我们发现了什么
The open-source control plane for AI agents — skill routing, context governance, trustworthy execution, evidence, security, and multi-agent orchestration.. Title: GitHub - casioreview20-glit
- 来源:GitHub(发现于 2026-07-27)
- 证据等级:D · 发现产品或需求信号,暂未获得可核验的商业证据。
- 商业模式:待核验
- 主题:独立产品
- 初筛评分:17.7/100 · 收录 1 次
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中文辅助译文(节选·触顶截断)
ForgeOS
面向 AI 智能体的技能智能操作系统与信任控制平面。
ForgeOS 决定可以运行哪些技能、哪些上下文可以进入、哪些步骤必须是确定性的,以及哪些证据足以接受完成。
5 分钟路径 · 工作原理 · 生态对比 · 面向开发者 · 面向专家 · Tiếng Việt · 22 种语言翻译
ForgeOS 存在的原因
智能体不会因为拥有更多的提示、更多的工具或更长的上下文窗口就变得可靠。
它在系统能够回答以下六个问题时才会变得可靠:
- 需要的具体结果是什么?
- 哪种技术是合适的——而哪些类似的技术在此处是错误的?
- 该工作单元所需的最小上下文是什么?
- 哪些步骤必须是确定性的,而不是委派给模型?
- 哪些独立证据可以证明输出?
- 同一工作流在失败后能否恢复、继续并审计自身?
ForgeOS v0.6 将这些问题转化为运行时:
已确认的意图
→ 结果 + 技术检索
→ 硬性策略与反触发过滤器
→ 最小 RoutePlan DAG
→ 每个工作单元隔离的 ContextPack
→ 确定性 / 智能体 / 反思执行图
→ 锚定输出 + 覆盖账本
→ 可信回执 + 证据门控
→ 发布、回滚、恢复与学习隔离它不是提示词集合。它是围绕技能、规则、钩子、智能体、工具、上下文、证据和学习的控制平面。
v0.6.1 中真实存在的内容
| 表面 | 已验证实现 |
|---|---|
| 旧版类型化结果脚手架 | 1,024 |
| Deep Skill Contract v2 技术 | 128 |
| L0 编排 / 信任 / 上下文技术 | 32 |
| L1 跨领域工程技术 | 96 |
| 独立评估器绑定 | 128 |
| 技能目录 | 250(146 核心,104 领域) |
| 稳定的程序化提供器 | 33 |
| 候选程序化提供器 | 242 |
| 内置技能 + 知识映射 | 1,299 |
| 代码审查智能一致性用例 | 12 |
| 智能体表面对抗用例 | 20/20 |
| 稳定提供器物化 | 33/33 |
| 路由器 Precision@1 / @3 | 93.75% / 100% |
| 路由器 Recall@6 | 100% |
| 不安全路由激活 | 0% |
[!IMPORTANT] 这 1,024 个旧版节点是结果脚手架,并非 1,024 个生产级程序化技能。v0.6 包含 128 个深度技术合约。33 个程序化提供器因兼容性而保留在声明的稳定路由通道中,但最终认证审计发现 0/128 证据合格的稳定项,以及 0 项通过 Revision 2 完成定义认证。其余证据需要留出、配套多模型、压力测试、独立审查和生产回执。
内核清单: 32 项 L0 技术 + 96 项 L1 技术 = 128 项深度内核技术。
目录路由状态: 33 个声明为稳定通道的程序化提供器以及 242 个候选。正式认证证据: 0 项稳定合格,0 项认证。请参阅 最终认证审计。
发布审计有意将这些声明保持为假:
1,024 个生产级程序化技能 假
完整的 PostgreSQL 生命周期高可用 假
通用 microVM 沙箱 假
专家标注的 200-PR 审查基准 假
10,000 次配对评估运行 假ForgeOS v0.6 不声称具备通用生产完整性,也不声称拥有 1,024 个生产级程序化技能。
请参阅 v0.6 声明边界。
通用通道,治理执行
不可变的 通用通道注册表 将工作路由 跨战略与研究、产品 UX/UI、视觉媒体与 3D、软件、 数据与 AI、智能体、安全、云运维、商务、教育、 硬件 / 制造以及机器人 / 物理 AI。通道是一种诚实的路由 与证据合约——并非声称 ForgeOS 可以自主运行工厂、 机器人、支付流程或生产环境。
物理世界的工作仍需人类批准。高风险第三方执行 需要兼容的已配置远程提供器;本地代理从不 伪装为 microVM。请参阅 远程 MicroVM 沙箱。
五分钟路径
