Teach Oh

/teach-oh

Setup that gathers project context and saves it to AGENTS.md (the cross-agent standard). Run when starting on a project or when strategy/aims have shifted.

When to Use

Invoke /teach-oh when:

• Starting on a new project - Before diving into work
• Context keeps getting lost - AI assistants don't "get" your project
• Onboarding a new AI tool - Establish shared understanding upfront
• After major strategic shifts - When aims or constraints have changed

Do not use when: You're mid-task. This is setup, not execution.

The Process

Step 0: Check for RNA MCP (Repo-Native Alignment)

Before exploring, check if RNA is available — it makes everything that follows richer.

Detection (in order):

1. Check if oh_search_context or search_symbols tools are available in the current session (RNA MCP already configured)
2. Check if repo-native-alignment is on PATH: which repo-native-alignment
3. Check if .mcp.json references repo-native-alignment or rna-server

If RNA is available: Proceed to Step 1. Use RNA tools (search_symbols, oh_search_context, graph_query) throughout exploration instead of Grep/Read.

If RNA is NOT available: Offer to install it:

"I can set up Repo-Native Alignment (RNA) — it gives me semantic code search, graph traversal, and business context awareness across your codebase. Takes ~1 minute. Want me to install it?"

If accepted:

1. Detect platform and chip:

   OS=$(uname -s)
   ARCH=$(uname -m)
   CHIP=$(sysctl -n machdep.cpu.brand_string 2>/dev/null || echo "")
   

   • macOS ARM M4+: Darwin + arm64 + brand_string contains "M4" → use darwin-arm64-m4
   • macOS ARM (other): Darwin + arm64 → use darwin-arm64
   • Linux x86_64: Linux + x86_64 → use linux-x86_64

2. Download the binary to ~/.local/bin/ (no sudo required):

   mkdir -p ~/.cargo/bin
   
   # macOS M4+
   curl -L https://github.com/open-horizon-labs/repo-native-alignment/releases/latest/download/repo-native-alignment-darwin-arm64-m4 -o ~/.cargo/bin/repo-native-alignment && chmod +x ~/.cargo/bin/repo-native-alignment
   
   # macOS M1/M2/M3
   curl -L https://github.com/open-horizon-labs/repo-native-alignment/releases/latest/download/repo-native-alignment-darwin-arm64 -o ~/.cargo/bin/repo-native-alignment && chmod +x ~/.cargo/bin/repo-native-alignment
   
   # Linux x86_64
   curl -L https://github.com/open-horizon-labs/repo-native-alignment/releases/latest/download/repo-native-alignment-linux-x86_64 -o ~/.cargo/bin/repo-native-alignment && chmod +x ~/.cargo/bin/repo-native-alignment
   

   ~/.cargo/bin is on PATH for Rust users (set up by rustup).

3. Run setup for the current project:

   repo-native-alignment setup --project .
   

   This configures .mcp.json and verifies the pipeline.

4. Tell the user: "RNA is installed. Continuing with RNA CLI tools for this session — search and graph work now. MCP tools (oh_search_context, search_symbols, graph_query) will be available after you restart Claude Code."

If declined: Proceed without RNA. teach-oh works fine without it — exploration just uses standard tools (Grep, Read, Glob).

Step 1: Explore the Codebase

Before asking questions, scan the project independently:

Structure & Stack

• Directory layout, key folders
• Package files (package.json, Cargo.toml, go.mod, etc.)
• Build configuration, CI/CD setup

Existing Context

• AGENTS.md, CLAUDE.md, README, CONTRIBUTING
• .oh/, docs/adr/ directories
• Any existing project documentation

Patterns & Conventions

• Naming conventions in code
• File organization patterns
• Recent git commits for style and focus

Don't ask about what you can discover. Use exploration to form better questions.

Step 2: Ask About What Matters

After exploration, ask targeted questions about what couldn't be inferred. Focus on strategy and aims, not just code.

Purpose & Aims

• What is this project trying to achieve?
• Who uses it? What change in their behavior indicates success?
• What's the current focus or priority?

