@Yuancheng: ➤ 最近还是不断有新的 Agent Harness 思路和实践在出现。 这两天看到 **OpenSquilla**,一个开源、能本地托管的 AI Agent。 ① 它有智能模型路由——同样的任务,token 成本比 OpenClaw 省 …

X AI KOLs Timeline 工具

摘要

OpenSquilla 是一个开源、可本地托管的 AI Agent,具有智能模型路由功能,可在不同模型间分配任务以节省 token 成本,并引入 MetaSkill 机制让 Agent 自动组织技能。

➤ 最近还是不断有新的 Agent Harness 思路和实践在出现。 这两天看到 **OpenSquilla**,一个开源、能本地托管的 AI Agent。 ① 它有智能模型路由——同样的任务,token 成本比 OpenClaw 省 60-80%,跑任务时还有个「老虎机」动画告诉你这一单省了多少钱。 路由省的不只是钱:现在各家模型各有所长、价格也不一样,benchmark 高低跟具体任务上的表现还常常对不上。 与其死磕单一最强模型,不如按任务把活派给最合适的那个——它真正在优化的,是「每块钱 token 换回多少智能」。 ② 刚发布 MetaSkill。简单说,它是「Skill 的 Skill」——一份告诉模型怎么检索、筛选、组合原子 Skill 的元 markdown。 因为单个 Skill 只干一件事,搜索归搜索,文档归文档。用户自己当调度员,脑子里一直装着下一步该使唤哪个,Skill 一多就会手忙脚乱。 MetaSkill 接管了这个「项目经理」的角色——由它来安排哪些步骤可以并行、哪些只能串行,让 Agent 学会自己组织技能。 ③ 还有 meta-skill-creator:一句话需求,自动合成一个新的 meta-skill,手写 30 分钟的活压到 3 分钟。等于是 Agent 自己造技能。 ➤ Why now?三件事撞到了一起:模型已经听得懂复杂的多步骤编排指令;社区 Skill 在爆发式增长,多到必须有个更高的抽象层来筛;大模型在线 trial-and-error 依然太贵,得把优化前置到 Skill 组织层。 这三条线指向同一点——Agent 要解决的问题,正在从「会不会调用工具」变成「会不会组织工具」。 **➤ 更深一层:**Harness 这层会不会只是个过渡概念、迟早被更强的模型吃掉? 我倒不这么看——只要模型还在分化、技能和工具还在指数级变多,「怎么组织、怎么调度」就是个不会消失的问题。 很有趣的方向。 GitHub:
查看原文
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缓存时间: 2026/06/03 23:55

➤ 最近还是不断有新的 Agent Harness 思路和实践在出现。

这两天看到 OpenSquilla,一个开源、能本地托管的 AI Agent。

① 它有智能模型路由——同样的任务,token 成本比 OpenClaw 省 60-80%,跑任务时还有个「老虎机」动画告诉你这一单省了多少钱。

路由省的不只是钱:现在各家模型各有所长、价格也不一样,benchmark 高低跟具体任务上的表现还常常对不上。

与其死磕单一最强模型,不如按任务把活派给最合适的那个——它真正在优化的,是「每块钱 token 换回多少智能」。

② 刚发布 MetaSkill。简单说,它是「Skill 的 Skill」——一份告诉模型怎么检索、筛选、组合原子 Skill 的元 markdown。

因为单个 Skill 只干一件事,搜索归搜索,文档归文档。用户自己当调度员,脑子里一直装着下一步该使唤哪个,Skill 一多就会手忙脚乱。

MetaSkill 接管了这个「项目经理」的角色——由它来安排哪些步骤可以并行、哪些只能串行,让 Agent 学会自己组织技能。

③ 还有 meta-skill-creator:一句话需求,自动合成一个新的 meta-skill,手写 30 分钟的活压到 3 分钟。等于是 Agent 自己造技能。

➤ Why now?三件事撞到了一起:模型已经听得懂复杂的多步骤编排指令;社区 Skill 在爆发式增长,多到必须有个更高的抽象层来筛;大模型在线 trial-and-error 依然太贵,得把优化前置到 Skill 组织层。

这三条线指向同一点——Agent 要解决的问题,正在从「会不会调用工具」变成「会不会组织工具」。

**➤ 更深一层:**Harness 这层会不会只是个过渡概念、迟早被更强的模型吃掉?

我倒不这么看——只要模型还在分化、技能和工具还在指数级变多,「怎么组织、怎么调度」就是个不会消失的问题。

很有趣的方向。

GitHub:


opensquilla/opensquilla

Source: https://github.com/opensquilla/opensquilla

OpenSquilla — Token-Efficient AI Agent

OpenSquilla logo

Same budget, more capability, better results.
A microkernel AI agent for your CLI, Web UI, and chat channels.