当您希望获得价值而无需先学习信任内核时,请使用此路径。
1. 安装
npm install
npm test
node src/cli/forge.mjs init已安装的包:
npx forgeos init
forge doctorforge init 创建一个安全的本地 SQLite-WAL 配置文件。其 API 密钥被写入一个 0600 权限的文件中,且永远不会被打印出来。
2. 找到合适的技术
forge skills search "react rerender"
forge skills inspect reducing-react-render-thrashing
forge route --query "compile the minimum context for a large monorepo"3. 检查 v0.6
forge v06 status
forge profile plan coding --target codex
forge security scan --file agent-surface.json4. 检查高风险执行边界
node src/cli/forge.mjs sandbox status --json在没有配置远程提供器的情况下,此命令会故意返回 unavailable 和退出码 2;ForgeOS 从不将本地代理表示为 microVM。有关签名提供器合约,请参阅 远程 MicroVM 沙箱。
5. 启动本地控制平面
npm start
# 仪表板:http://127.0.0.1:8787/dashboard
# MCP:http://127.0.0.1:8787/mcp
# A2A:http://127.0.0.1:8787/a2a深度操作员路径
在将 ForgeOS 嵌入 Codex、Claude Code、ChatGPT、开源智能体、CI 或内部平台时,请使用此路径。
技能智能路由器
路由器执行两阶段检索,而非匹配技能名称:
意图 / 失败门控
→ 结果检索
→ 直接技术触发检索
→ 反触发排除
→ 信任、租户、成熟度、工具、许可证、新鲜度过滤器
→ 效用度量重排序
→ 最小技术 DAG
→ 提供器解析
→ 冻结的 RoutePlan每个被选中和被拒绝的技术都有一个理由。硬性阻断始终胜过评分。
全局上下文内核 v2
ForgeOS 对完整请求进行预算管理:
系统 · 任务 · 已选技能段落 · 代码符号 · 制品
· 记忆 · 工具输出 · 引用 · 惰性工具模式
· 输出预留 · 安全预留它提供:
- 一个由解析器和物化器共享的令牌计费接口;
- 段落级技能加载;
- 每个工作单元隔离的上下文;
- 惰性工具模式物化;
- 语义 ABI 符号 ID 与陈旧哈希拒绝;
- 制品差异投影;
- 受作用域限制、带过期的本能注入;
- 内容寻址的原始日志与提炼后的失败区间;
- 每个未包含源的缺失清单。
确定性技能织构
一个 v0.6 技术被编译为可执行图:
确定性节点
范围选择 · 打包 · 规则解析 · 锚定 · 证据
智能体节点
调查 · 假设 · 领域判断
反思节点
矛盾 · 假阳性过滤 · 可执行性
控制节点
并行汇合 · 覆盖门控 · 重试 · 回滚SQLite 覆盖账本使用租约、心跳、隔离令牌和可信回执。被回收的工作器无法将工作单元标记为完成。
代码审查智能垂直切片
首个完整的垂直切片端到端地证明了架构:
完整范围
→ 关系感知工作单元
→ 上下文规则选择
→ 隔离的智能体分析
→ 行 / 哈希锚点
→ 编辑后重定位
→ 独立反思
→ 覆盖回执打包的 12 用例语料库是一个确定性一致性基准。它不被宣传为专家标注的 200-PR 基准。
持续学习——无需自动自我污染
观察到的模式成为受限的本能,而非稳定技能:
可信运行回执
→ 观察到的本能
→ 租户 / 项目 / 装备隔离 + TTL
→ 兼容的本能集群
→ 候选演进提议
→ 独立评估
→ 人类提升或回滚生产者无法提升自身习得的行为。
装备运行时 v2
ForgeOS 区分四种表面:
| 表面 | 用途 |
|---|---|
| 规则 | 必须始终应用的简短不变量 |
| 钩子 | 绑定到事件的确定性动作 |
| 技能 | 需要判断的条件性程序 |
| 智能体角色 | 独立的上下文、工具、模型或权限 |
中性事件包括 before.tool.execute、after.file.write、verification.checkpoint、session.compact 和 session.ended。宿主适配器必须标记不支持的功能,而不是声称虚假的等价性。
配置文件:
minimal · coding · creative · research · regulated
local-small · enterprise智能体表面安全
安全引擎扫描智能体系统本身:
