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Unicorn Harness

One person, hundred-person-team engineering judgment.

7 principles extracted from production-grade systems (Claude Code v2.1.88) and generalized into a thinking framework that applies to any product domain — SaaS, CLI/DevTools, Agent orchestration, AIGC, e-commerce, content platforms, and beyond.

"We don't just incubate unicorns — we build the engine that continuously fissions new ones." — Nebutra Manifesto

What This Is

A Claude Code SKILL that upgrades engineering decision-making. Not a tutorial. Not a checklist. A thinking operating system.

The gap between "can write code" and "can ship a unicorn-grade product" isn't technical — it's cognitive. This SKILL closes that gap by encoding the thinking patterns behind $1B products into 7 actionable principles.

The 7 Principles

# Principle One-liner
1 Minimum Intervention Lightest fix first — escalate only when cheaper options fail
2 Boundary Is Product Every line you draw shapes user experience
3 Lifecycle, Not Function Design how things are born, live, and die — before writing code
4 Earn Trust Progressively Never demand all trust upfront
5 Constraint As Fuel Limitations are design starting points, not excuses
6 Policy In Code, Not Wiki Rules in wikis get broken; rules in compilers don't
7 Soul Before Scale Product personality is foundation, not decoration

Quick Start

As a Claude Code SKILL

# Add as a git submodule to your project
git submodule add https://github.com/Nebutra/claude-code-harness.git .claude/skills/claude-code-harness

# Or copy the SKILL.md into your skills directory
cp claude-code-harness/SKILL.md ~/.claude/skills/claude-code-harness/SKILL.md

Just Read the Principles

Each principle has a deep-dive reference document:

Each reference covers: what the principle says, why it matters, how Claude Code implements it, how to migrate it to YOUR product, anti-patterns, and self-check questions.

Supplementary deep-dives (for specialized domains):

Blueprints (step-by-step decision checklists):

When to Use

You're doing... Focus on...
Building from 0 to 1 Soul, Constraint, Boundary
Designing API / architecture Boundary, Lifecycle, Policy
Performance / cost optimization Minimum Intervention, Constraint
Permission / security design Trust, Boundary, Policy
Building Agent / AI products All, especially Intervention + Lifecycle
Identifying tech debt All — use self-check questions as audit
Pre-launch review Full pass through all 7

Benchmarks

Tested with real prompts across 4 rounds, 6 subagents, 2 tasks (Agent architecture design + production codebase tech debt audit). Compared: no SKILL vs v1 SKILL vs v2 SKILL.

Agent Architecture Design Task

Metric No SKILL v2 SKILL
Tokens 23K 33K (+43%)
Boundary reasoning Lists component responsibilities Justifies each boundary by semantic difference; rebuts 3 common wrong approaches
Error handling Decision tree (classify → route) 5-level intervention ladder (retry → replan → human → fail)
Type safety Standard interfaces Opaque BudgetToken forces compile-time budget check
Crash recovery Checkpoint mentioned Every state answers "what if process crashes here?" + two-phase commit
Tech recommendations Specific (BullMQ, Postgres) Specific + rationale per choice
Anti-patterns section None 5 anti-patterns with explanation of why each is tempting

Tech Debt Audit Task (real production monorepo)

Metric No SKILL v2 SKILL
Tokens / tool calls 116K / 113 87K / 52 (-25% / -54%)
Unique findings Zod version split, phantom schemas S2S HMAC mismatch, mock payment path, hardcoded plan limit
Fix specificity Directional recommendations Inline code fixes, "fix today" vs "next sprint" triage
Insight quality Describes what exists "Half-completed good intentions are more dangerous than never starting — they create the illusion of safety"

What the SKILL produces that baseline doesn't

  • Opaque type patterns that make wrong usage a compile error
  • Intervention cost ladders for error handling and resource management
  • Watchdog processes that don't trust the executor to self-terminate
  • "Phantom reliability" diagnosis (code that looks production-ready but runs in-process memory)
  • Bugs found through boundary/lifecycle lens that standard audit misses (HMAC auth actually broken)

Honest limitations

  • +43% token cost on architecture tasks — worth it for high-stakes decisions, overkill for CRUD
  • Best on Sonnet/Opus — may degrade on smaller models
  • Not a domain expert — improves architectural judgment, doesn't replace business knowledge
  • Diminishing returns on simple tasks — writing a utility function doesn't need 7 principles

When to use / when to skip

Use Skip
0-to-1 architecture design Simple bug fixes
Tech debt audit Writing unit tests
Agent/AI product design CRUD endpoints
System review before launch Daily coding tasks
Upgrading demo to production Documentation updates

Part of the Nebutra Ecosystem

Nebutra Manifesto (philosophy)    → "Infinite fission, not infinite expansion"
Unicorn Harness (cognition)       → How to think     ← this repo
Nebutra Sailor (infrastructure)   → 53 modules built on these principles
Sleptons (community)              → OPC ecosystem powered by this thinking

Contributing

Migration examples from new domains are welcome. Each principle's reference file has a "Migrate to your product" section — if your domain isn't covered, submit a PR.

License

MIT — thinking frameworks should spread without friction.

Releases

No releases published

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