CI Website GitHub release Python 3.12+ Apache 2.0 License


Overview

OpenSquilla is a token-efficient, microkernel AI agent. A local model router sends each turn to the cheapest model that can handle it, while persistent memory, a layered sandbox, built-in web search, and on-device embeddings round out a single shared turn loop.

Every entry point — Web UI, CLI, and chat channels — runs through that same loop, so tool dispatch, retries, and decision logging behave identically everywhere. A pluggable provider layer speaks to OpenRouter, OpenAI, Anthropic, Ollama, DeepSeek, Gemini, Qwen/DashScope, and 20+ other LLM providers with no change to your code or config schema.

OpenSquilla 0.3.1 is the current release.

For task-oriented product documentation, start with the OpenSquilla Product Guide or the documentation index.


Installation

OpenSquilla runs on Windows, macOS, and Linux. Pick the path that matches your use case.

Windows portable and Quick terminal install give you a prebuilt release — no Git required. The other two — Install from source and Develop from source — build from a Git checkout (git clone + Git LFS).

Release install commands use published GitHub release assets. The Windows portable zip also has a /releases/latest/download/ alias for the current release. Python wheel installs use versioned wheel filenames because installers validate the version embedded in the wheel filename.

PathAudienceWhen to use
Windows portableWindows usersNo Python toolchain; one-zip launch
Quick terminal install (recommended)End users on any OSRelease wheel from a terminal
Install from sourceUsers tracking mainRun from a checkout, not edit it
Develop from sourceContributorsEdit, test, or debug the source

Prerequisites

RequirementWindows portableQuick terminal installInstall from sourceDevelop from source
Python 3.12+bundledvia uvvia uv or systemvia uv
Git + Git LFSrequiredrequired
uvinstalled if missingrecommendedrequired

The default recommended profile installs SquillaRouter — OpenSquilla’s on-device model router — and its model assets; OPENSQUILLA_INSTALL_PROFILE=core omits those dependencies. The separate --router disabled onboarding flag keeps the dependencies installed but turns the router off at runtime.

On Windows, SquillaRouter’s bundled ONNX runtime also needs the Visual C++ runtime. The Windows portable launcher and the from-source PowerShell installer install it automatically via winget; the Quick terminal install (uv tool install) path does not — if startup logs a DLL load failed error, install it manually (see Troubleshooting). OpenSquilla keeps running with direct single-model routing until it is installed.

Install links: Git · Git LFS · uv.

Windows portable (no Python)

The fastest path on Windows — the zip ships a bundled CPython runtime, so no separate Python install is required.

  1. Download the current portable zip: https://github.com/opensquilla/opensquilla/releases/latest/download/OpenSquilla-windows-x64-portable.zip
  2. Extract it to a writable folder such as Downloads or Documents, then right-click Start OpenSquilla.cmd and choose Run as administrator.
  3. Complete the first-run setup, then open http://127.0.0.1:18791/control/.

Preview builds are unsigned; administrator launch is the supported path. If SmartScreen appears, choose More infoRun anyway. If Smart App Control or enterprise policy blocks the unsigned app, use Quick terminal install instead.

Advanced portable usage

Provide an OpenRouter key before first start:

$env:OPENROUTER_API_KEY="sk-..."
Set-ExecutionPolicy -Scope Process Bypass
.\start.ps1

If OPENROUTER_API_KEY is set and no local config exists, the launcher writes an env-reference config and starts the gateway without prompting. If unset, the onboarding wizard lets you pick any supported provider.

The portable zip does not install a global opensquilla command. For a terminal where opensquilla … works, run OpenSquilla Shell.cmd, or call the bundled launcher directly:

.\opensquilla.cmd onboard --provider openrouter --api-key-env OPENROUTER_API_KEY

Quick terminal install

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; for main, development branches, or local checkouts use Install from source.

1. Install uv — skip if uv --version already works.

Linux / macOS:

curl -LsSf https://astral.sh/uv/install.sh | sh
. "$HOME/.local/bin/env"

Windows PowerShell:

powershell -c "irm https://astral.sh/uv/install.ps1 | iex"
$env:Path = "$env:USERPROFILE\.local\bin;" + $env:Path

2. 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"

This 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 such as ONNX Runtime, LightGBM, NumPy, and tokenizers, so a first install needs network access unless those wheels are already cached.