- 指令和提示边界违规;
- 钩子和包生命周期脚本;
- MCP 描述、权限和工具可达性;
- 命令允许列表;
- 密钥 / 环境引用;
- 密钥到出站的权限路径;
- 管道到 shell 和广泛的通配符能力;
- 安装前的配置文件权限差异。
其对抗语料库当前通过 20/20 用例。
代理式本地执行
本地运行器为普通命令提供真正的安全边界:
- 无 shell 插值;
- 命令和环境允许列表;
- 工作区和符号链接容纳;
- 超时和进程组终止;
- 有界 stdout / stderr;
- 内容寻址的执行回执。
它不是通用的网络拒绝型 microVM 沙箱。高风险第三方执行仍需要外部容器或 microVM 隔离层。
ForgeOS 现在拥有一个故障闭合的远程 microVM 控制平面适配器:它仅提交到已配置的 HTTPS 提供器,并且仅接受请求绑定、由 Ed25519 签名的回执,以及明确的网络和密钥隔离证据。它从不回退到本地代理。该适配器不是托管的 microVM 服务;兼容的生产提供器仍是外部部署要求。请参阅 远程 MicroVM 沙箱。
ForgeOS 工作原理
ForgeOS 将两个产品合并到一个运行时中:
- 技能智能层:检索技术、拒绝不安全的近似匹配、仅编译所需的技能段落,并构建冻结的执行计划。
- AI 控制平面:管理项目、制品、证据、审批、租约、恢复、联邦和发布门控。
已确认的意图或失败门控
→ 结果和直接技术检索
→ 反触发、租户、信任、工具、许可证和新鲜度过滤器
→ 最小冻结 RoutePlan DAG
→ 每个工作单元隔离的 ContextPack
→ 确定性 / 智能体 / 反思执行图
→ 锚定输出和隔离的覆盖账本
→ 可信回执和保障感知门控
→ 发布、恢复、回滚或学习隔离十个协作系统
| 系统 | 控制内容 |
|---|---|
| 技能智能路由器 | 结果检索、技术评分、反触发、硬性策略、提供器选择,以及可解释的 RoutePlan |
| 全局上下文内核 v2 | 跨策略、任务、技能段落、符号、制品、记忆、工具输出、引用和输出预留的统一令牌预算 |
| 确定性技能织构 | 包含确定性节点、智能体节点、反思节点、审批、锚点和停止条件的混合图 |
| 覆盖账本 | 工作单元所有权、租约、隔离令牌、完成覆盖、陈旧工作器拒绝和可恢复性 |
| 信任内核 | 证据新鲜度、制品谱系、审批权限、保障级别和发布决策 |
| 智能体表面安全 | 提示注入模式、危险的包脚本、密钥到出站路径、权限和适配器能力诚实性 |
| 代理式本地执行 | 无 shell |
……(正文超出本站单页篇幅上限,此处截断;完整表述请见下方原文入口。)
译文由上游机器翻译生成,可能有误;判断请以英文原文为准。
英文原文(来源本站未改写)
ForgeOS
Skill Intelligence OS and Trust Control Plane for AI agents.
ForgeOS decides which skill may run , which context may enter , which steps must be deterministic , and which evidence is strong enough to accept completion .
5-minute path · How it works · Ecosystem comparison · For developers · For experts · Tiếng Việt · 22 translations
Why ForgeOS exists
An agent does not become reliable because it has more prompts, more tools, or a longer context window.
It becomes reliable when the system can answer six questions:
- What exact outcome is required?
- Which technique is appropriate—and which similar techniques are wrong here?
- What is the smallest context needed for this work unit?
- Which steps must be deterministic rather than delegated to a model?
- What independent evidence proves the output?
- Can the same workflow recover, resume, and audit itself after failure?
