NIC Task Planning
nginx/kubernetes-ingress
Plans a change to the NGINX Ingress Controller before any code: acceptance criteria, security impact, affected layers, invariants, test surface and an ordered file list.
Creates detailed, sectionized implementation plans through research, stakeholder interviews, and multi-LLM review.
Install Gepetto
$ npx skills add meshery/meshery-operator --skill gepetto -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install meshery/meshery-operator gepetto --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/meshery/meshery-operator.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/gepetto .claude/skills/gepetto && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "gepetto" agent skill from https://github.com/meshery/meshery-operator/tree/master/.claude/skills/gepetto into .claude/skills/gepetto/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gepetto", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/meshery/meshery-operator/tree/master/.claude/skills/gepettoType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add meshery/meshery-operator --skill gepetto -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install meshery/meshery-operator gepetto --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/meshery/meshery-operator.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/gepetto .agents/skills/gepetto && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "gepetto" agent skill from https://github.com/meshery/meshery-operator/tree/master/.claude/skills/gepetto into .agents/skills/gepetto/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gepetto", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add meshery/meshery-operator --skill gepetto -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install meshery/meshery-operator gepetto --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/meshery/meshery-operator.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/gepetto .cursor/skills/gepetto && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "gepetto" agent skill from https://github.com/meshery/meshery-operator/tree/master/.claude/skills/gepetto into .cursor/skills/gepetto/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gepetto", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/meshery/meshery-operator.git --path .claude/skills/gepetto--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add meshery/meshery-operator --skill gepetto -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install meshery/meshery-operator gepetto --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/meshery/meshery-operator.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/gepetto .gemini/skills/gepetto && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "gepetto" agent skill from https://github.com/meshery/meshery-operator/tree/master/.claude/skills/gepetto into .gemini/skills/gepetto/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gepetto", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install meshery/meshery-operator gepettoInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add meshery/meshery-operator --skill gepetto -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/meshery/meshery-operator.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/gepetto .github/skills/gepetto && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "gepetto" agent skill from https://github.com/meshery/meshery-operator/tree/master/.claude/skills/gepetto into .github/skills/gepetto/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gepetto", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add meshery/meshery-operator --skill gepetto -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install meshery/meshery-operator gepetto --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/meshery/meshery-operator.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/gepetto .opencode/skills/gepetto && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "gepetto" agent skill from https://github.com/meshery/meshery-operator/tree/master/.claude/skills/gepetto into .opencode/skills/gepetto/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gepetto", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
gepetto- GitHub stars
- 151
- Used in
- 3 other repos
- Token cost
- ~2.7k tokens
- SKILL.md length
- 674 words
- Files
- 7 (incl. references)
- Skills in repo
- 8
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Creates detailed, sectionized implementation plans through research, stakeholder interviews, and multi-LLM review.
- Works in 12 steps: Print Intro → Validate Spec File Input → Setup Planning Session → …
- Planning features that need thorough pre-implementation analysis
- SKILL.md covers CRITICAL: First Actions, Logging Format and Workflow
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Gepetto is an agent skill from meshery/meshery-operator. Creates detailed, sectionized implementation plans through research, stakeholder interviews, and multi-LLM review. Use when planning features that need thorough pre-implementation analysis.
Its SKILL.md is about 2.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including reference files (for example `README.md`, `references/external-review.md` and `references/interview-protocol.md`).
It sits in Agent Workflows, covering Planning. It works with Kubernetes. The repository describes itself as: Meshery Operator is a Kubernetes Operator that deploys and manages the lifecycle of two Meshery components critical to Meshery's operations of Kubernetes clusters. The licence is Apache-2.0.
When your agent uses it
- Planning features that need thorough pre-implementation analysis
- Tasks that involve Planning
Example prompts
- “Use the gepetto skill to create detailed, sectionized implementation plans through research, stakeholder interviews, and multi-LLM review”
- “/gepetto”
Workflow steps
12 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 632cd41. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Gepetto loads about 2.7k tokens when it runs, and up to ~7.5k if it reads all its reference files. Until then it costs about 49 tokens; SKILL.md has 674 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from meshery/meshery-operator at commit 632cd41, republished under its Apache-2.0 licence (© meshery). 674 words, ~2,684 tokens.