3. Configure and run.

opensquilla onboard
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.

For a fully pinned install, use the versioned wheel URL: https://github.com/opensquilla/opensquilla/releases/download/v0.3.1/opensquilla-0.3.1-py3-none-any.whl.

Install from source

Use this path to run OpenSquilla from a checkout without editing it. The clone is only the package source for the installer; after install, use the opensquilla command — do not run uv run. Choose Develop from source instead if you intend to modify the code.

  1. Clone with LFS assets

    git lfs install
    git clone https://github.com/opensquilla/opensquilla.git
    cd opensquilla
    git lfs pull --include="src/opensquilla/squilla_router/models/**"
    
  2. Run the installer

    macOS / Linux

    bash scripts/install_source.sh
    

    Windows PowerShell

    powershell -ExecutionPolicy Bypass -File ./scripts/install_source.ps1
    

    The script installs .[recommended] (SquillaRouter + memory + local models) into a dedicated user environment via uv tool install, falling back to python -m pip install --user when uv is unavailable. Open a new terminal if opensquilla is not on PATH after install.

  3. (optional) Install advanced extras. Most channels — Feishu, Telegram, DingTalk, QQ, WeCom, Slack, and Discord — work from the base install. The opt-in extras are:

    • matrix — Matrix channel (pulls in matrix-nio)
    • matrix-e2e — Matrix channel with end-to-end encryption (requires libolm)
    • document-extras — PDF generation via WeasyPrint
    OPENSQUILLA_INSTALL_EXTRAS=matrix bash scripts/install_source.sh        # macOS / Linux
    
    powershell -ExecutionPolicy Bypass -File ./scripts/install_source.ps1 -Extras matrix   # Windows
    
  4. Configure and run — see Configuration.

Install from source — terminal prerequisites and installer options

Install prerequisites (Git, Git LFS, uv) from a terminal

Windows PowerShell:

winget install --id Git.Git -e
winget install --id GitHub.GitLFS -e
powershell -ExecutionPolicy Bypass -c "irm https://astral.sh/uv/install.ps1 | iex"
git lfs install

macOS (Homebrew):

brew install git git-lfs uv
git lfs install

Debian / Ubuntu:

sudo apt update && sudo apt install -y git git-lfs
curl -LsSf https://astral.sh/uv/install.sh | sh
git lfs install

On Fedora use sudo dnf install -y git git-lfs; on Arch use sudo pacman -S --needed git git-lfs; then install uv with the curl command above. PATH changes from these installers apply to new terminal sessions.

Installer environment variables and PATH checks

OPENSQUILLA_INSTALL_PROFILE=core   bash scripts/install_source.sh   # minimal runtime, no SquillaRouter
OPENSQUILLA_INSTALL_DRY_RUN=1      bash scripts/install_source.sh   # print the plan only

Verify which opensquilla your shell runs with command -v opensquilla (macOS/Linux) or where.exe opensquilla (Windows). If it is not on PATH, run uv tool update-shell. After reinstalling from a local checkout, restart the gateway so it loads the updated package.

Develop from source

Use this path when you are working on OpenSquilla’s source code: making changes, running tests, or debugging behavior against this checkout. It is not the normal install path. Unlike Install from source, this path requires uv: uv sync creates a repository-local .venv, and uv run executes commands against the files in this checkout.

uv sync --extra recommended --extra dev
uv run opensquilla --help

The recommended extra includes SquillaRouter for development too; the dev extra installs the test, lint, and typecheck tools. Install additional extras into the same environment you run:

uv sync --extra recommended --extra dev --extra matrix
uv run opensquilla channels status matrix --json

In this mode, prefix every opensquilla command in Configuration with uv run. Do not debug a development checkout through a user-local opensquilla command — that command runs in a different Python environment.


Configuration

First-run setup

opensquilla onboard is the interactive first-run wizard. It writes the active config file and keeps provider secrets in environment variables when you pass --api-key-env. The router defaults to recommended (SquillaRouter on supported providers); pass --router disabled for direct single-model routing.

opensquilla onboard                # full interactive wizard
opensquilla onboard --if-needed    # idempotent: safe for scripts and re-installs
opensquilla onboard --minimal      # provider only; skip channels and search
opensquilla onboard status         # inspect every setup section without writing

In SSH, CI, or any environment without a TTY, use the non-interactive form — keep the secret in the environment and pass its name, not its value:

Linux / macOS

export OPENROUTER_API_KEY="sk-..."
opensquilla onboard --provider openrouter --api-key-env OPENROUTER_API_KEY

Windows PowerShell

$env:OPENROUTER_API_KEY="sk-..."
opensquilla onboard --provider openrouter --api-key-env OPENROUTER_API_KEY

OpenRouter is only an example — substitute any supported provider and its API-key variable.