Strategic Constraints

• What constraints never bend? (Compliance, performance SLAs, etc.)
• What trade-offs has the team made intentionally?
• What's explicitly out of scope?

Team & Decision-Making

• How does the team make decisions?
• What does "done" mean here?
• Any patterns or practices that are sacred?

What to Avoid

• Past mistakes that shouldn't be repeated
• Patterns that look tempting but don't fit
• Areas of the codebase that are sensitive

Ask only what you couldn't discover. Respect the user's time.

Step 3: Write Persistent Context

Synthesize findings into a structured section and offer to append to AGENTS.md (or create it if missing).

Offer two sections:

1. Open Horizons Framework - The strategic framework for AI-assisted work (offer to include if user uses OH skills)
2. Project Context - Project-specific aims, constraints, and patterns (always include)

If phase agents were installed in Step 5, use the agents variant below. Otherwise use the skills variant.

Skills variant (no agents):

# Open Horizons Framework

**The shift:** Action is cheap. Knowing what to do is scarce.

**The sequence:** aim → problem-space → problem-statement → solution-space → execute → ship

**Where to start (triggers):**
- Can't explain why you're building this → `/aim`
- Keep hitting the same blockers → `/problem-space`
- Solutions feel forced → `/problem-statement`
- About to start coding → `/solution-space`
- Work is drifting or reversing → `/salvage`

**Reflection skills (use anytime):**
- `/review` - Check alignment before committing
- `/dissent` - Seek contrary evidence before one-way doors
- `/salvage` - Extract learning, restart clean
- `/distill` - Curate accumulated metis; surface patterns for promotion

**Key insight:** Enter at the altitude you need. Climb back up when you drift.

---

# Project Context

## Purpose
[What this project does and why it matters]

## Current Aims
[Active goals and what success looks like]

## Key Constraints
- [Constraint 1]: [Why it exists]
- [Constraint 2]: [Why it exists]

## Patterns to Follow
- [Pattern]: [When/why to use it]

## Anti-Patterns to Avoid
- [Anti-pattern]: [Why it's problematic here]

## Decision Context
[How the team makes decisions, what "done" means]

Agents variant (phase agents installed):

# Open Horizons Framework

**The shift:** Action is cheap. Knowing what to do is scarce.

**The sequence:** aim → problem-space → problem-statement → solution-space → execute → ship

Each phase runs as an agent with isolated context and scoped tools. Dispatch via
the `task` tool — each agent reads/writes `.oh/<session>.md` to pass context
between phases.

**Where to start (triggers):**
- Can't explain why you're building this → dispatch `oh-aim` agent
- Keep hitting the same blockers → dispatch `oh-problem-space` agent
- Solutions feel forced → dispatch `oh-problem-statement` agent
- About to start coding → dispatch `oh-solution-space` agent
- Ready to implement → dispatch `oh-execute` agent
- Code complete, need to deliver → dispatch `oh-ship` agent
- Work is drifting or reversing → `/salvage`

**Reflection skills (use anytime, in main session):**
- `/review` - Check alignment before committing
- `/dissent` - Seek contrary evidence before one-way doors
- `/salvage` - Extract learning, restart clean
- `/distill` - Curate accumulated metis; surface patterns for promotion

**Key insight:** Enter at the altitude you need. Climb back up when you drift.

---

# Project Context

## Purpose
[What this project does and why it matters]

## Current Aims
[Active goals and what success looks like]

## Key Constraints
- [Constraint 1]: [Why it exists]
- [Constraint 2]: [Why it exists]

## Patterns to Follow
- [Pattern]: [When/why to use it]

## Anti-Patterns to Avoid
- [Anti-pattern]: [Why it's problematic here]

## Decision Context
[How the team makes decisions, what "done" means]

Output Format

Present findings for user approval before writing:

## Teach-OH Summary

### What I Discovered
- Stack: [technologies found]
- Structure: [key patterns observed]
- Existing context: [what docs already exist]

### Questions I Have
1. [Question about aims/strategy]
2. [Question about constraints]
3. [Question about team practices]

---

After your answers, I'll draft a AGENTS.md section for your approval.

