Agent skill

ai-guide

Use when onboarding to a project, exploring architecture, or understanding why decisions were made: interactive tours, decision archaeology, and codebase discovery.

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Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/other/ai-guide-arcasilesgroup-ai-engineering

SKILL.md

Guide

Project onboarding, architecture tours, and decision archaeology. Optimized for the human, not the code. Reads everything, modifies nothing. Teaches understanding, not artifacts.

When to Use

  • New to a project and need orientation.
  • Want to understand component relationships and data flow.
  • Asking "why was X chosen over Y?"
  • NOT for writing code -- use ai-build agent.
  • NOT for generating docs -- use /ai-write.

Modes

tour -- Architecture Overview

  1. Map structure -- use Glob to identify key directories, entry points, config files.
  2. Identify stack -- detect languages, frameworks, build tools.
  3. Present overview -- component boundaries, dependencies, data flow (ASCII diagram).
  4. Explain key patterns -- design patterns, idioms, conventions used.
  5. Highlight evolution -- git log --oneline for major changes.
  6. Flag gotchas -- non-obvious behavior, implicit assumptions, known debt.
  7. Suggest next -- related components worth exploring.

find -- Topic Search

  1. Search codebase -- Grep/Glob for the topic across source, config, docs.
  2. Search decisions -- check state/decision-store.json for related decisions.
  3. Search specs -- look in specs/ for relevant specifications.
  4. Present results -- files, functions, and context around the topic.
  5. Answer the question -- "where does X happen?", "how do I add a Y?", "what tests cover Z?"

history -- Decision Archaeology

  1. Search decision store -- state/decision-store.json for formal decisions.
  2. Search git history -- git log --all --grep for related commits.
  3. Search specs -- specs/ for specs that introduced the decision.
  4. Reconstruct context -- what was known, what constraints existed, what alternatives were considered.
  5. Present alternatives -- what other options existed and why they were rejected.
  6. Assess relevance -- has context changed? Are original constraints still valid?
  7. Do NOT recommend -- present analysis, let developer decide.

onboard -- Structured Onboarding

  1. Map structure -- directories, entry points, config, dependencies.
  2. Identify stack -- languages, frameworks, tools.
  3. Discover patterns -- recurring code patterns, naming conventions.
  4. Find key files -- main entry, config, models, tests.
  5. Review standards -- .ai-engineering/standards/ for project conventions.
  6. Socratic checkpoints -- after each phase, ask one question to confirm understanding.
  7. Personalized path -- based on what the developer wants to work on.

Quick Reference

/ai-guide tour                    # architecture overview
/ai-guide find "authentication"   # where does auth happen?
/ai-guide history "why SQLite"    # decision archaeology
/ai-guide onboard                 # structured onboarding

Common Mistakes

  • Making decisions for the developer -- present tradeoffs, let them decide.
  • Writing code during a tour -- guide is strictly read-only.
  • Over-quizzing -- max 2 Socratic questions per interaction.
  • Teaching below the developer's level -- match cues to Bloom's taxonomy.

Integration

  • Uses /ai-explain for 3-tier depth explanations.
  • Reads state/decision-store.json for decision context.
  • Reads state/audit-log.ndjson for session context (privacy by design).

References

  • .claude/skills/ai-explain/SKILL.md -- 3-tier depth model.
  • .ai-engineering/manifest.yml -- governance structure.
  • state/decision-store.json -- decision records. $ARGUMENTS

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