Re-configure one section later without redoing the whole wizard (these examples assume the relevant API key is already in the environment):

opensquilla configure provider --provider openai --model gpt-4o --api-key-env OPENAI_API_KEY
opensquilla configure router --router recommended
opensquilla configure search   --search-provider brave --api-key-env BRAVE_SEARCH_API_KEY
opensquilla configure channels

Sections: provider, router, channels, search, image-generation, memory-embedding. The Web UI exposes the same catalog and status model at /control/setup: Provider and Router are the fast path, while Channels, Search, Image generation, and Memory embedding sit in the Capability Center and can be configured later. Empty channels are treated as an opt-out, not a failed setup.

Config load order: OPENSQUILLA_GATEWAY_CONFIG_PATH./opensquilla.toml~/.opensquilla/config.toml → built-in defaults. Environment values for individual secrets always win over file values.

Migrate from OpenClaw or Hermes Agent

If you already have state under ~/.openclaw or ~/.hermes, run a dry run first to inspect the migration report, then apply it explicitly:

opensquilla migrate openclaw --json
opensquilla migrate openclaw --apply

opensquilla migrate hermes --json
opensquilla migrate hermes --apply

Use opensquilla migrate --source openclaw,hermes --apply to import both default homes. Add --migrate-secrets only after reviewing the dry-run report. See MIGRATION.md for custom paths and conflict handling.

Run

opensquilla gateway run                # foreground, 127.0.0.1:18791
opensquilla gateway start --json       # background + health wait
opensquilla chat                       # interactive REPL
opensquilla agent -m "your prompt"     # one-shot, automation-friendly

Open the Web UI at http://127.0.0.1:18791/control/. The Health view shows whether OpenSquilla is ready, what is not ready, and the next recovery steps. From the CLI, run:

opensquilla doctor
opensquilla doctor --json
opensquilla doctor --config ./opensquilla.toml --json

/health and /healthz are lightweight liveness endpoints for process checks. opensquilla doctor and the Web UI Health view are the readiness surfaces for provider config, memory, logs, search, channels, sandbox posture, router, image generation, and recovery guidance. Press Ctrl+C to stop a foreground gateway.

Other command groups include sessions, skills, memory, migrate, cron, channels, providers, models, and cost. Run opensquilla --help or opensquilla <group> --help for details.

Advanced configuration — verify a channel, public network binding, Docker

Connect and verify a messaging channel

Channel saves are config changes, not runtime-connectivity proof. Restart the gateway after channel edits, then verify the live channel:

opensquilla gateway restart
opensquilla channels status <name> --json

Treat a channel as connected only when the status payload reports enabled=true, configured=true, and connected=true. Feishu defaults to websocket mode, Telegram to polling, and Slack can use Socket Mode — none of those modes needs a public URL. Feishu webhook mode, Telegram webhook mode, Slack webhook mode, and WeCom require a public, provider-reachable URL.

Public network binding

To reach the Web UI from another machine, bind the gateway to all interfaces and use the host’s public IP:

opensquilla gateway run --listen 0.0.0.0 --port 18791

Public access also requires the host firewall or cloud security group to allow inbound TCP on that port. Do not expose the gateway with [auth] mode = "none" — configure token auth before binding to 0.0.0.0.

Docker

The compose path runs an opensquilla:local image you build yourself. Build it from a source checkout with the Git LFS router assets pulled (see Install from source for the clone and git lfs pull):

docker build -t opensquilla:local .

./start.sh (or start.ps1 on Windows) then runs docker compose up -d and tails the gateway logs. Docker avoids a host Python toolchain — not the local image build.

Provider tiers, sandbox tuning, image generation, and concurrency settings live in opensquilla.toml.example.


