Multi-step planning orchestration: research, stakeholder interviews, specification synthesis, implementation planning, and external LLM review.
Works with
Guides users through structured discovery: research topics, detailed interviews, and spec synthesis before writing implementation plans
Generates self-contained section files with dependencies, requirements, and acceptance criteria for autonomous or manual implementation
Integrates feedback from external LLM reviewers (Gemini, Codex) and supp
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiongepettoExecute the skills CLI command in your project's root directory to begin installation:
Fetches gepetto from softaworks/agent-toolkit and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate gepetto. Access via /gepetto in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Orchestrates a multi-step planning process: Research β Interview β Spec Synthesis β Plan β External Review β Sections
BEFORE anything else, do these in order:
Print intro banner immediately:
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GEPETTO: AI-Assisted Implementation Planning
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Research β Interview β Spec Synthesis β Plan β External Review β Sections
Note: GEPETTO will write many .md files to the planning directory you pass it
Check if user provided @file at invocation AND it's a spec file (ends with .md).
If NO @file was provided OR the path doesn't end with .md, output this and STOP:
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GEPETTO: Spec File Required
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This skill requires a markdown spec file path (must end with .md).
The planning directory is inferred from the spec file's parent directory.
To start a NEW plan:
1. Create a markdown spec file describing what you want to build
2. It can be as detailed or as vague as you like
3. Place it in a directory where gepetto can save planning files
4. Run: /gepetto @path/to/your-spec.md
To RESUME an existing plan:
1. Run: /gepetto @path/to/your-spec.md
Example: /gepetto @planning/my-feature-spec.md
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Do not continue. Wait for user to re-invoke with a .md file path.
Determine session state by checking existing files:
Set planning_dir = parent directory of the spec file
Set initial_file = the spec file path
Scan for existing planning files:
claude-research.mdclaude-interview.mdclaude-spec.mdclaude-plan.mdclaude-integration-notes.mdclaude-ralph-loop-prompt.mdclaude-ralphy-prd.mdreviews/ directorysections/ directoryDetermine mode and resume point:
| Files Found | Mode | Resume From |
|---|---|---|
| None | new | Step 4 |
| research only | resume | Step 6 (interview) |
| research + interview | resume | Step 8 (spec synthesis) |
| + spec | resume | Step 9 (plan) |
| + plan | resume | Step 10 (external review) |
| + reviews | resume | Step 11 (integrate) |
| + integration-notes | resume | Step 12 (user review) |
| + sections/index.md | resume | Step 14 (write sections) |
| all sections complete | resume | Step 15 (execution files) |
| + claude-ralph-loop-prompt.md + claude-ralphy-prd.md | complete | Done |
Print status:
Planning directory: {planning_dir}
Mode: {mode}
If resuming:
Resuming from step {N}
To start fresh, delete the planning directory files.
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STEP {N}/17: {STEP_NAME}
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{details}
Step {N} complete: {summary}
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See research-protocol.md.
See research-protocol.md.
Based on decisions from step 4, launch research subagents:
Task(subagent_type=Explore)Task(subagent_type=Explore) with WebSearchIf both are needed, launch both Task tools in parallel (single message with multiple tool calls).
Important: Subagents return their findings - they do NOT write files directly. After collecting results from all subagents, combine them and write to <planning_dir>/claude-research.md.
Skip this step entirely if user chose no research in step 4.
Run in main context (AskUserQuestion requires it). The interview should be informed by:
Write Q&A to <planning_dir>/claude-interview.md
Combine into <planning_dir>/claude-spec.md:
This synthesizes the user's raw requirements into a complete specification.
Create detailed plan β <planning_dir>/claude-plan.md
IMPORTANT: Write for an unfamiliar reader. The plan must be fully self-contained - an engineer or LLM with no prior context should understand what we're building, why, and how just from reading this document.
Launch TWO subagents in parallel to review the plan:
Both receive the plan content and return their analysis. Write results to <planning_dir>/reviews/.
Analyze the suggestions in <planning_dir>/reviews/.
You are the authority on what to integrate or not. It's OK if you decide to not integrate anything.
Step 1: Write <planning_dir>/claude-integration-notes.md documenting:
Step 2: Update <planning_dir>/claude-plan.md with the integrated changes.
Use AskUserQuestion:
The plan has been updated with external feedback. You can now review and edit claude-plan.md.
