md and substitute all {PLACEHOLDER} values with user-provided inputs.

3. Output and Save

  1. Display: Output the complete generated prompt in the chat
  2. Save: Use scripts/save_prompt.py to save to <PROJECT_ROOT>/docs/prompts/
echo "<generated_prompt>" | python scripts/save_prompt.py <project_root> <phase_number> <phase_name>

The file is saved as: docs/prompts/phase-<N>-<name>.md

Template Features

The generated prompt includes:

  • Orchestration requirements: Main session coordinates, subagents implement
  • Delegation patterns: File creation, testing, infrastructure, integration
  • Progress tracking: TodoWrite integration for task management
  • Validation workflow: Group validation and final success criteria checks
  • Error handling: Failure analysis, rollback procedures, escalation guidance
  • Handoff preparation: Documentation for next phase transition
  • Plan updates: Update implementation plan with actual outcomes upon completion

Subagent Patterns Reference

Task TypePatternConcurrency
File creation (independent)ParallelHigh (5-7)
File creation (dependent)SequentialLow (1-2)
Testing/ValidationPer test suiteMedium (3-5)
Docker/InfrastructurePer serviceMedium (3-4)
IntegrationPer integration pointLow (2-3)

Output Format

The generated prompt follows this structure:

Implement Phase {N}: {Name} of the trading platform...

IMPORTANT ORCHESTRATION REQUIREMENTS:
1. This is an ORCHESTRATION SESSION...
2. Use the implement-plan skill...
3. Spawn SUBAGENTS for all implementation...
4. Track progress using TodoWrite...
5. Coordinate subagents and validate...

## Implementation Strategy
[Phase overview, orchestration workflow, delegation patterns]

## Error Handling
[Failure analysis, rollback, escalation]

## Success Criteria Validation
[Automated and manual checks]

## Handoff to Next Phase
[Update implementation plan, completion documentation, context prep, clean state]

Integration with implement-plan/implement-phase

Generated prompts are automatically discovered and used by the implementation skills:

Workflow

1. prompt-generator creates: docs/prompts/phase-2-data-pipeline.md
                                    ↓
2. implement-plan discovers prompt via Glob("docs/prompts/phase-*.md")
                                    ↓
3. implement-plan passes prompt path to implement-phase
                                    ↓
4. implement-phase uses prompt for detailed orchestration instructions
                                    ↓
5. On completion, implement-phase archives to: docs/prompts/completed/

Naming Convention

Prompts must follow this naming pattern for auto-discovery:

docs/prompts/phase-<N>-<name>.md

Examples:
  docs/prompts/phase-1-foundation.md      → Phase 1
  docs/prompts/phase-2-data-pipeline.md   → Phase 2
  docs/prompts/phase-3-agent-system.md    → Phase 3

Directory Structure

docs/prompts/
├── phase-1-foundation.md        # Pending - ready for implementation
├── phase-2-data-pipeline.md     # Pending - ready for implementation
├── phase-3-agent-system.md      # Pending - ready for implementation
└── completed/                   # Archived after successful completion
    ├── phase-1-foundation.md    # Completed
    └── phase-2-data-pipeline.md # Completed

Benefits

  • Pre-planning: Generate all prompts upfront before implementation
  • Consistency: Same orchestration patterns across all phases
  • Tracking: Completed folder shows implementation progress
  • Review: Archived prompts document what instructions were used

Resources

references/

  • implementation-prompt-template.md: Full prompt template with all placeholders and patterns

scripts/

  • save_prompt.py: Saves generated prompts to docs/prompts/ with metadata header

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