ForgeOS v0.6 turns those questions into a runtime:
confirmed intent
→ outcome + technique retrieval
→ hard policy and anti-trigger filters
→ minimum RoutePlan DAG
→ isolated ContextPack per work unit
→ deterministic / agent / reflection execution graph
→ anchored outputs + coverage ledger
→ trusted receipts + evidence gates
→ release, rollback, recovery, and learning quarantineIt is not a prompt collection. It is the control plane around skills, rules, hooks, agents, tools, context, evidence, and learning.
What is real in v0.6.1
| Surface | Verified implementation |
|---|---|
| Legacy typed outcome scaffolds | 1,024 |
| Deep Skill Contract v2 techniques | 128 |
| L0 orchestration/trust/context techniques | 32 |
| L1 cross-domain engineering techniques | 96 |
| Independent evaluator bindings | 128 |
| Skill catalog | 250 (146 core, 104 domain) |
| Stable procedural providers | 33 |
| Candidate procedural providers | 242 |
| Built-in skill + knowledge mappings | 1,299 |
| Code Review Intelligence conformance cases | 12 |
| Agent-surface adversarial cases | 20/20 |
| Stable provider materialization | 33/33 |
| Router Precision@1 / @3 | 93.75% / 100% |
| Router Recall@6 | 100% |
| Unsafe route activation | 0% |
[!IMPORTANT]
The 1,024 legacy nodes are outcome scaffolds, not 1,024 production-grade procedural skills. v0.6 contains 128 deep technique contracts. Thirty-three procedural providers remain in the declared stable routing channel for compatibility, but the final certification audit finds 0/128 evidence-qualified stable and 0 certified under the Revision 2 Definition of Done. The remaining evidence requires holdout, paired multi-model, pressure, independent review, and production receipts.
Kernel inventory: 32 L0 techniques + 96 L1 techniques = 128 deep kernel techniques.
Catalog routing states: 33 declared stable-channel procedural providers and 242 candidates. Formal certification evidence: 0 stable-qualified, 0 certified. See Final Certification Audit.
The release audit intentionally keeps these claims false:
1,024 production-grade procedural skills false
full PostgreSQL lifecycle HA false
universal microVM sandbox false
expert-labeled 200-PR review benchmark false
10,000 paired evaluation runs falseForgeOS v0.6 does not claim universal production completeness or 1,024 production-grade procedural skills.
See Claims Boundary v0.6.
Universal lanes, governed execution
The immutable Universal Lane Registry routes work across strategy and research, product UX/UI, visual media and 3D, software, data and AI, agents, security, cloud operations, commerce, education, hardware/manufacturing, and robotics/physical AI. A lane is a truthful routing and evidence contract—not a claim that ForgeOS can autonomously operate a factory, robot, payment flow, or production environment.
Physical-world work remains human-approved. High-risk third-party execution requires a compatible configured remote provider; the local broker never pretends to be a microVM. See Remote MicroVM Sandbox.
Five-minute path
Use this path when you want value without learning the Trust Kernel first.
1. Install
npm install
npm test
node src/cli/forge.mjs initInstalled package:
npx forgeos init
forge doctorforge init creates a safe local SQLite-WAL profile. Its API key is written to a 0600 file and is never printed.
2. Find the right technique
forge skills search "react rerender"
forge skills inspect reducing-react-render-thrashing
forge route --query "compile the minimum context for a large monorepo"3. Inspect v0.6
forge v06 status
forge profile plan coding --target codex
forge security scan --file agent-surface.json4. Check the high-risk execution boundary
node src/cli/forge.mjs sandbox status --jsonWithout a configured remote provider this intentionally returns unavailable and exit code 2; ForgeOS never represents the local broker as a microVM. See Remote MicroVM Sandbox for the signed provider contract.
5. Start the local control plane
npm start
# Dashboard: http://127.0.0.1:8787/dashboard
# MCP: http://127.0.0.1:8787/mcp
# A2A: http://127.0.0.1:8787/a2aDeep operator path
Use this path when embedding ForgeOS into Codex, Claude Code, ChatGPT, an open-source agent, CI, or an internal platform.
Skill Intelligence Router
The router performs two-stage retrieval instead of matching a skill name:
intent / failed gate
→ outcome retrieval
→ direct technique-trigger retrieval
→ anti-trigger exclusion
→ trust, tenant, maturity, tool, license, freshness filters
→ measured-utility reranking
→ minimum technique DAG
→ provider resolution
→ frozen RoutePlanEvery selected and rejected technique has a reason. Hard blockers always beat score.