If you want Claude's help editing the plan, open a separate Claude session - this session
is mid-workflow and can't assist with edits until the workflow completes.
When you're done reviewing, select "Done" to continue.
Options: "Done reviewing"
Wait for user confirmation before proceeding.
See section-index.md
Read claude-plan.md. Identify natural section boundaries and create <planning_dir>/sections/index.md.
CRITICAL: index.md MUST start with a SECTION_MANIFEST block. See the reference for format requirements.
Write index.md before proceeding to section file creation.
Launch parallel subagents - one Task per section for maximum efficiency:
sections/index.md to get the SECTION_MANIFEST list# Launch all in ONE message for parallel execution:
Task(
subagent_type="general-purpose",
prompt="""
Write section file: section-01-{name}
Inputs:
- <planning_dir>/claude-plan.md
- <planning_dir>/sections/index.md
Output: <planning_dir>/sections/section-01-{name}.md
The section file must be COMPLETELY SELF-CONTAINED. Include:
- Background (why this section exists)
- Requirements (what must be true when complete)
- Dependencies (requires/blocks)
- Implementation details (from the plan)
- Acceptance criteria (checkboxes)
- Files to create/modify
The implementer should NOT need to reference any other document.
"""
)
Task(
subagent_type="general-purpose",
prompt="Write section file: section-02-{name} ..."
)
Task(
subagent_type="general-purpose",
prompt="Write section file: section-03-{name} ..."
)
# ... one Task per section in the manifest
Wait for ALL subagents to complete before proceeding.
Delegate to subagent to reduce main context token usage:
Task(
subagent_type="general-purpose",
prompt="""
Generate two execution files for autonomous implementation.
Input files:
- <planning_dir>/sections/index.md (has SECTION_MANIFEST)
- <planning_dir>/sections/section-*.md (all section files)
OUTPUT 1: <planning_dir>/claude-ralph-loop-prompt.md
For ralph-loop plugin. EMBED all section content inline.
Structure:
- Mission statement
- Full content of sections/index.md
- Full content of EACH section file (embedded, not referenced)
- Execution rules (dependency order, verify acceptance criteria)
- Completion signal: <promise>ALL-SECTIONS-COMPLETE</promise>
OUTPUT 2: <planning_dir>/claude-ralphy-prd.md
For Ralphy CLI. REFERENCE section files (don't embed).
Structure:
- PRD header
- How to use (ralphy --prd command)
- Context explanation
- Checkbox task list: one "- [ ] Section NN: {name}" per section
Write both files.
"""
)
Wait for subagent completion before proceeding.
Verify all files were created successfully:
claude-ralph-loop-prompt.mdclaude-ralphy-prd.mdPrint generated files and next steps:
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GEPETTO: Planning Complete
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Generated files:
- claude-research.md (research findings)
- claude-interview.md (Q&A transcript)
- claude-spec.md (synthesized specification)
- claude-plan.md (implementation plan)
- claude-integration-notes.md (feedback decisions)
- reviews/ (external LLM feedback)
- sections/ (implementation units)
- claude-ralph-loop-prompt.md (for ralph-loop plugin)
- claude-ralphy-prd.md (for Ralphy CLI)
How to implement:
Option A - Manual (recommended for learning/control):
1. Read sections/index.md to understand dependencies
2. Implement each section file in order
3. Each section is self-contained with acceptance criteria
Option B - Autonomous with ralph-loop (Claude Code plugin):
/ralph-loop @<planning_dir>/claude-ralph-loop-prompt.md --completion-promise "COMPLETE" --max-iterations 100
Option C - Autonomous with Ralphy (external CLI):
ralphy --prd <planning_dir>/claude-ralphy-prd.md
# Or: cp <planning_dir>/claude-ralphy-prd.md ./PRD.md && ralphy
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Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
β Do
β Don't
π‘ Pro Tips
β Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
β Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
pproenca/dot-skills
ailabs-393/ai-labs-claude-skills
mattpocock/skills
We added gepetto from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
gepetto fits our agent workflows well β practical, well scoped, and easy to wire into existing repos.
gepetto reduced setup friction for our internal harness; good balance of opinion and flexibility.
We added gepetto from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Useful defaults in gepetto β fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
gepetto is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Registry listing for gepetto matched our evaluation β installs cleanly and behaves as described in the markdown.
Useful defaults in gepetto β fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
We added gepetto from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Useful defaults in gepetto β fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
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