本文へ移動
cccskills
無料GitHub で公開

wiki-onboarding

Generate two complementary onboarding documents that together give any engineer — from newcomer to principal — a complete understanding of a codebase. Use when user asks for onboarding docs or getting-started guides, user runs /deep-wiki, or user wants to help new team members understand a codebase.

インストール方法を見る

含まれるファイル(1)

  • SKILL.md4.5 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Wiki Onboarding Guide Generator

Generate two complementary onboarding documents that together give any engineer — from newcomer to principal — a complete understanding of a codebase.

When to Use

  • User asks for onboarding docs or getting-started guides
  • User runs /deep-wiki:onboard command
  • User wants to help new team members understand a codebase

Language Detection

Scan the repository for build files to determine the primary language for code examples:

  • package.json / tsconfig.json → TypeScript/JavaScript
  • *.csproj / *.sln → C# / .NET
  • Cargo.toml → Rust
  • pyproject.toml / setup.py / requirements.txt → Python
  • go.mod → Go
  • pom.xml / build.gradle → Java

Guide 1: Principal-Level Onboarding

Audience: Senior/staff+ engineers who need the "why" behind decisions.

Required Sections

  1. System Philosophy & Design Principles — What invariants does the system maintain? What were the key design choices and why?
  2. Architecture Overview — Component map with Mermaid diagram. What owns what, communication patterns.
  3. Key Abstractions & Interfaces — The load-bearing abstractions everything depends on
  4. Decision Log — Major architectural decisions with context, alternatives considered, trade-offs
  5. Dependency Rationale — Why each major dependency was chosen, what it replaced
  6. Data Flow & State — How data moves through the system (traced from actual code, not guessed)
  7. Failure Modes & Error Handling — What breaks, how errors propagate, recovery patterns
  8. Performance Characteristics — Bottlenecks, scaling limits, hot paths
  9. Security Model — Auth, authorization, trust boundaries, data sensitivity
  10. Testing Strategy — What's tested, what isn't, testing philosophy
  11. Operational Concerns — Deployment, monitoring, feature flags, configuration
  12. Known Technical Debt — Honest assessment of shortcuts and their risks

Rules

  • Every claim backed by (file_path:line_number) citation
  • Minimum 3 Mermaid diagrams (architecture, data flow, dependency graph)
  • All Mermaid diagrams use dark-mode colors (see wiki-vitepress skill)
  • Focus on WHY decisions were made, not just WHAT exists

Guide 2: Zero-to-Hero Contributor Guide

Audience: New contributors who need step-by-step practical guidance.

Required Sections

  1. What This Project Does — 2-3 sentence elevator pitch
  2. Prerequisites — Tools, versions, accounts needed
  3. Environment Setup — Step-by-step with exact commands, expected output at each step
  4. Project Structure — Annotated directory tree (what lives where and why)
  5. Your First Task — End-to-end walkthrough of adding a simple feature
  6. Development Workflow — Branch strategy, commit conventions, PR process
  7. Running Tests — How to run tests, what to test, how to add a test
  8. Debugging Guide — Common issues and how to diagnose them
  9. Key Concepts — Domain-specific terminology explained with code examples
  10. Code Patterns — "If you want to add X, follow this pattern" templates
  11. Common Pitfalls — Mistakes every new contributor makes and how to avoid them
  12. Where to Get Help — Communication channels, documentation, key contacts
  13. Glossary — Terms used in the codebase that aren't obvious
  14. Quick Reference Card — Cheat sheet of most-used commands and patterns

Rules

  • All code examples in the detected primary language
  • Every command must be copy-pasteable
  • Include expected output for verification steps
  • Use Mermaid for workflow diagrams (dark-mode colors)
  • Ground all claims in actual code — cite (file_path:line_number)

When to Use

This skill is applicable to execute the workflow or actions described in the overview.

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

12-agent academic paper writing pipeline. 10 modes (full/plan/outline/revision/revision-coach/abstract/lit-review/format-convert/citation-check/disclosure). 6 paper types, 5 citation formats, bilingual abstracts, LaTeX/DOCX-via-Pandoc/PDF output. Style Calibration + Writing Quality Check + Anti-Patterns with IRON RULE markers. Triggers: write paper, academic paper, guide my paper, parse reviews, AI disclosure, 寫論文, 學術論文, 引導我寫論文, 審查意見.

日本語の概要は準備中です。原文の説明を表示しています。

bouclem/skills62026年5月31日 更新

Multi-perspective academic paper review with dynamic reviewer personas. Simulates 5 independent reviewers (EIC + 3 peer reviewers + Devil's Advocate) with field-specific expertise. Supports full review, re-review (verification), quick assessment, methodology focus, Socratic guided, and calibration modes. Triggers on: review paper, peer review, manuscript review, referee report, review my paper, critique paper, simulate review, editorial review, calibrate reviewer, reviewer calibration, measure reviewer accuracy.

日本語の概要は準備中です。原文の説明を表示しています。

bouclem/skills62026年5月31日 更新

Orchestrator for the full academic research pipeline: research -> write -> integrity check -> review -> revise -> re-review -> re-revise -> final integrity check -> finalize. Coordinates deep-research, academic-paper, and academic-paper-reviewer into a seamless 10-stage workflow with mandatory integrity verification, two-stage peer review, and reproducible quality gates. Triggers on: academic pipeline, research to paper, full paper workflow, paper pipeline, end-to-end paper, research-to-publication, complete paper workflow.

日本語の概要は準備中です。原文の説明を表示しています。

bouclem/skills62026年5月31日 更新

Create, iterate, and scale paid ad creative for Google Ads, Meta, LinkedIn, TikTok, and similar platforms. Use when generating headlines, descriptions, primary text, or large sets of ad variations for testing and performance optimization.

日本語の概要は準備中です。原文の説明を表示しています。

bouclem/skills62026年5月31日 更新

This skill should be used when the user asks to "implement LLM-as-judge", "compare model outputs", "create evaluation rubrics", "mitigate evaluation bias", or mentions direct scoring, pairwise comparison, position bias, evaluation pipelines, or automated quality assessment.

日本語の概要は準備中です。原文の説明を表示しています。

bouclem/skills62026年5月31日 更新

AI agent development workflow for building autonomous agents, multi-agent systems, and agent orchestration with CrewAI, LangGraph, and custom agents.

日本語の概要は準備中です。原文の説明を表示しています。

bouclem/skills62026年5月31日 更新

bouclem のスキルをすべて見る

このスキルの問題を報告する