Download SKILL.mdSave it as
.claude/skills/gepetto/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.- name
- gepetto
- description
- Creates detailed, sectionized implementation plans through research, stakeholder interviews, and multi-LLM review. Use when planning features that need thorough pre-implementation analysis.
Gepetto
Orchestrates a multi-step planning process: Research → Interview → Spec Synthesis → Plan → External Review → Sections
CRITICAL: First Actions
BEFORE anything else, do these in order:
1. Print Intro
Print intro banner immediately:
═══════════════════════════════════════════════════════════════
GEPETTO: AI-Assisted Implementation Planning
═══════════════════════════════════════════════════════════════
Research → Interview → Spec Synthesis → Plan → External Review → Sections
Note: GEPETTO will write many .md files to the planning directory you pass it2. Validate Spec File Input
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:
═══════════════════════════════════════════════════════════════
GEPETTO: Spec File Required
═══════════════════════════════════════════════════════════════
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
═══════════════════════════════════════════════════════════════Do not continue. Wait for user to re-invoke with a .md file path.
3. Setup Planning Session
Determine session state by checking existing files:
Set
planning_dir= parent directory of the spec fileSet
initial_file= the spec file pathScan for existing planning files:
claude-research.mdclaude-interview.mdclaude-spec.mdclaude-plan.mdclaude-integration-notes.mdclaude-ralph-loop-prompt.mdclaude-ralphy-prd.mdreviews/directorysections/directory
Determine 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 |
- Create TODO list with TodoWrite based on current state
Print status:
Planning directory: {planning_dir}
Mode: {mode}If resuming:
Resuming from step {N}
To start fresh, delete the planning directory files.Logging Format
═══════════════════════════════════════════════════════════════
STEP {N}/17: {STEP_NAME}
═══════════════════════════════════════════════════════════════
{details}
Step {N} complete: {summary}
───────────────────────────────────────────────────────────────Workflow
4. Research Decision
See research-protocol.md.
- Read the spec file
- Extract potential research topics (technologies, patterns, integrations)
- Ask user about codebase research needs
- Ask user about web research needs (present derived topics as multi-select)
- Record which research types to perform in step 5
5. Execute Research
See research-protocol.md.
Based on decisions from step 4, launch research subagents:
- Codebase research:
Task(subagent_type=Explore) - Web research:
Task(subagent_type=Explore)with WebSearch
If 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.
6. Detailed Interview
Run in main context (AskUserQuestion requires it). The interview should be informed by:
- The initial spec
- Research findings (if any)
7. Save Interview Transcript
Write Q&A to <planning_dir>/claude-interview.md
8. Write Initial Spec (Spec Synthesis)
Combine into <planning_dir>/claude-spec.md:
- Initial input (the spec file)
- Research findings (if step 5 was done)
- Interview answers (from step 6)
This synthesizes the user's raw requirements into a complete specification.
Show full SKILL.md (276 more words)Show less
9. Generate Implementation Plan
Create detailed plan → <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.
10. External Review
Launch TWO subagents in parallel to review the plan:
- Gemini via Bash
- Codex via Bash
Both receive the plan content and return their analysis. Write results to <planning_dir>/reviews/.
11. Integrate External Feedback
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:
- What suggestions you're integrating and why
- What suggestions you're NOT integrating and why
Step 2: Update <planning_dir>/claude-plan.md with the integrated changes.
12. User Review of Integrated Plan
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.
13. Create Section Index
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.
14. Write Section Files — Parallel Subagents
Launch parallel subagents - one Task per section for maximum efficiency:
- First, parse
sections/index.mdto get the SECTION_MANIFEST list - Then launch ALL section Tasks in a single message (parallel execution):
# 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 manifestWait for ALL subagents to complete before proceeding.
15. Generate Execution Files — Subagent
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.
16. Final Status
Verify all files were created successfully:
- All section files from SECTION_MANIFEST
claude-ralph-loop-prompt.mdclaude-ralphy-prd.md
17. Output Summary
Print generated files and next steps:
═══════════════════════════════════════════════════════════════
GEPETTO: Planning Complete
═══════════════════════════════════════════════════════════════
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
═══════════════════════════════════════════════════════════════© meshery, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 6 other files (references) in .claude/skills/gepetto of meshery/meshery-operator.
