hepha-skill

skill
Security Audit
Warn
Health Warn
  • No license — Repository has no license file
  • Description — Repository has a description
  • Active repo — Last push 0 days ago
  • Low visibility — Only 7 GitHub stars
Code Warn
  • Code scan incomplete — No supported source files were scanned during light audit
Permissions Pass
  • Permissions — No dangerous permissions requested
Purpose
This tool is a structured workflow prompt for AI coding assistants like Claude Code. It breaks down large software requirements into small, safe, and continuously shippable tasks through an autonomous iterative loop (Plan → Execute → Check → Review → Commit).

Security Assessment
Overall risk is rated as Low. The tool functions essentially as a structured system prompt or a set of instructions rather than an executable software application. The automated audit confirmed that it requests no dangerous system permissions. Additionally, no source code files were scanned by the automated tools, which indicates this is likely a text-based or Markdown-driven project rather than a compiled binary. As it appears to be purely a set of instructions for an AI agent, it does not inherently make unauthorized network requests, execute hidden shell commands, or contain hardcoded secrets.

Quality Assessment
The project is very new and currently has low community visibility with only 7 GitHub stars. However, it is actively maintained, with its most recent push occurring just today. While the automated scan flagged a missing license file, the README explicitly displays an MIT license badge, indicating standard open-source permissions. Given its current maturity level, community trust is still in the early stages, but the transparent documentation is a positive sign.

Verdict
Safe to use, though developers should treat it as a beta prompt template and review the provided AI instructions before integrating it into their workflow.
SUMMARY

A skill that turns large requirements into small, safe, continuously shippable tasks through autonomous iterative delivery loops.

README.md

Hepha

Hepha

English | 中文

Stars
License: MIT
Claude Compatible
OpenClaw Skill

Turn large requirements into small, safe, continuously shippable tasks — through autonomous iterative delivery loops.

Features · Quick Start · How It Works · Workflow Demo · Documentation · Changelog


⭐ Why Hepha?

If you've ever spent hours specifying a feature, watching an AI agent go off the rails, and then spending more time fixing the chaos than writing the code — Hepha is for you.

Hepha forces a disciplined loop: PLAN → EXECUTE → CHECK → REVIEW → COMMIT. Every task is validated before touching the codebase. Every commit is minimal and safe.

"Less talk, show me code." — Hepha's philosophy

What you get

  • 🚀 Autonomous delivery — One prompt, continuous commits until done
  • 🛡️ Risk-controlled — Each loop ships one minimal, validated task
  • 📊 Visible progress — Real-time task graph and progress bar
  • 🔍 Evidence-driven — Every commit requires checks + browser review
  • 🔄 Self-correcting — Auto-replans when blocked, asks only when truly necessary

Features

Feature What it does
Auto-Decomposition Breaks large requirements into validated task graphs with dependency tracking
Schema Validation Forces complete task definitions with required fields (id, title, state, depends_on, acceptance, risk, files_hint)
Research Decision Matrix Explicit rules: research only when truly needed (new lib, arch change, >2 options), skip for CRUD/bugfix/style
Progress Visualization Live progress bars, status tables, and task dependency graphs in Markdown
Two-layer Control Skill handles strategy; Rule enforces hard constraints and stop conditions
Deterministic Stop Policy Stops on repeated failures or no executable tasks; reports blockers clearly

Quick Start

# 1. Clone or copy the skill into your Claude Code/OpenClaw skills directory
cp -r skills/hepha ~/.claude/skills/

# 2. Activate Hepha mode with a single prompt
Enable hepha mode.
Run loop: plan -> execute -> check -> review -> commit.
Continue until backlog is complete.
Requirement: <paste your requirement here>

That's it. Hepha will:

  1. Analyze your requirement and auto-decompose it into a task graph
  2. Execute one task at a time through the validated loop
  3. Commit after each successful loop
  4. Stop when all tasks are done or a stop condition is hit

How It Works

flowchart LR
    U[User Requirement] --> S[Skill Engine]
    S --> P[Auto-Decomposition]
    P --> T[Task Graph + Schema Validation]
    T --> E[Execute One Task]
    E --> C[Check: lint/test/build]
    C --> R[Review: browser validation]
    R --> V{Pass?}
    V -- No --> E
    V -- Yes --> G[Commit]
    G --> M{More Tasks?}
    M -- Yes --> E
    M -- No --> D[Delivery Summary]