After user answers:

## Proposed AGENTS.md Addition

[Draft the Project Context section]

---

**Write to AGENTS.md?** [Yes/No - show what will be added/updated]

Example

/teach-oh

Agent explores, then:

## Teach-OH Summary

### What I Discovered
- Stack: TypeScript, React, Node.js, PostgreSQL
- Structure: Monorepo with apps/ and packages/
- Existing context: README exists, no AGENTS.md or CLAUDE.md
- Recent focus: Auth refactor (last 12 commits)

### Questions I Have
1. What's the main aim right now? The auth work—is that about security, UX, or maintenance?
2. I see both REST and GraphQL endpoints. Is one preferred, or context-dependent?
3. Any performance constraints? I see a Redis layer but no docs on when to use it.
4. What patterns should I follow vs. avoid?

User answers, agent drafts:

## Proposed AGENTS.md Addition

# Open Horizons Framework

**The shift:** Action is cheap. Knowing what to do is scarce.

**The sequence:** aim → problem-space → problem-statement → solution-space → execute → ship

**Where to start (triggers):**
- Can't explain why you're building this → `/aim`
- Keep hitting the same blockers → `/problem-space`
- Solutions feel forced → `/problem-statement`
- About to start coding → `/solution-space`
- Work is drifting or reversing → `/salvage`

**Reflection skills:** `/review`, `/dissent`, `/salvage`, `/distill`

**Key insight:** Enter at the altitude you need. Climb back up when you drift.

---

# Project Context

## Purpose
Customer portal for B2B SaaS. Users are account admins managing their organization's settings, users, and billing.

## Current Aims
- Simplify auth flow so new SSO providers can be added in <1 day (currently takes 2 weeks)
- Success: Adding Okta support by end of Q1

## Key Constraints
- SOC2 compliance: All auth changes need security review
- <200ms API response time (SLA commitment)
- No breaking changes to existing OAuth integrations

## Patterns to Follow
- REST for public API, GraphQL for internal dashboard
- Redis for session state only, not general caching
- Feature flags via LaunchDarkly for gradual rollouts

## Anti-Patterns to Avoid
- Don't abstract OAuth providers into single interface (they have semantic differences)
- Avoid adding new environment variables without updating .env.example

## Decision Context
Tech lead approves architecture changes. PRs need one review. "Done" = deployed to staging with passing E2E tests.

---

**Write to AGENTS.md?** This will create a new file at ./AGENTS.md

Step 4 (Optional, OMP only): Phase-Aware Hook

If the user is running OMP (oh-my-pi), offer to install the phase-aware skills hook. This hook makes the framework self-guiding — it detects where the user is in the development cycle and suggests the right skill before each prompt.

When to offer: After writing AGENTS.md, if the project uses OMP. Detect OMP by checking for .omp/ directory or omp in the shell path.

What to ask:

"Install the phase-aware skills hook? It reads your .oh/ session files and suggests the right OH skill at the right moment. Copies oh-skills-phase.ts to .omp/hooks/ for auto-discovery."

If accepted:

1. Fetch the hook source from GitHub and write it to the project's .omp/hooks/oh-skills-phase.ts (create the directory if needed):

   https://raw.githubusercontent.com/open-horizon-labs/skills/master/hooks-omp/oh-skills-phase.ts
   

   Do NOT fabricate or rewrite the hook — always fetch the canonical source.

2. Optionally create .oh/skills-config.json based on what you learned about the project. The config is loaded once at session start (changes require restarting OMP):

{
  "projectSkills": ["aim", "problem-space", "solution-space", "execute", "review", "dissent"],
  "disabledSkills": [],
  "phaseOverrides": {
    "execute": ["dissent"]
  }
}

Customization guidance:

• projectSkills: Include only the skills relevant to this project's workflow. A solo dev doing rapid iteration might skip problem-space. A team with compliance requirements might always want dissent before execute. Note: phaseOverrides targets must be included in projectSkills — override skills are filtered by the same allow list. Reflection skills (review, dissent, salvage, distill) are always-available and don't need to appear in projectSkills — they're invoked on demand, not phase-triggered.
• disabledSkills: Skills that don't fit this project (e.g., ship for a library that publishes via CI).
• phaseOverrides: Extra skills to suggest during specific phases. Common: adding dissent during execute for security-sensitive projects.