- SKILL.md
- README.md
- references/external-review.md
- references/interview-protocol.md
- references/research-protocol.md
- references/section-index.md
- references/section-splitting.md
Open the folder on GitHubat commit 632cd41
Used in 3 other repositories
We found 3 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 3 other GitHub owners. This page covers the copy in meshery/meshery-operator, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Gepetto next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Gepetto this skillmeshery/meshery-operator | 151 | 3 repos | ~2.7k | Automated safety check: Pass | Apache-2.0 | |
| NIC Task Planningnginx/kubernetes-ingress | 5.1k | — | ~1.7k | Automated safety check: Pass | Apache-2.0 | |
| Executing Plans Inlineobra/superpowers | 297k | 2 repos | ~5.1k | Automated safety check: Pass | MIT | |
| Interview Meaddyosmani/agent-skills | 104k | 6 repos | ~3.8k | Automated safety check: Pass | MIT | |
| OpenSpec Guided OnboardingFission-AI/OpenSpec | 72k | 1 repos | ~4.5k | Automated safety check: Pass | MIT | |
| Writing Plansgeeksblabla/stateofdev.ma | 163 | 57 repos | ~661 | Automated safety check: Pass | None |
Similar skills
Executing Plans Inline
obra/superpowers
Has the agent carry out an implementation plan itself, task by task in the current session, keeping a ledger, proving each step with a test and ending with one whole-branch review.
Interview Me
addyosmani/agent-skills
Asks one question at a time, each with a best guess attached, until the agent is about 95 percent sure what you really want, before any plan, spec or code.
OpenSpec Guided Onboarding
Fission-AI/OpenSpec
Walks you through a complete OpenSpec workflow cycle with narration while doing real work in your codebase.
Writing Plans
geeksblabla/stateofdev.ma
A skill your agent uses when design is complete and you need detailed implementation tasks for engineers with zero codebase context - creates comprehensive implementation plans with exact file…
Subagent Driven Development
Asvarox/allkaraoke
A skill your agent uses when executing implementation plans with independent tasks in the current session
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Related
Works with
Categories
Questions about Gepetto
What does Gepetto do?
Creates detailed, sectionized implementation plans through research, stakeholder interviews, and multi-LLM review. Gepetto is an agent skill from meshery/meshery-operator. Creates detailed, sectionized implementation plans through research, stakeholder interviews, and multi-LLM review.
When should I use Gepetto?
Gepetto fits situations like: planning features that need thorough pre-implementation analysis; tasks that involve Planning.
How do I install Gepetto in Claude Code?
Run `npx skills add meshery/meshery-operator --skill gepetto -a claude-code`. Or copy the skill folder (.claude/skills/gepetto in meshery/meshery-operator) into .claude/skills/gepetto in your project. Claude Code loads it when a task matches its description.
How do I install Gepetto in Codex?
Run `npx skills add meshery/meshery-operator --skill gepetto -a codex`. Or copy the skill folder (.claude/skills/gepetto in meshery/meshery-operator) into .agents/skills/gepetto in your project. Codex loads it when a task matches its description.
Can I use Gepetto in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add meshery/meshery-operator --skill gepetto -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/gepetto, .gemini/skills/gepetto, .github/skills/gepetto and .opencode/skills/gepetto in your project.
What does Gepetto need to run?
SKILL.md names no scripts, command-line tools or credentials: Gepetto is instructions for the agent only.
Does Gepetto access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Gepetto safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Gepetto use?
Gepetto is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Gepetto use?
About 2.7k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 4.8k tokens, read only when the agent opens those files.
What are the alternatives to Gepetto?
Skills that share tags, products or a category with Gepetto: NIC Task Planning (nginx/kubernetes-ingress, 5.1k stars), Executing Plans Inline (obra/superpowers, 297k stars), Interview Me (addyosmani/agent-skills, 104k stars) and OpenSpec Guided Onboarding (Fission-AI/OpenSpec, 72k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Gepetto?
meshery (a GitHub organization) maintains it in meshery/meshery-operator, which has 151 GitHub stars. The repository holds 8 skills in this directory. The repository was last updated on September 21, 2026.
Source: meshery/meshery-operator on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.