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PurrrrrFocus: Pomodoro Timer App - App Store Workflow Engine — Multi-Step Orchestration for Bun RapidPhoto: Pro Photo Editor App - App Store GitHub - DheerG/swarms: Achieve extraordinary results with claude code across a variety of tasks SPICE simulation → oscilloscope → verification with Claude Code — Lucas Gerads Show HN: VCoding – A 5 MB native Windows IDE with no dynamic dependencies Show HN: LLMs don't hallucinate because they're bad at math, it's the format GitHub - Agent-FM/agentfm-core: AgentFM is a peer-to-peer network that turns everyday computers into a decentralized AI supercomputer. AgentFM lets you run massive AI workloads directly across a global mesh of idle CPUs and GPUs. 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Every destination, simultaneously. No cloud middleman, no per-channel fees, no limits. GitHub - ocrbase-hq/ocrbase: 📄 PDF/IMG ->.MD/JSON Document OCR API for PaddleOCR and GLMOCR. Self-hostable. GitHub - impactjo/home-memory: MCP server that lets your AI assistant remember everything about your home. GitHub - Sets88/dbcls: DbCls is a powerful terminal database client that supports various databases GitHub - neptun2000/heor-agent-mcp GitHub - SeanFDZ/macmind: Single-layer transformer in HyperTalk for the classic Macintosh RollQuation: Math Puzzles - Apps on Google Play GitHub - dropbox/witchcraft Show HN: Agent-cache – Multi-tier LLM/tool/session caching for Valkey and Redis GitHub - opentalon/opentalon: OpenTalon is an open-source platform built from the ground up in Go as a robust alternative to OpenClaw LinkedIn™ 职位抓取工具 - Chrome 应用商店 GitHub - EdoardoBambini/Agent-Armor-Iaga: AI agents are getting tool access — shell, file system, databases, APIs, secrets. 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Supports all Whisper models, NVIDIA GPU (CUDA) acceleration, JSON/SRT/VTT output, SSE streaming, offline mode, and multi-arch (amd64, arm64). GitHub - yisding/reviewwiggum GitHub - MarwanAlsoltany/serrors: Structured errors for Go: sentinel hierarchies, typed data, custom formatting, and slog integration. GitHub - soatok/age-php GitHub - Luthiraa/markitme GitHub - stagas/rtdiff: realtime git diff gui and AI-assisted commits GitHub - tombedor/excalicharts GitHub - wh1le/excalidraw-edit: Open and edit .excalidraw files from the terminal. Offline, auto-saves to disk. MalExt Sentry - Malicious Extension Scanner - Chrome 应用商店 GitHub - syi0808/asciianimesvg: Generate animated ASCII art SVGs from text. CLI, Rust library, WASM, and web editor. GitHub - zaina-ml/ml_forge: A visual-based graph node editor for training computer vision models. GitHub - anakin87/llm-rl-environments-lil-course: 🌱 A little course on Reinforcement Learning Environments for evaluating and training Language Models GitHub - takaakit/superpowers-uml: Superpowers-UML modifies Superpowers to ensure a software development workflow in which AI agents design through UML modeling. AdriByte Studio - Sviluppo Web e Soluzioni Digitali GitHub - chouligi/angel-copilot: Your personalized Angel Investment Advisor Show HN: MoodSense AI (ML and FastAPI and Gradio, Deployed on Hugging Face) Moodsense Ai - a Hugging Face Space by aman179102 GitHub - agenteractai/lodmem: Level Of Detail Context Management for Agents GitHub - ostefani/subnetlens: A fast, concurrent network scanner with a TUI and plain-text CLI, built in Go. It discovers live hosts on your network, scans their open ports, resolves hostnames, and fingerprints operating systems—delivered. Cyber Pulse: Agentic Intel - Apps on Google Play Whisper API: Self-Hostable Speech to Text Transcription The Agent-Web Protocol Stack: A Research Thesis GitHub - msmarkgu/RelayFreeLLM: A restful API designed to route user prompts to various AI model providers. Show HN: Provepy – A Python decorator that proves your code using Lean and LLMs Show HN: Pardonned.com – A searchable database of US Pardons GitHub - patrickdappollonio/dux: Dux is a terminal UI that lets you run multiple AI coding agents side by side, each in its own git worktree, with full companion terminals, macros, commit generation, and a command palette that knows more tricks than you do. kMC Crystal Simulator Show HN: HyperFlow – A self-improving agent framework built on LangGraph GitHub - stef41/vibescore: 🎵 Grade your vibe-coded project. One command, instant letter grade across security, quality, dependencies, and testing. GitHub - stef41/lmscan: 🔍 Detect AI-generated text and fingerprint which LLM wrote it. Open-source GPTZero alternative. Zero dependencies, works offline. imgur.com GitHub - visionscaper/collabmem: Enabling long-term collaboration with Agentic AI - building up episodic and world model memory over time with in-context awareness 在 Steam 上购买 FriedrichAI: Offline AI 立省 10% GitHub - atripati/ark: AI Runtime Kernel — a context operating system for AI agents. Eliminates tool bloat, loads only what’s needed, and gives LLMs their reasoning space back. GitHub - nowork-studio/toprank: Open-source Claude Code skills for SEO, SEM, Google Ads GitHub - tacomanator/sash: Lightweight macOS menu bar app for reliably cycling through windows of the current application. Appents | Social Media Management for Product-First Teams GitHub - pnhoang/youtube-spam-blocker: Automatically detects and hides spam messages in YouTube Live chat. Set rate limits, keyword filters, and block repeat offenders. GitHub - decisionnode/DecisionNode: CLI + Local MCP - A shared structured memory store across Claude Code, Cursor, Windsurf, Antigravity, and every MCP client. Semantically queryable. GitHub - AvaCodeSolutions/django-email-learning: An open source Django app for creating email-based learning platforms with IMAP integration and React frontend components. The $100K Gap in Kubernetes Security Tooling Function Calling Harness: From 6.75% to 100%
GitHub - the-open-engine/zeroshot: Your autonomous engineering team in a CLI. The agent loop produces senior-level code that you can actually trust in prod because of non-negotiable feedback from independent reviewers. Supports Claude Code, OpenAI Codex, OpenCode, and Gemini CLI with trivial setup.
covibes · 2026-06-23 · via Hacker News: Show HN