What’s New in 0.3.1

OpenSquilla 0.3.1 is a maintenance release for the 0.3 line. It updates the stable install metadata and brings selected channel, chat, provider, and workflow fixes from the integration branch onto the stable release line:

  • Channel setup and replies — Slack Socket Mode, app mentions, signing secrets, and threaded replies preserve the channel context needed for setup and replies.
  • Media and voice workflow handoffs — short-drama/video helper workflows remain bundled, generated media flows have clearer review pauses, and voice/audio handoffs are usable end to end.
  • Chat formatting — user message bubbles preserve multiline text and read like authored messages instead of compressed UI labels.
  • Provider request hardening — malformed tool-call history is kept away from providers before it becomes invalid request state.
  • Install and release checks — installer URLs, release metadata, version consistency tests, and CI impact gates are updated for 0.3.1.

Full notes: CHANGELOG.md · docs/releases/0.3.1.md.

What’s New in 0.2.1

OpenSquilla 0.2.1 is a maintenance release focused on release-package startup and long-running agent reliability:

  • Windows portable startup — the portable launcher better detects and bootstraps the Visual C++ runtime needed by the bundled ONNX router.
  • Long-running agent turns — tool-heavy WebUI sessions recover more cleanly from oversized tool results, malformed tool calls, artifact delivery handoffs, and degraded final responses.
  • Cleaner WebUI output — generated artifact markers are kept out of normal chat replay while delivered files remain visible.
  • Memory recall scoring — local and OpenAI-compatible embedding vectors are normalized before semantic search, and strong keyword matches remain usable when vector scores are low.

Full notes: CHANGELOG.md · release notes.

What’s New in 0.2.0

This release expands OpenSquilla across migration, CLI chat, channels, scheduling, and long-running tool work:

  • Migration path from existing agent homesopensquilla migrate previews and applies imports from existing OpenClaw/Hermes homes, including memory, persona files, skills, MCP/channel config, conflict handling, and migration reports.
  • Usable chat CLIopensquilla chat now has a persistent terminal UI, streaming output, queued input, slash-mode discovery, tool/status strips, and more deterministic live prompt behavior.
  • Cross-surface cron automation — cron jobs now cover structured schedules, timezone-aware exact/every/cron runs, channel or webhook delivery, failure destinations, manual runs, and WebUI/CLI/RPC parity.
  • Better Feishu and Discord channels — channel adapters expose clearer capability metadata, safer DM/group handling, native file and artifact paths, and improved attachment/thread behavior while privileged actions stay scoped.
  • Sturdier long-running turns — failed turns are kept out of provider replay, malformed tool calls are handled more safely, and approval-gated retries wait for operator decisions.
  • Smarter context and tool budgeting — provider-budget compaction, prompt cache preservation, bounded tool results, and side-effect-aware concurrency make large tool-heavy sessions more predictable.
  • Web UI and release polish — recency ordering, table layout, mobile controls, duplicate notifications, setup forms, release URLs, and install paths are tightened for 0.2.0.

Full notes: CHANGELOG.md · release notes.


Key Features

CapabilityWhat it does
Token-efficient routingSquillaRouter — a local LightGBM + ONNX classifier in the recommended extra — scores each turn on length, language, code, keywords, and semantic embeddings, then routes it across four tiers (T0–T3) to the cheapest capable model. Classification runs on-device; your prompt never leaves the machine to make that decision.
Adaptive reasoning and promptsOpenSquilla requests extended reasoning only for turns the router scores as complex, and the system prompt scales with task complexity — lightweight for trivial turns, full instructions for complex ones.
20+ LLM providersThe provider registry targets 20+ LLM backends — OpenRouter, OpenAI, Anthropic, Ollama, DeepSeek, Gemini, DashScope/Qwen, Moonshot, Mistral, Groq, Zhipu, SiliconFlow, vLLM, LM Studio, and more, with primary-plus-fallback selection; first-run onboarding exposes the verified subset.
On-demand skills and MCP15 bundled skills (coding, GitHub, cron, pptx/docx/xlsx/pdf, summarization, tmux, weather, and more) load only when the task needs them. OpenSquilla is an MCP client, and can also run as an MCP server — opensquilla mcp-server run needs the mcp extra (install opensquilla[recommended,mcp]). Skills can be authored, installed, and published from the CLI.
Persistent local memoryA curated MEMORY.md plus dated Markdown notes, searched with SQLite full-text keyword search and sqlite-vec semantic recall. Embeddings run on-device via bundled ONNX, or swap to OpenAI/Ollama. Optional exponential decay and opt-in “dream” consolidation are available.
Layered security sandboxThree policy tiers (Standard / Strict / Locked) on a permission matrix. Bubblewrap isolates code execution on Linux; the macOS Seatbelt backend currently renders profiles only (execution pending), and there is no sandbox backend on Windows yet. A denial ledger auto-pauses autonomous runs after repeated denials, rejected outputs are purged, and skill metadata and tool results are XML-escaped against prompt injection.
Built-in toolsFile read/write/edit, shell and background processes, git, web search (Brave or DuckDuckGo) and fetch behind an SSRF guard, spreadsheet/PPTX/PDF authoring, image generation, and text-to-speech.
Unified gatewayA Starlette ASGI server on 127.0.0.1:18791 with WebSocket RPC and an embedded control console (/control/). Web UI, CLI, and channels for Terminal, WebSocket, Slack, Telegram, Discord, Feishu, DingTalk, WeCom, Matrix, and QQ all share one TurnRunner.
Durable sessions, subagents, and schedulingSQLite-backed session, transcript, and replay storage with per-agent workspaces. Agents spawn depth-bounded subagents, and a SchedulerEngine with an in-tree cron parser runs recurring jobs via opensquilla cron.
Operator controlsHuman-in-the-loop approvals can pause sensitive tool calls for a decision; per-turn and per-session token and cost rollups (opensquilla cost) and diagnostics are available from the CLI and Web UI.