    V -- Blocked --> B[Auto-Replan]
    B --> P

The Loop: PLAN → EXECUTE → CHECK → REVIEW → COMMIT

1. PLAN

  • Auto-Decomposition: If no backlog exists, automatically break down requirements into tasks using patterns (CRUD, Authentication, UI Components, API Integration)
  • Schema Validation: Every task must have: id, title, state, depends_on, acceptance, risk, files_hint
  • Select Task: Pick from ready queue (all dependencies done)

2. RESEARCH

Research is ONLY required for:

  • ✅ New library/framework/tool
  • ✅ Architecture changes
  • ✅ Implementation uncertainty (>2 options)
  • ❌ NOT for: CRUD, bug fixes, style changes

3. EXECUTE

  • Keep changes focused on required files only
  • Avoid speculative refactors
  • Keep functions small and reusable

4. CHECK

Run all relevant project checks:

lint → tests → build/typecheck

Fix and retry until pass.

5. REVIEW (For UI/flow changes)

Use MCP browser tools or Playwright to validate:

  • Page load success
  • Key interaction path works
  • Expected state is visible

6. COMMIT

Commit only when:

  • ✅ checks passed
  • ✅ review passed
  • ✅ acceptance criteria met

Workflow Demo

Before & After

Without Hepha With Hepha
One big prompt, unpredictable output One prompt, structured autonomous loops
No visibility into progress Real-time task graph + progress bar
Large, risky commits Small, validated commits after each loop
Goes off rails easily Auto-replans when blocked
No evidence of quality Every commit has check + review evidence

Live Progress Example

Overall Progress: [████████░░] 80% (4/5 tasks complete)

Status Summary:
| Status        | Count | Tasks                            |
|---------------|-------|----------------------------------|
| ✅ Done        | 4     | TASK-001, 002, 004, 005          |
| 🔄 In Progress| 1     | TASK-003                         |
| ⏳ Todo        | 0     | -                                |
| 🚫 Blocked    | 0     | -                                |

Task Dependency Graph:
TASK-001 (✅) ──► TASK-002 (✅) ──► TASK-003 (🔄)
     │
     └──────────────► TASK-004 (✅)

Usage Example

# Prompt:
Enable hepha mode.
Run autonomous loops until complete.
Requirement: Implement user authentication with JWT.

The skill will:

  1. Auto-decompose into 4-6 tasks (e.g., TASK-001: DB schema, TASK-002: auth middleware, TASK-003: login API, TASK-004: frontend login form, TASK-005: JWT validation)
  2. Execute each task through the validated loop
  3. Commit after each successful loop
  4. Stop when complete or blocked

Project Structure

skills/hepha/
├── SKILL.md                           # Main skill definition (for Claude Code/OpenClaw)
├── references/                        # Documentation
│   ├── decomposition-patterns.md      # Task breakdown patterns
│   ├── planning_task-decomposition.md # Task schema reference
│   ├── progress-template.md           # Progress visualization guide
│   └── validation_quality-gates.md    # Quality gate definitions
└── templates/                         # Runtime file templates
    ├── backlog.md.template             # Task graph template
    ├── progress.md.template           # Progress log template
    └── decision-log.md.template        # Research log template

Runtime Artifacts

Hepha creates and maintains these files in your project's .hepha/ directory:

File Purpose
backlog.md Task graph with states, dependencies, and risk levels
progress.md Per-loop execution log with evidence and progress visualization
decision-log.md Research and technical decisions with trade-off analysis

Technical Approach

  • Two-layer control model
    • Skill handles strategy and execution orchestration
    • Rule enforces hard constraints and stop conditions
  • Small-batch delivery: Each loop handles one minimal sub-task — no "big-bang" refactors
  • Evidence-driven quality: Every loop includes verification output; commit only after check + review pass
  • Deterministic stop policy: Stop after repeated failures or no executable tasks; report blockers and current state

Scope and Non-goals

  • ✅ This is an execution protocol for autonomous coding
  • ✅ Optimizes continuous delivery speed under controlled risk
  • ❌ Does NOT replace product decisions when requirements conflict
  • ❌ Is NOT a full external workflow scheduler

Documentation


Changelog

v1.0.0 (2026-03-28)

  • Initial release
  • Auto-decomposition with task graph generation
  • PLAN → EXECUTE → CHECK → REVIEW → COMMIT loop
  • Schema validation for all tasks
  • Research decision matrix
  • Progress visualization with Markdown bars and dependency graphs
  • Runtime artifacts: backlog.md, progress.md, decision-log.md
  • Dual language support (English + 中文)

License

MIT

Hepha — Built for developers who believe in evidence over promises.

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