oh-my-customcode

Your AI Agent Stack. Compiled, Not Configured.

한국어 문서 (Korean)

45 agents. 82 skills. 21 rules. One command.

npm install -g oh-my-customcode && cd your-project && omcustom init

What's New in v0.38.0

| Feature | Description | |---------|-------------| | Interactive Init Wizard | omcustom init now uses @clack/prompts for guided setup — language, framework, team mode | | PostCompact Hook | Automatic rule reinforcement after context compaction (CC v2.1.76+) — prevents rule amnesia | | @omcustom/eval-core MVP | LLM evaluation engine: session/turn/outcome collection, SQLite via Drizzle ORM, CLI interface | | Codex-exec Auto-delegation | Routing skills automatically delegate to Codex when available | | CC v2.1.72~v2.1.76 Compatibility | SessionEnd timeout config, HTML comment optimization, autoMemoryDirectory, full model ID support | | Template Full Sync | All 200+ template files are byte-identical to source | | Hook System Hardening | Duplicate recorder removal, context-budget field fix, orphan cleanup |

Philosophy

oh-my-customcode is built on two ideas:

1. Agent systems are compiled, not configured.

| Compile Concept | oh-my-customcode | |----------------|-----------------| | Source code | .claude/skills/ — reusable knowledge and workflows | | Build artifacts | .claude/agents/ — executable specialists assembled from skills | | Compiler | mgr-sauron (R017) — structural verification and integrity | | Spec | .claude/rules/ — constraints and build rules | | Linker | Routing skills — connect agents to tasks | | Standard library | guides/ — shared reference documentation |

Skills are source. Agents are compiled output. Sauron verifies the build. This separation means skills evolve independently of agents, and agents can be recompiled from updated skills at any time.

2. If it can't be done, make it work.

When no specialist exists for a task, oh-my-customcode does not fail. It creates one.

User: "Review this Terraform module"
  → Routing: no terraform expert found
  → mgr-creator discovers: infra-aws-expert skills + docker-best-practices guide
  → Creates: infra-terraform-expert.md
  → Executes the review immediately
  → Agent persists for future use

This is not a fallback. It is the design. The system treats missing expertise as a build problem — find the right skills, compile a new agent, execute.

How It Works

Orchestration

The main conversation acts as a singleton orchestrator (R010). It never writes files directly. Every action is delegated through routing skills to specialized agents.

User (natural language)
  → Routing skill (intent detection, confidence scoring)
    → Specialized agent (isolated execution)
      → Result returned to orchestrator
        → Response to user

Four routing skills cover the full domain:

| Routing Skill | Routes To | |--------------|-----------| | secretary-routing | Manager agents (mgr-), system agents (sys-) | | dev-lead-routing | Language, backend, frontend, tooling, DB, infra, arch agents | | de-lead-routing | Data engineering agents (de-*) | | qa-lead-routing | QA team (qa-planner, qa-writer, qa-engineer) |

Model Selection

Each agent runs on the model optimized for its task:

| Model | When | Examples | |-------|------|---------| | opus | Complex reasoning, architecture | Design review, research synthesis | | sonnet | Implementation, general tasks | Code generation, agent creation | | haiku | Fast validation, search | File search, count verification |

The reasoning-sandwich pattern formalizes this: opus for pre-analysis, sonnet for implementation, haiku for post-verification.

Parallel Execution

Independent tasks run in parallel (R009). Up to 4 concurrent agents per message:

Agent(lang-golang-expert):sonnet  ┐
Agent(lang-python-expert):sonnet  ├─ All spawned in one message
Agent(qa-engineer):sonnet         │
Agent(arch-documenter):haiku      ┘

Agents (45)

| Category | Count | Agents | |----------|-------|--------| | Languages | 6 | lang-golang, lang-python, lang-rust, lang-kotlin, lang-typescript, lang-java21 | | Backend | 6 | be-fastapi, be-springboot, be-go-backend, be-express, be-nestjs, be-django | | Frontend | 4 | fe-vercel, fe-vuejs, fe-svelte, fe-flutter | | Data Engineering | 6 | de-airflow, de-dbt, de-spark, de-kafka, de-snowflake, de-pipeline | | Database | 4 | db-supabase, db-postgres, db-redis, db-alembic | | Tooling | 3 | tool-npm, tool-optimizer, tool-bun | | Architecture | 2 | arch-documenter, arch-speckit | | Infrastructure | 2 | infra-docker, infra-aws | | QA | 3 | qa-planner, qa-writer, qa-engineer | | Security | 1 | sec-codeql | | Managers | 6 | mgr-creator, mgr-updater, mgr-supplier, mgr-gitnerd, mgr-sauron, mgr-claude-code-bible | | System | 2 | sys-memory-keeper, sys-naggy |

Each agent declares its tools, model, memory scope, and limitations in YAML frontmatter. Tool budgets are enforced per agent type for accuracy.