If declined: Skip. The skills work fine without it — this is an enhancement, not a requirement.

If the user is not running OMP: Skip this step entirely. The hook requires the OMP hook API and will not work with other agents. Users can still install it manually later by copying the file to .omp/hooks/.

Step 5 (Optional, OMP only): Install Phase Agents

Phase skills benefit from running in isolated context windows with scoped tools — formalizing the pattern of clearing sessions between phases. Offer to install pre-built agent wrappers that give each phase its own context.

When to offer: After Step 4, if OMP detected.

What to ask:

"Install OH phase agents? Each phase gets isolated context and scoped tools — aim/problem-statement are read-only, execute gets full capabilities. Writes to .omp/agents/."

If accepted:

Fetch all 6 agent files from GitHub and write each to .omp/agents/ (create the directory if needed):

Base URL: https://raw.githubusercontent.com/open-horizon-labs/skills/master/agents-omp/
Files:
  oh-aim.md
  oh-problem-space.md
  oh-problem-statement.md
  oh-solution-space.md
  oh-execute.md
  oh-ship.md

Do NOT fabricate or rewrite the agent files — always fetch the canonical source.

MCP preamble (only if OH MCP is configured — check for oh_get_endeavors in the parent session's available tools, or for .oh/mcp.json in the project): After writing all 6 files, append this block to each agent file:

## Open Horizons MCP
- Query related endeavors for context before starting analysis
- Log key outputs (aim statements, problem statements, decisions) to the graph
- Link session work to active endeavors

If OH MCP is not present, skip this block — the agents work without it.

RNA MCP preamble (only if repo-native-alignment MCP is configured — check for oh_search_context in the parent session's available tools, or for rna-server in .mcp.json): After writing all 6 files, append this block to each agent file:

## Repo-Native Alignment MCP
When rna-server tools are available:
- Before framing: call `oh_search_context` with your task description to find relevant outcomes, guardrails, and metis
- After producing output: write learnings to `.oh/metis/<slug>.md`
- When checking progress: call `outcome_progress` with the relevant outcome ID
- When discovering constraints: write to `.oh/guardrails/<slug>.md`
- When measuring progress: write to `.oh/signals/<slug>.md`
- After completing work: tag commits with `[outcome:X]`

If RNA MCP is not present, skip this block — the agents work without it.

Cross-cutting skills (review, dissent, salvage) stay as skills — they need conversation context to detect drift.

If declined: Skip. Skills continue to work as prompt injections.

Step 6 (Optional, Claude Code): Install Phase Agents

If the user is running Claude Code (not OMP), offer to install phase agents to .claude/agents/.

When to offer: After writing AGENTS.md, if Claude Code detected (check for .claude/ directory or if running as Claude Code).

What to ask:

"Install OH phase agents for Claude Code? Each phase gets its own agent with scoped tools. Writes to .claude/agents/."

If accepted:

Fetch all 6 agent files from GitHub and write each to .claude/agents/ (create the directory if needed):

Base URL: https://raw.githubusercontent.com/open-horizon-labs/skills/master/agents-claude/
Files:
  oh-aim.md
  oh-problem-space.md
  oh-problem-statement.md
  oh-solution-space.md
  oh-execute.md
  oh-ship.md

Do NOT fabricate or rewrite the agent files — always fetch the canonical source.

MCP preambles: The pre-packaged Claude Code agents already include OH MCP and RNA MCP preamble sections. No additional append needed.

If declined: Skip. Skills continue to work as slash commands.

What This Enables

With project context established:

• /aim frames outcomes in your language
• /problem-space knows which constraints are real
• /dissent understands your risk tolerance
• /review checks against your definition of done
• /execute follows your patterns

Notes

• Context lives in AGENTS.md so it persists across sessions
• Keep it focused—this isn't documentation, it's working context
• Re-run when aims shift, constraints change, or context feels stale

Remember: This is setup, not ongoing work. Invest 10 minutes when starting or when things have shifted.

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