OpenKoi

Stop babysitting your AI. OpenKoi iterates until the code is right.

AI coding tools generate a first draft and leave you to fix it. You review, correct, re-prompt — and become the AI's QA department. OpenKoi is different. It follows a Plan-Execute-Evaluate-Refine loop, iterating on its own output until results meet your quality standards. The agent is its own reviewer.

Ships as a single static binary. Zero runtime dependencies. Works with any model.

Three Steps

# 1. Install
cargo install openkoi
# or
curl -fsSL https://openkoi.ai/install.sh | sh

# 2. Run — OpenKoi finds your API keys automatically
openkoi "Refactor the auth module to use JWT tokens"

# 3. Ship — it iterates until the code passes its own review
#    [PLAN] Analyzing src/auth/ — 4 files, 312 lines
#    [EXEC] Rewriting token.rs, middleware.rs, handlers.rs
#    [EVAL] correctness=9.2 safety=9.5 style=8.8
#    [REFN] Style below 9.0 — tightening error types
#    [EVAL] correctness=9.4 safety=9.5 style=9.3
#    ✓ Done. 3 iterations. 4 files changed.

No config file needed. No setup wizard. OpenKoi detects your API keys from environment variables, existing CLI tools, and local model servers — and picks the best available model.

What Changes

Features

• Self-iteration — Plan, execute, evaluate, refine. The agent is its own reviewer.
• 8+ providers — Anthropic, OpenAI, Google, Ollama, AWS Bedrock, Groq, DeepSeek, Moonshot/Kimi, and any OpenAI-compatible endpoint.
• Dynamic model discovery — Probes provider APIs for available models, caches results locally. Fuzzy validation with "did you mean?" suggestions for typos.
• Role-based models — Assign different models to executor, evaluator, planner, and embedder roles. Auto-resolves a small/fast model for cost-sensitive internal tasks.
• Automatic retry — Rate limits, server errors, and timeouts are retried with exponential backoff and jitter. Context overflow is detected and handled separately.
• Real-time progress — Structured progress output on stderr showing plan, iterations, scores, tool calls, and costs. Suppress with --quiet.
• Live task monitoring — openkoi status --live polls the running task every second with a progress bar, score, cost, and recent history.
• Task state persistence — Current task state written to ~/.openkoi/state/current-task.json; completed tasks appended to task-history.jsonl with auto-rotation.
• HTTP API — Localhost REST API (port 9742) for submitting tasks, querying status, and reading cost data. Optional Bearer token auth.
• Webhooks — Fire HTTP callbacks on task.complete, task.failed, and budget.warning events.
• Smart truncation — Tool outputs exceeding 2000 lines or 50KB are truncated with the full output saved to ~/.openkoi/tool-output/.
• Context overflow handling — Detects overflow errors from all major providers and prunes context instead of failing.
• Persistent memory — SQLite + vector search. Learnings persist across sessions.
• Pattern mining — Observes your usage, proposes new skills to automate recurring workflows.
• Skill system — OpenClaw-compatible .SKILL.md format. Write once, use with any provider.
• Rich messaging — Slack, Discord, and Telegram integrations send structured task results with fields, colors, and thread support.
• 3-tier plugins — MCP (external tools), WASM (sandboxed), Rhai (scripting).
• 10 integrations — Slack, Discord, MS Teams, GitHub, Jira, Linear, Notion, Google Docs, Telegram, Email.
• TUI dashboard — Real-time view of tasks, costs, learnings, plugins, and config.
• Soul system — Optional personality that evolves with your interaction patterns.

CLI

openkoi "task"              # Run a task (default 3 iterations)
openkoi chat                # Interactive REPL
openkoi learn               # Review proposed skills (interactive picker)
openkoi status              # Show costs, memory, active models
openkoi status --live       # Watch the running task in real-time
openkoi status --costs      # Show cost tracking summary
openkoi doctor              # Run diagnostics
openkoi connect             # Interactive picker: choose provider or integration
openkoi connect copilot     # Login to GitHub Copilot (direct)
openkoi connect chatgpt     # Login to ChatGPT Plus/Pro (direct)
openkoi disconnect          # Interactive picker: choose from connected providers
openkoi disconnect copilot  # Remove stored credentials (direct)
openkoi daemon              # Interactive picker: start/stop/status
openkoi export              # Interactive picker: choose target and format
openkoi export all          # Export all data as JSON (direct)
openkoi -m ?                # Interactive model picker
openkoi --select-model      # Same as -m ?
openkoi update              # Self-update

Task flags

openkoi "task" -i 5               # Set max iterations (default 3)
openkoi "task" --quality 0.9      # Set quality threshold (default 0.8)
openkoi "task" --quiet            # Suppress progress output; only emit final result
openkoi "task" -m claude-sonnet-4 # Use a specific model

All commands that accept an argument also work without one — omitting the argument shows an interactive selection menu. Explicit arguments still work exactly as before.

Providers

Subscription-based (OAuth login, free with your existing plan)

Use openkoi connect to authenticate via device-code flow. No API key needed.

Tokens are stored in ~/.openkoi/auth.json and refreshed automatically.

API key providers

Set an environment variable or paste a key when prompted during openkoi init.

API keys are saved to ~/.openkoi/credentials/<provider>.key (owner-only permissions).

