Best for
- Use when the user asks to "onboard me", "onboard to this project", "generate onboarding guide", "new developer guide", "how do I get started", or "help me ramp up".
tobihagemann/turbo/claude/skills/onboard/SKILL.md
Developer onboarding guide that composes architecture mapping, tooling review, and agentic setup review with setup, troubleshooting, and next-steps agents to produce a comprehensive guide at .turbo/onboarding.md and .turbo/onboarding.html. Use when the user asks to "onboard me", "onboard to this project", "generate onboarding guide", "new developer guide", "how do I get started", or "help me ramp up".
Decision brief
Developer onboarding pipeline. Composes /map-codebase, /review-tooling, and /review-agentic-setup with inline agents, then synthesizes everything into .turbo/onboarding.md and .turbo/onboarding.html. Analysis-only.
Compatibility matrix
| Platform | Status | Evidence | What to check |
|---|---|---|---|
| Codex | Not declared | No explicit evidence | Portability before use |
| Claude Code | Not declared | No explicit evidence | Portability before use |
| Cursor | Not declared | No explicit evidence | Portability before use |
| Gemini CLI | Not declared | No explicit evidence | Portability before use |
Installation
The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.
npx skills add https://github.com/tobihagemann/turbo --skill "claude/skills/onboard"Inspect the Agent Skill "onboard" from https://github.com/tobihagemann/turbo/blob/1c4cc7c9f13514d968e65783f921b82251d3fc0d/claude/skills/onboard/SKILL.md at commit 1c4cc7c9f13514d968e65783f921b82251d3fc0d. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.
Workflow
Use the Agent tool to launch all 6 agents below in a single assistant message so they run concurrently. Run them in the foreground so all their results return in this turn. Each Agent call uses model: "opus" and no name. Each Composed Skills agent invokes its assigned skill via…
After all agents complete:
Review the “Prerequisites and Setup” section in the pinned source before continuing.
Review the “Development Workflow” section in the pinned source before continuing.
Convert the markdown report into a styled, interactive HTML page.
Permission review
No configured static risk pattern was detected
This is not proof of safety. Runtime behavior, indirect dependencies, and hidden external systems are outside the static scan.
Evidence record
| Signal | Value | Evidence type | Meaning |
|---|---|---|---|
| Quality score | 86/100 | Computed | Documentation, specificity, maintenance, and trust rules |
| Repository stars | 398 | Source | Repository attention, not individual Skill quality |
| Compatibility | 0 platforms | Source | Declared in the catalog source record |
| Usage guide | automated source guide | Editorial | Generated or reviewed according to the visible evidence level |
Pinned source
Developer onboarding pipeline. Composes /map-codebase, /review-tooling, and /review-agentic-setup with inline agents, then synthesizes everything into .turbo/onboarding.md and .turbo/onboarding.html. Analysis-only.
At the start, use TaskCreate to create a task for each phase:
Use the Agent tool to launch all 6 agents below in a single assistant message so they run concurrently. Run them in the foreground so all their results return in this turn. Each Agent call uses model: "opus" and no name. Each Composed Skills agent invokes its assigned skill via the Skill tool; each Inline Agent follows its exploration brief directly. Every agent's prompt must direct it to treat the shared working tree and its git index as read-only and to explore by reading and reasoning, except that each Composed Skills agent writes the report files its own skill defines.
Launch one Agent tool call per row. Each agent's prompt instructs it to invoke its assigned skill via the Skill tool.
| Skill | Onboarding role |
|---|---|
/map-codebase | Architecture understanding: structure, tech stack, entry points, patterns, data flow, dependencies, testing |
/review-tooling | Development workflow: linters, formatters, pre-commit hooks, test runners, CI/CD |
/review-agentic-setup | Agentic coding: CLAUDE.md, AGENTS.md, skills, MCP servers, hooks, cross-tool compatibility |
Launch one Agent tool call each with the exploration brief below.