🎉 New in v5.4: Now supports OpenCode CLI! Use Claude, Codex, Gemini, or OpenCode as your AI provider. Also supports GitHub, GitLab, Jira, and Azure DevOps as issue backends. See Providers and Multi-Platform Issue Support.

npm install -g @the-open-engine/zeroshot

Demo
Demo (100x speed, 90-minute run, 5 iterations to approval)

CI npm version License: MIT Node 18+ Platform: Linux | macOS

Discord

Zeroshot is an open-source AI coding agent orchestration CLI that runs multi-agent workflows to autonomously implement, review, test, and verify code changes.

It runs a planner, an implementer, and independent validators in isolated environments, looping until changes are verified or rejected with actionable, reproducible failures.

Built for tasks where correctness matters more than speed.

How It Works

  • Plan: translate a task into concrete acceptance criteria
  • Implement: make changes in an isolated workspace (local, worktree, or Docker)
  • Validate: run automated checks with independent validators
  • Iterate: repeat until verified, or return actionable failures
  • Resume: crash-safe state persisted for recovery

Quick Start

zeroshot run 123                    # GitHub issue number
zeroshot run feature.md             # Markdown file
zeroshot run "Add dark mode"        # Inline text

Or describe a complex task inline:

zeroshot run "Add optimistic locking with automatic retry: when updating a user,
retry with exponential backoff up to 3 times, merge non-conflicting field changes,
and surface conflicts with details. Handle the ABA problem where version goes A->B->A."

Why Not Just Use a Single AI Agent?

Approach Writes Code Runs Tests Blind Validation Iterates Until Verified
Chat-based assistant ⚠️
Single coding agent ⚠️ ⚠️
Zeroshot (multi-agent)

Use Cases

  • Autonomous AI code refactoring
  • AI-powered pull request automation
  • Automated bug fixing with validation
  • Multi-agent code generation for software engineering
  • Agentic coding workflows with blind validation

Who Is This For?

  • Senior engineers who care about correctness and reproducibility
  • Teams automating PR workflows and code review gates
  • Infra/platform teams standardizing agentic workflows
  • Open-source maintainers working through issue backlogs
  • AI power users who want verification, not vibes

Install and Requirements

Platforms: Linux, macOS. Windows (native/WSL) is deferred while we harden reliability and multi-provider correctness.

npm install -g @the-open-engine/zeroshot

Requires: Node 18+, at least one provider CLI (Claude Code, Codex, Gemini, Opencode).

