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.
Adopted by
Most recently taken up by
- iuliandita/skillstheir own version, first seen Oct 14, 2026
- alonbaron/claude-skillstheir own version, first seen Oct 12, 2026
- genfeedai/genfeed.aitheir own version, first seen Sep 12, 2026
- Anmoll-W/thepmcode-skillstheir own version, first seen Aug 31, 2026
- sid-git-repo/claude-skillstheir own version, first seen Aug 31, 2026
- zhao-wuyan/ccw-command-explorertheir own version, first seen May 8, 2026
Other versions8 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 8
- huangserva/skill-prompt-generator★ 1.5ksame name
- zhao-wuyan/ccw-command-explorer★ 45same name
- ttmouse/skills★ 34same name
- alonbaron/claude-skills★ 14same name
- iuliandita/skills★ 11same name
- Anmoll-W/thepmcode-skills★ 8same name
- genfeedai/genfeed.ai★ 4same name
- sid-git-repo/claude-skills★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository34 other files it gives its agents.
- adrSkill
- adversarial-reviewerSkill
- agent-creatorSkill
- brainstormSkill
- codebase-auditSkill
- codebase-researchSkill
- code-quality-auditSkill
- code-reviewSkill
- context-saverSkill
- continuous-learningSkill
- create-planSkill
- design-languageSkill
- e2e-testingSkill
- eval-harnessSkill
- grumpy-reviewerSkill
- implement-phaseSkill
- implement-planSkill
- iterate-planSkill
- security-reviewSkill
- ship-issueSkill
- skill-visualizerSkill
- strategic-compactSkill
- tt-create-build-loopSkill
- tt-create-planSkill
- tt-implement-phaseSkill
- tt-implement-planSkill
- tt-workflow-auditSkill
- tt-workflow-buildSkill
- tt-workflow-runSkill
- user-storySkill
- verification-loopSkill
- video-explainerSkill
- visual-explainerSkill
- workflow-guideSkill
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
- Distinctive: line 38
When triggered, gather these inputs from the user:
- Distinctive: line 50
Read any ADRs referenced in the plan before implementation
- Distinctive: line 51
Create new ADRs when architectural decisions arise during implementation
- Distinctive: line 52
Update the plan with ADR references when deviating from the original design
- Distinctive: line 58
Ask the user for required variables.
- Very specific: line 71
Read the template from references/implementation-prompt-template.md and substitute all {PLACEHOLDER} values with user-provided inputs.
- Very specific: line 76
Save: Use scripts/save_prompt.py to save to <PROJECT_ROOT>/docs/prompts/
- Distinctive: line 94
Plan updates: Update implementation plan with actual outcomes upon completion
“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.
Files
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:
| Variable | Description | Example |
PHASE_NUMBER | Phase identifier | "1", "2", "3" |
PHASE_NAME | Descriptive phase name | "Foundation", "Data Pipeline" |
PHASE_DOC_PATH | Path to phase plan document | /project/docs/plans/01-foundation.md |
PROJECT_ROOT | Project root directory | /home/user/myproject |
GENERAL_PLAN_PATH | Path to general plan (optional) | /project/docs/plans/00-general-plan.md |
ADR_PATH | Path 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
- Display: Output the complete generated prompt in the chat
- Save: Use
scripts/save_prompt.pyto 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 Type | Pattern | Concurrency |
| File creation (independent) | Parallel | High (5-7) |
| File creation (dependent) | Sequential | Low (1-2) |
| Testing/Validation | Per test suite | Medium (3-5) |
| Docker/Infrastructure | Per service | Medium (3-4) |
| Integration | Per integration point | Low (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 3Directory 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 # CompletedBenefits
- 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 todocs/prompts/with metadata header
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