Skills (82)

| Category | Count | Includes | |----------|-------|----------| | Best Practices | 24 | Go, Python, TypeScript, Kotlin, Rust, React, FastAPI, Spring Boot, Django, Flutter, Docker, AWS, Postgres, Redis, Kafka, dbt, Spark, Snowflake, Airflow, pipeline-architecture-patterns, alembic, and more | | Routing | 4 | secretary, dev-lead, de-lead, qa-lead | | Workflow | 12 | structured-dev-cycle, deep-plan, research, evaluator-optimizer, dag-orchestration, worker-reviewer-pipeline, reasoning-sandwich, and more | | Development | 7 | dev-review, dev-refactor, analysis, create-agent, intent-detection, web-design-guidelines, omcustom-takeover | | Operations | 9 | update-docs, audit-agents, sauron-watch, monitoring-setup, fix-refs, release-notes, and more | | Memory | 3 | memory-save, memory-recall, memory-management | | Package | 3 | npm-publish, npm-version, npm-audit | | Optimization | 3 | optimize-analyze, optimize-bundle, optimize-report | | Security | 3 | adversarial-review, cve-triage, jinja2-prompts | | Other | 8 | codex-exec, vercel-deploy, skills-sh-search, result-aggregation, writing-clearly-and-concisely, and more |

Skills use a 3-tier scope system: core (universal), harness (agent/skill maintenance), package (project-specific).

Commands

All commands are invoked inside the Claude Code conversation.

Development

| Command | What it does | |---------|-------------| | /dev-review | Code review against best practices | | /dev-refactor | Refactor for structure and patterns | | /structured-dev-cycle | 6-stage development: plan → verify → implement → verify → compound → done | | /deep-plan | Research-validated planning | | /research | 10-team parallel analysis with cross-verification |

Agent Management

| Command | What it does | |---------|-------------| | /omcustom:analysis | Analyze project, auto-configure agents and skills | | /omcustom:create-agent | Create a new agent | | /omcustom:takeover | Extract canonical spec from existing agent or skill | | /omcustom:audit-agents | Audit agent dependencies | | /omcustom:update-docs | Sync project structure and documentation | | /omcustom:sauron-watch | Full structural verification (5+3 rounds) |

Package & Release

| Command | What it does | |---------|-------------| | /omcustom:npm-publish | Publish to npm | | /omcustom:npm-version | Semantic versioning | | /omcustom:npm-audit | Dependency security audit | | /omcustom:release-notes | Generate release notes from git history |

Memory & System

| Command | What it does | |---------|-------------| | /memory-save | Save session context | | /memory-recall | Search and recall memories | | /omcustom:monitoring-setup | OTel monitoring toggle | | /omcustom:lists | Show all commands | | /omcustom:status | System health check |

Rules (21)

| Priority | Count | Purpose | |----------|-------|---------| | MUST | 14 | Safety, permissions, agent design, identification, orchestration, verification, completion, enforcement | | SHOULD | 6 | Interaction, error handling, memory, HUD, ecomode, ontology routing | | MAY | 1 | Optimization |

Key rules: R010 (orchestrator never writes files), R009 (parallel execution mandatory), R017 (sauron verification before push), R020 (completion verification before declaring done), R021 (advisory-first enforcement model).

Guides (28)

Reference documentation covering best practices, architecture decisions, and integration patterns. Located in guides/ at project root, covering topics from agent design to CI/CD to observability.

Safety

oh-my-customcode includes security and lifecycle hooks:

| Hook | Trigger | Action | |------|---------|--------| | secret-filter | Bash, Read output | Detects AWS keys, API tokens, private keys, bearer tokens | | audit-log | Edit, Write, Bash, Agent | Append-only JSONL at ~/.claude/audit.jsonl | | schema-validator | Write, Edit, Bash input | Validates tool inputs, flags dangerous patterns | | PostCompact | Context compaction | Reinjects enforced rules (R007–R018) — prevents rule amnesia |

Security hooks are advisory (exit 0). They warn but never block.

CLI

omcustom init                  # Interactive setup wizard (language, framework, team mode)
omcustom init --lang ko        # Initialize with Korean
omcustom update                # Update to latest
omcustom list                  # List components
omcustom doctor                # Verify installation
omcustom doctor --fix          # Auto-fix issues
omcustom security              # Scan for security issues

Project Structure

your-project/
├── CLAUDE.md                   # Entry point
├── .claude/
│   ├── agents/                 # 45 agent definitions
│   ├── skills/                 # 78 skill modules
│   ├── rules/                  # 21 governance rules (R000-R021)
│   ├── hooks/                  # 15 lifecycle hook scripts
│   ├── schemas/                # Tool input validation schemas
│   ├── specs/                  # Extracted canonical specs
│   ├── contexts/               # 4 shared context files
│   └── ontology/               # Knowledge graph for RAG
└── guides/                     # 28 reference documents

Development

bun install          # Install dependencies
bun run dev          # Development mode
bun test             # Run tests
bun run build        # Production build

Requirements: Node.js >= 18.0.0, Claude Code CLI.

License

MIT