# Install one or more providers
npm i -g @anthropic-ai/claude-code
npm i -g @openai/codex
npm i -g @google/gemini-cli
# Opencode: see https://opencode.ai

# Authenticate with the provider CLI
claude login        # Claude
codex login         # Codex
gemini auth login   # Gemini
opencode auth login # Opencode

# GitHub auth (for issue numbers)
gh auth login

Providers

Zeroshot shells out to provider CLIs. Pick a default and override per run:

zeroshot providers
zeroshot providers set-default codex
zeroshot run 123 --provider gemini

See docs/providers.md for setup, model levels, and Docker mounts. See docs/provider-cli-helper.md for the strict TypeScript provider helper, the zeroshot-agent-provider JSON executable contract, and the boundary with Orchestra.

Why Multiple Agents?

Single-agent sessions degrade. Context gets buried under thousands of tokens. The model optimizes for "done" over "correct."

Zeroshot fixes this with isolated agents that check each other's work. Validators can't lie about code they didn't write. Fail the check? Fix and retry until it actually works.

What Makes It Different

  • Blind validation - Validators never see the worker's context or code history
  • Repeatable workflows - Task complexity determines agent count and model selection
  • Accept/reject loop - Rejections include actionable findings, not vague complaints
  • Crash recovery - All state persisted to SQLite; resume anytime
  • Isolation modes - None, git worktree, or Docker container
  • Cost control - Model ceilings prevent runaway API spend

Required Handoff Quality Gates

Zeroshot owns a tool-neutral handoff contract for --pr and --ship flows. It does not know which tool produced a gate. Repos configure required gates, validators publish matching qualityGates evidence, and the git-pusher trigger refuses to wake until every configured gate has fresh passing evidence after IMPLEMENTATION_READY.

Gate config can come from run options or repo settings:

{
  "ship": {
    "requiredQualityGates": [
      {
        "id": "repo-quality",
        "scope": "repo",
        "description": "Repository quality gate",
        "command": "repo-quality --changed --json"
      }
    ]
  }
}

The id and optional scope are generic. A repo may bind repo-quality to any local quality command, a CI status command, or another quality command outside Zeroshot. Validators receive the configured gate list and must publish entries with status, completedAt or timestamp, and evidence.command, evidence.exitCode, and string evidence.output. Failing or unavailable commands mean approved: false with gate status FAIL or UNAVAILABLE.

The pusher fails closed before commit, push, PR creation, or merge when a configured gate is missing, failing, unavailable, stale, older than IMPLEMENTATION_READY, or lacks usable evidence. If no requiredQualityGates are configured, Zeroshot preserves its existing validator consensus behavior.

When to Use Zeroshot

Zeroshot performs best when tasks have clear acceptance criteria.

Scenario Use Why
Add rate limiting (sliding window, per-IP, 429) Yes Clear requirements
Refactor auth to JWT Yes Defined end state
Fix login bug Yes Success is measurable
Fix 2410 lint violations Yes Clear completion criteria
Make the app faster No Needs exploration first
Improve the codebase No No acceptance criteria
Figure out flaky tests No Exploratory

Rule of thumb: if you cannot describe what "done" means, validators cannot verify it.

Command Overview

# Run
zeroshot run 123                      # GitHub issue
zeroshot run feature.md               # Markdown file
zeroshot run "Add dark mode"          # Inline text

# Isolation
zeroshot run 123 --worktree       # git worktree
zeroshot run 123 --docker         # container

# Automation (--ship implies --pr implies --worktree)
zeroshot run 123 --pr             # worktree + create PR
zeroshot run 123 --ship           # PR + auto-merge on approval

# Background mode
zeroshot run 123 -d
zeroshot run 123 --ship -d

# Control
zeroshot list
zeroshot status <id>
zeroshot logs <id> -f
zeroshot resume <id>
zeroshot stop <id>
zeroshot kill <id>

# Providers
zeroshot providers
zeroshot providers set-default codex

# Agent library
zeroshot agents list
zeroshot agents show <name>

# Maintenance
zeroshot clean
zeroshot purge

Multi-Platform Issue Support

Zeroshot works with GitHub, GitLab, Jira, and Azure DevOps. Just paste the issue URL or key. When working in a git repository, zeroshot automatically detects the issue provider from your git remote URL. No configuration needed!

# GitHub
zeroshot run 123
zeroshot run https://github.com/org/repo/issues/123

# GitLab (cloud and self-hosted)
zeroshot run https://gitlab.com/org/repo/-/issues/456
zeroshot run https://gitlab.mycompany.com/org/repo/-/issues/789

# Jira
zeroshot run PROJ-789
zeroshot run https://company.atlassian.net/browse/PROJ-789

# Azure DevOps
zeroshot run https://dev.azure.com/org/project/_workitems/edit/999

Requires: CLI tools (gh, glab, jira, or az) for the platform you use. See issue-providers README for setup and self-hosted instances.