Local

Credential Discovery

OpenKoi auto-discovers credentials in this order:

1. Environment variables — ANTHROPIC_API_KEY, OPENAI_API_KEY, GOOGLE_API_KEY, etc.
2. OAuth store — GitHub Copilot, ChatGPT tokens from openkoi connect
3. External CLIs — Claude CLI (~/.claude/.credentials.json), Qwen CLI
4. macOS Keychain — Claude Code credentials (macOS only)
5. Saved credentials — ~/.openkoi/credentials/*.key
6. Local probes — Ollama at localhost:11434

Connect and Disconnect

# Interactive picker (shows all providers and integrations)
openkoi connect

# Or specify directly
openkoi connect copilot     # GitHub Copilot
openkoi connect chatgpt     # ChatGPT Plus/Pro

# Interactive disconnect (shows only currently connected providers)
openkoi disconnect

# Or specify directly
openkoi disconnect copilot
openkoi disconnect chatgpt
openkoi disconnect anthropic   # Remove saved API key
openkoi disconnect all         # Remove all OAuth tokens

# Show connection status
openkoi connect status

HTTP API

The daemon exposes a localhost REST API on port 9742 for external tools, scripts, and web UIs.

# Submit a task
curl -X POST http://localhost:9742/api/v1/tasks \
  -H "Content-Type: application/json" \
  -d '{"description": "Fix the login bug", "max_iterations": 5}'

# Check status
curl http://localhost:9742/api/v1/status

Configure in config.toml:

[api]
enabled = true
port = 9742
token = "your-secret-token"  # Optional Bearer auth

[api.webhooks]
on_task_complete = "https://example.com/hooks/complete"
on_task_failed = "https://example.com/hooks/failed"
on_budget_warning = "https://example.com/hooks/budget"

Architecture

              ┌─────────────────┐
              │   Orchestrator   │
              └────────┬────────┘
       ┌───────┬───────┼───────┬──────────┐
       ▼       ▼       ▼       ▼          ▼
   Executor Evaluator Learner Pattern   Integrations
       │                     Miner
       ▼
     Tools (MCP / WASM / Rhai)

Supported platforms: Linux (x86_64, ARM64) and macOS (Intel, Apple Silicon). Built with Rust + Tokio. < 10ms startup, ~5MB idle memory, ~20MB binary.

Skills

Skills are markdown files (SKILL.md) with YAML frontmatter that teach OpenKoi how to handle specific tasks. They use the same format as OpenClaw, so skills are portable between tools.

How skills work

OpenKoi loads skills from multiple sources in precedence order:

When you run a task, the skill selector ranks eligible skills by semantic similarity and historical effectiveness, then injects the most relevant ones into the prompt. You don't need to specify which skill to use — OpenKoi picks automatically.

Bundled skills

These ship with the binary and are always available:

Writing a custom skill

Create a directory with a SKILL.md file:

mkdir -p .agents/skills/my-skill

---
name: my-skill
description: Enforces our team's API conventions.
metadata:
  categories: ["api", "code"]
---

# My Skill

When building API endpoints for this project:

- Use snake_case for all field names
- Return 404 with `{"error": "not_found"}` for missing resources
- Always include `X-Request-Id` header in responses
- Validate all path parameters before database queries

Place it in .agents/skills/ for project-specific skills, or ~/.openkoi/skills/user/ for global skills. OpenKoi picks it up automatically on the next run.

Example: self-iterate

The self-iterate skill is how OpenKoi works on its own codebase. When a task targets the OpenKoi source tree, the skill selector activates it automatically based on category matching (self-improvement, rust, code, refactor).

It enforces architectural invariants that must never be violated:

• Single binary — everything embeds via include_str!, no runtime file dependencies
• Zero-dependency crypto — SHA-256 and base64 are hand-rolled, only getrandom for CSPRNG
• Provider parity — all providers implement the same ModelProvider trait
• Iteration safety — circuit breakers (token budget, time budget, max iterations) cannot be weakened
• Atomic writes — all credential/config files use write-to-temp-then-rename

It also defines hard boundaries on recursive self-improvement: OpenKoi can improve its own skills, providers, and memory system, but cannot disable its own safety circuit breakers or bypass evaluation.

Evaluator skills

Evaluator skills define how OpenKoi judges its own output. They specify scoring dimensions and rubrics:

---
name: my-evaluator
kind: evaluator
description: Evaluates database migrations for safety.
metadata:
  categories: ["database", "migration"]
  dimensions:
    - { name: reversibility, weight: 0.4 }
    - { name: data_safety, weight: 0.35 }
    - { name: performance, weight: 0.25 }
---

# Database Migration Evaluator

## Reversibility (40%)
- Is there a matching down migration?
- Can the migration be rolled back without data loss?
...

Place evaluator skills in .agents/evaluators/ (project) or ~/.openkoi/evaluators/user/ (global).

Managing skills

openkoi learn               # Review pattern-proposed skills
openkoi learn --install     # Install a managed skill
openkoi status              # See active skills and effectiveness scores

OpenKoi's pattern miner watches your usage and proposes new skills when it detects recurring workflows. Run openkoi learn to review and approve them.

Environment

All paths default to ~/.openkoi/ (config) and ~/.local/share/openkoi/ (data). Set OPENKOI_HOME to relocate everything under a single directory:

export OPENKOI_HOME=/tmp/openkoi-test
openkoi status   # config at /tmp/openkoi-test/, data at /tmp/openkoi-test/data/

Install

# Via Cargo
cargo install openkoi

# Via shell installer
curl -fsSL https://openkoi.ai/install.sh | sh

Full documentation at openkoi.ai.

License

MIT