MetaSkill docs: docs/features/meta-skills.md, docs/features/meta-skill-user-guide.md, and docs/authoring/meta-skills.md.


Benchmark Results

PinchBench 1.2.1 average results across 25 tasks:

AgentBase ModelAvg. scoreTotal input tokensTotal output tokensTotal cost
OpenSquillaModel router (Opus4.7, GLM5.1, DS4 Flash)0.92511,721,32861,475$0.688
OpenClawClaude Opus 4.70.92553,066,24350,890$6.233

Score is the mean across the 25 tasks; token counts and cost are totals for the full run.


Troubleshooting

Windows: DLL load failed / Visual C++ runtime

If startup logs DLL load failed while importing onnxruntime_pybind11_state, OpenSquilla keeps running with direct single-model routing, but the bundled SquillaRouter runtime stays inactive until the Visual C++ Redistributable for Visual Studio 2015–2022 (x64) is installed.

The Windows portable launcher and the from-source PowerShell installer attempt to install the redistributable via winget. If you used Quick terminal install, or winget is unavailable, install it manually and restart PowerShell: https://aka.ms/vs/17/release/vc_redist.x64.exe. Then restore the recommended router:

opensquilla onboard --provider openrouter --api-key-env OPENROUTER_API_KEY --router recommended
opensquilla gateway restart

Credits

OpenSquilla is inspired by OpenClaw. Bundled third-party content is attributed in THIRD_PARTY_NOTICES.md.

Community contributors are acknowledged in CONTRIBUTORS.md, including release-specific attribution notes for squash-merged or replayed work.


Contributing

Contributions of every kind are welcome — bug reports, feature ideas, documentation, new provider or channel adapters, skills, and core runtime work. See CONTRIBUTING.md, then open an issue or pull request on GitHub.

Code of Conduct · Security · Support · License (Apache-2.0)

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X AI KOLs

本文系统梳理了AI Agent架构与工程实践,涵盖控制流、上下文工程、工具设计、记忆、多Agent组织、评测、追踪和安全,基于OpenClaw实现展开,强调Harness(测试验证基础设施)对系统稳定性的关键作用。

@seclink: 最近这个开源工具挺火的。 看起来像是 钉钉悟空 、 字节 aily的开源版本。 你可以基于它来实现自己的agent 并且接入到上述的 即时通讯平台之中。 有的哥们基于这个改吧改吧,就能给投资人演示,拿到了不小规模的估值 。 让投资人记忆深…

X AI KOLs Following

CowAgent 是一个基于大模型的开源 AI 助理框架,支持自主任务规划、长期记忆、知识库、多模型切换和多渠道接入(微信、飞书、钉钉等),可快速构建和部署个性化 AI agent。

@gkxspace: 这才是 AI Native 团队的最终形态! 我之前花三周用 OpenClaw 搭 AI 团队,让多agent在Discord里协作,纯属浪费时间(我想我不是一个人) 之前我自己搭的遇到的问题: token 烧得飞快、gent 之间"打架…

X AI KOLs Timeline

作者分享了使用 OpenClaw 搭建多智能体团队时遇到的 token 浪费、死循环等问题,并发现 helioim_ai 通过给每个 AI 独立身份和职责边界,实现了更高效的人机协作,还具备夜间“做梦”自我改进机制。