Important for --pr mode: Run zeroshot from the target repository directory. PRs are created on the git remote of your current directory. If you run from a different repo, zeroshot will warn you and skip the "Closes #X" reference (the PR is still created, but won't auto-close the issue).

Architecture

Zeroshot is a message-driven coordination layer with smart defaults.

  • The conductor classifies tasks by complexity and type.
  • A workflow template selects agents and validators.
  • Agents publish results to a SQLite ledger.
  • Validators approve or reject with specific findings.
  • Rejections route back to the worker for fixes.
                                ┌─────────────────┐
                                │      TASK       │
                                └────────┬────────┘
                                         │
                                         ▼
                ┌────────────────────────────────────────────┐
                │                 CONDUCTOR                  │
                │     Complexity × TaskType → Workflow       │
                └────────────────────────┬───────────────────┘
                                         │
           ┌─────────────────────────────┼─────────────────────────────┐
           │                             │                             │
           ▼                             ▼                             ▼
     ┌───────────┐                ┌───────────┐                ┌───────────┐
     │  TRIVIAL  │                │  SIMPLE   │                │ STANDARD+ │
     │  1 agent  │──────────▶     │  worker   │                │ planner   │
     │ (level1)  │  COMPLETE      │ + 1 valid.│                │ + worker  │
     │ no valid. │                └─────┬─────┘                │ + 3-5 val.│
     └───────────┘                      │                      └─────┬─────┘
                                        ▼                            │
                                 ┌─────────────┐                     ▼
                             ┌──▶│   WORKER    │             ┌─────────────┐
                             │   └──────┬──────┘             │   PLANNER   │
                             │          │                    └──────┬──────┘
                             │          ▼                           │
                             │   ┌─────────────────────┐            ▼
                             │   │ ✓ validator         │     ┌─────────────┐
                             │   │   (generic check)   │ ┌──▶│   WORKER    │
                             │   └──────────┬──────────┘ │   └──────┬──────┘
                             │       REJECT │ ALL OK     │          │
                             └──────────────┘     │      │          ▼
                                                  │      │   ┌──────────────────────┐
                                                  │      │   │ ✓ requirements       │
                                                  │      │   │ ✓ code (STANDARD+)   │
                                                  │      │   │ ✓ security (CRIT)    │
                                                  │      │   │ ✓ tester (CRIT)      │
                                                  │      │   │ ✓ adversarial        │
                                                  │      │   │   (real execution)   │
                                                  │      │   └──────────┬───────────┘
                                                  │      │       REJECT │ ALL OK
                                                  │      └──────────────┘     │
                                                  ▼                           ▼
     ┌─────────────────────────────────────────────────────────────────────────────┐
     │                                COMPLETE                                     │
     └─────────────────────────────────────────────────────────────────────────────┘

Complexity Model

Task Complexity Agents Validators
Fix typo in README TRIVIAL 1 None
Add dark mode toggle SIMPLE 2 Generic validator
Refactor auth system STANDARD 4 Requirements, code
Implement payment flow CRITICAL 7 Requirements, code, security, tester, adversarial

Model Selection by Complexity

Complexity Planner Worker Validators
TRIVIAL - level1 -
SIMPLE - level2 1 (level2)
STANDARD level2 level2 2 (level2)
CRITICAL level3 level2 5 (level2)

Levels map to provider-specific models. Configure with zeroshot providers setup <provider> or settings.providerSettings. (Legacy maxModel applies to Claude only.)

Custom Workflows (Framework Mode)

Zeroshot is message-driven, so you can define any agent topology.

  • Expert panels: parallel specialists -> aggregator -> decision
  • Staged gates: sequential validators, each with veto power
  • Hierarchical: supervisor dynamically spawns workers
  • Dynamic: conductor adds agents mid-execution

Coordination primitives:

  • Message bus (pub/sub topics)
  • Triggers (wake agents on conditions)
  • Ledger (SQLite, crash recovery)
  • Dynamic spawning (CLUSTER_OPERATIONS)

Creating Custom Clusters with a Provider CLI

Start your provider CLI and describe your cluster:

Create a zeroshot cluster config for security-critical features:

1. Implementation agent (level2) implements the feature
2. FOUR parallel validators:
   - Security validator: OWASP checks, SQL injection, XSS, CSRF
   - Performance validator: No N+1 queries, proper indexing
   - Privacy validator: GDPR compliance, data minimization
   - Code reviewer: General code quality

3. ALL validators must approve before merge
4. If ANY validator rejects, implementation agent fixes and resubmits
5. Use level3 for security validator (highest stakes)

Look at cluster-templates/base-templates/full-workflow.json
and create a similar cluster. Save to cluster-templates/security-review.json

Built-in validation checks for missing triggers, deadlocks, and invalid type wiring before running.

