mcpField
H
harness-engineering

harness-engineering

github.com/kangarookingAgent workflows693181 installsUpdated 8w ago
Repository

About harness-engineering

harness-engineering initializes a Harness Engineering framework in a project for teams structuring AI-assisted development. It combines planning, implementation, and evaluation agents with sprint contracts and quality hooks.

Key features

  1. 01Scaffolds project framework files
  2. 02Sets up planner, generator, and evaluator agents
  3. 03Defines verifiable sprint completion criteria
  4. 04Adds loop detection and completion hooks
  5. 05Provides plan, build, QA, and sprint commands

Use cases

  1. 01Set up AI-assisted development for a new project
  2. 02Add a plan-build-verify cycle to an existing project

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/kangarooking/kangarooking-skills --skill harness-engineering

After installing, type/harness-engineeringin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

scripts/
scaffold.py
templates/
CLAUDE.md
settings.json
templates/agents/
doc-gardener.md
evaluator.md
generator.md
planner.md
templates/commands/
build.md
plan.md
qa.md
sprint.md
templates/docs/
architecture.md
golden-principles.md
sprint-workflow.md
templates/docs/contracts/
TEMPLATE.md
templates/hooks/
context-injector.py
loop-detector.py
pre-completion-check.py

Details

From the project README

Harness Engineering Framework

One-click initialization of a complete Harness Engineering framework in any project directory.

Based on insights from OpenAI (Codex), Anthropic (3-agent GAN architecture), and LangChain (self-verify loops), this skill sets up:

  • 3-agent architecture: Planner (spec), Generator (build), Evaluator (test)
  • Sprint contracts: Machine-verifiable "done" criteria before coding
  • Quality hooks: Loop detection, pre-completion checklist, context injection
  • Slash commands: /plan, /build, /qa, /sprint
  • Golden principles: 10 non-negotiable rules enforced across all agents

When to Use

  • Starting a new project and want structured AI-assisted development
  • Want to set up Plan-Build-Verify-Fix workflow in current project
  • User says "harness", "init harness", "setup framework", or similar

Initialization Process

Step 1: Gather Project Info

Before generating files, ask the user:

  1. Project name (or detect from current directory name)
  2. Tech stack (optional, e.g. "React + Node.js", "Python FastAPI", "Go microservice")
  3. Project type (web app, API service, CLI tool, library, etc.)

If the user provides a description with /harness <description>, extract the info from context.

Step 2: Generate Framework Files

Execute the scaffold script:

python3 {{SKILL_PATH}}/scripts/scaffold.py --project-name "<PROJECT_NAME>" --tech-stack "<TECH_STACK>" --project-type "<PROJECT_TYPE>" --target-dir "<CURRENT_PROJECT_DIR>"

This generates the following structure in the current project:

<project>/
  CLAUDE.md                        # Project map (<80 lines)
  .claude/
    agents/
      planner.md                   # Spec creation agent
      generator.md                 # Implementation agent
      evaluator.md                 # Testing/grading agent
      doc-gardener.md              # Doc freshness agent
    commands/
      plan.md                      # /plan command
      build.md                     # /build command
      qa.md                        # /qa command
      sprint.md                    # /sprint command
    hooks/
      loop-detector.py             # File edit loop detection
      pre-completion-check.py      # Task completion checklist
      context-injector.py          # Session context middleware
  docs/
    architecture.md                # System design
    golden-principles.md           # Non-negotiable rules
    sprint-workflow.md             # Sprint process
    contracts/
      TEMPLATE.md                  # Sprint contract template
    specs/                         # (populated by planner)
    plans/                         # (populated by planner)
Step 3: Configure Hooks

After generating files, merge hook configuration into the project's .claude/settings.json (or create it):

python3 {{SKILL_PATH}}/scripts/merge_settings.py --target-dir "<CURRENT_PROJECT_DIR>"

This adds hook definitions without overwriting existing settings.

Step 4: Verify Installation

Confirm all files were created:

ls -la CLAUDE.md .claude/agents/ .claude/commands/ .claude/hooks/ docs/

Report to the user what was created and how to start using it.

Usage After Initialization

CommandPurpose
/plan <description>Create a feature specification from 1-4 sentences
/buildBuild the most recent spec using sprint workflow
/qaRun evaluator against current code
/sprint <description>Full Plan-Build-Verify cycle from scratch

Key Principles

The framework enforces these rules (see docs/golden-principles.md after install):

  1. Spec before code - No implementation without a written spec
  2. Testable criteria - Every feature has machine-verifiable acceptance criteria
  3. Self-verify first - Generator must self-check before evaluator runs
  4. Loop awareness - Editing same file 5+ times triggers a stop-and-reassess
  5. Contract-driven - Sprint contracts define "done" before coding begins

Architecture

For full details, read the generated docs/architecture.md after installation. Key flow:

User Prompt → Planner (spec) → Generator + Evaluator negotiate contract
→ Generator builds → Evaluator tests → Fix loop (max 3x) → Complete

Comments

Markdown supported