Token-Efficient AI Agent Intelligence
Microkernel AI Agent — same budget, have your Agent do more, do it better.
Smart routing, persistent memory, secure sandbox, plus built-in search and local embeddings.
- Read moreClaw-SWE-Bench released 📊 2026-06-10
A Benchmark for Evaluating OpenClaw-style Agent Harnesses on Coding Tasks.
- Read moreGitHub stars surpassed 3,000 🎉 2026-06-05
From 1,000 to 3,000 in under three weeks — thank you to everyone who starred, contributed, and shared. Onward.
- Read moreOpenSquilla 0.3.1 maintenance release 2026-06-03
A 0.3 maintenance release that makes day-to-day use less fragile: chat rendering, Slack setup, media handoffs, and provider validation.
See It in Action
Quick demos showing how OpenSquilla solves real workflows
Quickstart
Four paths to get started — pick the one that fits you
The recommended path on Windows, macOS, and Linux. uv installs OpenSquilla into its own isolated environment and manages its own Python — no system Python required. This path installs published releases only.
Install uv
Skip if uv --version already works.
$ curl -LsSf https://astral.sh/uv/install.sh | sh $ . "$HOME/.local/bin/env"
Install OpenSquilla
The same command on every platform.
$ uv tool install --python 3.12 "opensquilla[recommended] @ https://github.com/opensquilla/opensquilla/releases/download/v0.3.1/opensquilla-0.3.1-py3-none-any.whl"
Installs the OpenSquilla wheel from the release URL, then lets uv download the dependencies declared by the selected extras. The default recommended extra includes SquillaRouter runtime dependencies (ONNX Runtime, LightGBM, NumPy, tokenizers).
Configure and run
# Interactive onboarding wizard $ opensquilla onboard # Start ASGI server $ opensquilla gateway run
If opensquilla is not found right after a fresh uv install, open a new terminal or re-run the PATH line from step 1.
Wheel URLs are versioned by design — installers validate the version in the filename. The command above pins to v0.3.1.
Deploy Once, Reach Everywhere 3
Configure one Agent, serve users across multiple channels
Every Token Spent Where It Matters
OpenSquilla makes your Agent spend less, remember more, and run safer.
Cost Optimization
Multiple strategies coordinated to maximize every Token
MetaSkills Protocol
A meta-protocol that tells the Agent how to retrieve, filter, compose — and even evolve — skills at scale
Human-Like Memory
Four-tier cognitive architecture — gets smarter the more you use it
Security Sandbox
Let your Agent take action — without fearing what it might do
Microkernel: Tiny Core, Vast Ecosystem
Inspired by OS microkernels — the core engine does the minimum: orchestration and state management. Everything else runs as plugins in "user space". Switch LLM providers? Implement a Protocol. Add new tools? 5 lines of code. Plugin crashes don't affect the core; core upgrades don't break plugins.
Same Budget, Higher Intelligence Density
Side-by-side comparison with peer open-source Agent frameworks4
| Dimension | OpenSquilla | OpenClaw | Hermes Agent |
|---|---|---|---|
| 🏗️Architecture | ✅ Microkernel with 5-layer separation, ultra-compact core orchestrator (~100 lines), all capabilities pluggable, auto-skip + rollback on errors | ⚠️ Mature plugin ecosystem (dozens of extensions), clean boundaries but more layers | ❌ Massive monolithic sync main loop (thousands of lines), all logic tightly coupled |
| 💰Cost Optimization | ✅ ML routing + reasoning depth tiers + prompt cache isolation + on-demand skills — multi-strategy savings of 60-80% | ⚠️ Config-pinned primary + fallback chain, no content-aware selection | ⚠️ Crude keyword + length heuristics, single routing strategy only |
| 🪄MetaSkills Protocol | ✅ Composable workflows + meta-skill-creator for self-authoring + 10+ bundled & N+ community Skills auto-retrieved + Dream Mode distills usage into new candidates while idle | ⚠️ Prompt-driven skill chains, no meta-protocol layer, no self-evolution; new workflows live as docs, not first-class runtime objects | ❌ No reusable workflow abstraction — multi-step work is re-prompted from scratch every session |
| 💾Memory System | ✅ Vector + keyword + dedup + temporal decay + hot memory promotion + auto schema migration | ⚠️ Has decay / promotion / diversity reranking, but lacks four-tier cognitive structure & Memory Dream consolidation | ⚠️ Keyword-only search, no vector semantics, requires external integration for semantic memory |
| 🛡️Security Sandbox | ✅ No Docker dependency — syscall-level CPU/memory/time isolation + 3-tier network control. Fits in serverless | ⚠️ Docker optional with OpenShell as a lighter alternative, still heavier than syscall-level isolation | ✅ Dangerous command approval + 6 execution environments (local/Docker/SSH etc) |
| 💰Cost Tracking | ✅ Actual cost per call out of the box, quota hooks for auto-throttling on overspend | ✅ Built-in pricing table, cost written to session metadata | ✅ Input/output/cache-read/cache-write/reasoning tokens tracked separately |
| 📊Observability | ✅ Decision logs store hashes, not raw text (compliance-friendly), every pipeline stage instrumented | ✅ Native OpenTelemetry (as plugin), plug-and-play with Prometheus/Grafana | ⚠️ SQLite session table + call counter, basic level |
| 🧩Extension DX | ✅ 5-line duck-typed class is a valid plugin — no base class, no SDK package, no manifest | ⚠️ Implement interface in plugin-sdk + write manifest file | ⚠️ Tools auto-register on import (implicit side effects) |
Who Benefits Most from OpenSquilla?
These scenarios get the highest ROI
Free Tokens, Zero-Cost Trial
OpenSquilla is fully open source — pull from GitHub and self-host anytime.
But running LLMs still costs Tokens. We're giving you a starting Token credit so you can verify "OpenSquilla saves 60-80%" with zero risk.
10 seconds to fill out, no credit card required.