See CLAUDE.md for the cluster schema and examples.

Crash Recovery

All state is persisted in the SQLite ledger. You can resume at any time:

zeroshot resume cluster-bold-panther

Isolation Modes

Git Worktree (Default for --pr/--ship)

zeroshot run 123 --worktree

Lightweight isolation using git worktree. Creates a separate working directory with its own branch. Auto-enabled with --pr and --ship.

Docker Container

zeroshot run 123 --docker

Full isolation in a fresh container. Your workspace stays untouched. Useful for risky experiments or parallel runs.

When to Use Which

Scenario Recommended
Quick task, review changes yourself No isolation (default)
PR workflow, code review --worktree or --pr
Risky experiment, might break things --docker
Running multiple tasks in parallel --docker
Full automation, no review needed --ship

Default behavior: Agents modify files only; they do not commit or push unless using an isolation mode that explicitly allows it.

Docker Credential Mounts

When using --docker, zeroshot mounts credential directories so agents can access provider CLIs and tools like AWS, Azure, and kubectl.

Default mounts: gh, git, ssh (GitHub CLI, git config, SSH keys)

Available presets: gh, git, ssh, aws, azure, kube, terraform, gcloud, claude, codex, gemini

# Configure via settings (persistent)
zeroshot settings set dockerMounts '["gh", "git", "ssh", "aws", "azure"]'

# View current config
zeroshot settings get dockerMounts

# Per-run override
zeroshot run 123 --docker --mount ~/.aws:/root/.aws:ro

# Provider credentials
zeroshot run 123 --docker --mount ~/.config/codex:/home/node/.config/codex:ro
zeroshot run 123 --docker --mount ~/.config/gemini:/home/node/.config/gemini:ro

# Disable all mounts
zeroshot run 123 --docker --no-mounts

# CI: env var override
ZEROSHOT_DOCKER_MOUNTS='["aws","azure"]' zeroshot run 123 --docker

See docs/providers.md for provider CLI setup and mount details.

Custom mounts (mix presets with explicit paths):

zeroshot settings set dockerMounts '[
  "gh",
  "git",
  {"host": "~/.myconfig", "container": "$HOME/.myconfig", "readonly": true}
]'

Container home: Presets use $HOME placeholder. Default: /root. Override with:

zeroshot settings set dockerContainerHome '/home/node'
# Or per-run:
zeroshot run 123 --docker --container-home /home/node

Env var passthrough: Presets auto-pass related env vars (for example, aws -> AWS_REGION, AWS_PROFILE). Add custom:

zeroshot settings set dockerEnvPassthrough '["MY_API_KEY", "TF_VAR_*"]'

Resources

  • CLAUDE.md - Architecture, cluster config schema, agent primitives
  • docs/providers.md - Provider setup, model levels, and Docker mounts
  • docs/context-management.md - Context selection, context packs, and state snapshots
  • Discord - Support and community
  • zeroshot export <id> - Export conversation to markdown
  • sqlite3 ~/.zeroshot/*.db - Direct ledger access for debugging
Troubleshooting
Issue Fix
claude: command not found npm i -g @anthropic-ai/claude-code && claude auth login
codex: command not found npm i -g @openai/codex && codex login
gemini: command not found npm i -g @google/gemini-cli && gemini auth login
gh: command not found Install GitHub CLI
--docker fails Docker must be running: docker ps to verify
Cluster stuck zeroshot resume <id> to continue
Agent keeps failing Check zeroshot logs <id> for actual error
zeroshot: command not found npm install -g @the-open-engine/zeroshot
Agents misbehave /analyze-cluster-postmortem <id> in Claude Code (creates issue if fix is generalizable)

Contributing

See CONTRIBUTING.md for development setup and guidelines.

Please read CODE_OF_CONDUCT.md before participating.

For security issues, see SECURITY.md.

TUI

The TUI is not included in this release. Use zeroshot logs -f, zeroshot logs -w, zeroshot list, and zeroshot status <id> for monitoring.


MIT - The Open Engine Company

Built on Claude Code by Anthropic.