| Agent | Exploration Brief |
|---|---|
| Prerequisites and Setup | Read README.md, CONTRIBUTING.md, and package manager configs (package.json, Gemfile, Cargo.toml, go.mod, pyproject.toml, Package.swift, etc.). Extract: required language runtimes and versions, system dependencies, environment variables, database or service requirements, first-time setup steps (install, build, run, seed), and any bootstrap or setup scripts. |
| Troubleshooting | Search for troubleshooting content in README.md, TROUBLESHOOTING.md, docs/ directory, FAQ files, and GitHub Discussions/Wiki if accessible. Extract common errors, known quirks, platform-specific gotchas, and debugging tips. If no troubleshooting docs exist, report that. |
| Next Steps | Run gh issue list --state open --json number,title,url,reactionGroups,comments,labels --limit 50. Identify: (1) issues labeled good-first-issue or good first issue, (2) top 5 issues by engagement score (sum of reactions weighted 2x for thumbs-up, plus comment count). If gh is not available or not in a GitHub repo, skip and note that. |
Each agent writes its findings as structured markdown.
After all agents complete:
.turbo/threat-model.md exists; if so, read it for the Security Considerations section./review-tooling findings become "Development Workflow" (what tools are used and how to run them). /review-agentic-setup findings become "AI-Assisted Development" (what's set up and how to use it). Focus on what exists, not what's missing. Strip severity labels, findings numbering, and gap framing from review skill outputs. Present detected tools and configurations as project conventions the new developer should know..turbo/onboarding.md using the report template. Output the welcome summary as text before writing the file.# Onboarding Guide
**Date:** <date>
**Project:** <project name>
## Welcome
<3-5 sentences: what this project is, who it's for, fastest path to a first contribution>
## Prerequisites and Setup
<from Prerequisites and Setup agent: language runtimes, dependencies, first-time setup steps, build/run commands>
## Architecture Overview
<from /map-codebase: condensed executive summary and key structural insights — not the full report, which lives at .turbo/codebase-map.md>
## Development Workflow
<from /review-tooling: reframed as "how to develop" — what linters/formatters to run, how to test, pre-commit hooks, CI/CD pipeline>
## AI-Assisted Development
<from /review-agentic-setup: reframed as "how to use AI coding tools" — what CLAUDE.md/AGENTS.md cover, installed skills, MCP servers, cross-tool compatibility>
## Security Considerations
<from .turbo/threat-model.md if present: key trust boundaries, security-sensitive areas, and what to be careful with — or omit this section if no threat model exists>
## Troubleshooting
<from Troubleshooting agent: common errors, known quirks, debugging tips, or "no troubleshooting docs found">
## Next Steps
<from Next Steps agent: good-first-issue issues, top-engaged issues, or "no GitHub issues found">
Convert the markdown report into a styled, interactive HTML page.
/frontend-design skill to load design principles..turbo/onboarding.md for the full report content..turbo/onboarding.html (single file, no external dependencies beyond Google Fonts) that presents the onboarding guide with:
@media print/map-codebase skill produces its own full report at .turbo/codebase-map.md. The onboarding guide includes a condensed summary and links to the full report.Alternatives
alirezarezvani/claude-skills
App Store Optimization (ASO) toolkit for researching keywords, analyzing competitor rankings, generating metadata suggestions, and improving app visibility on Apple App Store and Google Play Store. Use when the user asks about ASO, app store rankings, app metadata, app titles and descriptions, app store listings, app visibility, or mobile app marketing on iOS or Android. Supports keyword research and scoring, competitor keyword analysis, metadata optimization, A/B test planning, launch checklist
K-Dense-AI/scientific-agent-skills
Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing, distributed ML, integration with existing pandas code. For out-of-core analytics on single machine use vaex; for in-memory speed use polars.
K-Dense-AI/scientific-agent-skills
Use NeuroKit2 to build or audit reproducible research workflows for physiological time-series preprocessing, event/interval analysis, multimodal alignment, variability, and complexity. Trigger when code imports neurokit2 or needs its current APIs, schemas, and method-aware validation—not for diagnosis or device validation.
wanshuiyin/Auto-claude-code-research-in-sleep
Use it for engineering and operations tasks; the detail page covers purpose, installation, and practical steps.