Global Context Kernel v2
ForgeOS budgets the complete request:
system · task · selected skill sections · code symbols · artifacts
· memory · tool output · references · lazy tool schemas
· output reserve · safety reserveIt provides:
- one token-accounting interface shared by resolver and materializer;
- section-level skill loading;
- isolated context per work unit;
- lazy tool-schema materialization;
- Semantic ABI symbol IDs and stale-hash rejection;
- artifact delta projection;
- scoped, expiring instinct injection;
- content-addressed raw logs with distilled failure ranges;
- an omission manifest for every source not included.
Deterministic Skill Fabric
A v0.6 technique is compiled into an executable graph:
Deterministic nodes
scope-selection · bundling · rule-resolution · anchoring · evidence
Agent nodes
investigation · hypothesis · domain judgment
Reflection nodes
contradiction · false-positive filter · actionability
Control nodes
parallel join · coverage gate · retry · rollbackThe SQLite coverage ledger uses leases, heartbeat, fencing, and trusted receipts. A reclaimed worker cannot mark a work unit complete.
Code Review Intelligence vertical slice
The first complete vertical slice proves the architecture end to end:
complete scope
→ relation-aware work units
→ contextual rule selection
→ isolated agent analysis
→ line/hash anchors
→ relocation after edits
→ independent reflection
→ coverage receiptThe bundled 12-case corpus is a deterministic conformance benchmark. It is not advertised as an expert-labeled 200-PR benchmark.
Continuous Learning—without automatic self-poisoning
Observed patterns become scoped instincts, not stable skills:
trusted run receipts
→ observed instinct
→ tenant/project/harness isolation + TTL
→ compatible instinct cluster
→ candidate evolution proposal
→ independent evaluation
→ human promotion or rollbackThe producer cannot promote its own learned behavior.
Harness Runtime v2
ForgeOS distinguishes four surfaces:
| Surface | Use it for |
|---|---|
| Rule | Short invariant that must always apply |
| Hook | Deterministic action bound to an event |
| Skill | Conditional procedure requiring judgment |
| Agent role | Separate context, tools, model, or authority |
Neutral events include before.tool.execute, after.file.write, verification.checkpoint, session.compact, and session.ended. Host adapters must mark unsupported features instead of claiming false parity.
Profiles:
minimal · coding · creative · research · regulated
local-small · enterpriseAgent Surface Security
The security engine scans the agent system itself:
- instruction and prompt-boundary violations;
- hooks and package lifecycle scripts;
- MCP descriptions, permissions, and tool reachability;
- command allowlists;
- secret/environment references;
- secret-to-egress permission paths;
- pipe-to-shell and broad wildcard capability;
- profile permission diffs before installation.
Its adversarial corpus currently passes 20/20 cases.
Brokered local execution
The local runner provides a real safety boundary for normal commands:
- no shell interpolation;
- command and environment allowlists;
- workspace and symlink containment;
- timeout and process-group termination;
- bounded stdout/stderr;
- content-addressed execution receipt.
It is not a universal network-denying microVM sandbox. High-risk third-party execution still requires an external container or microVM isolation layer.
ForgeOS now has a fail-closed remote microVM control-plane adapter: it submits only to a configured HTTPS provider and accepts only request-bound, Ed25519-signed receipts with explicit network and secret isolation evidence. It never falls back to the local broker. The adapter is not a hosted microVM service; a compatible production provider remains an external deployment requirement. See Remote MicroVM Sandbox.
How ForgeOS works
ForgeOS combines two products in one runtime:
- A Skill Intelligence layer that retrieves techniques, rejects unsafe near-matches, compiles only the required skill sections, and builds a frozen execution plan.
- An AI control plane that manages projects, artifacts, evidence, approvals, leases, recovery, federation, and release gates.
confirmed intent or failed gate
→ outcome and direct-technique retrieval
→ anti-trigger, tenant, trust, tool, license, and freshness filters
→ minimum frozen RoutePlan DAG
→ isolated ContextPack per work unit
→ deterministic / agent / reflection Execution Graph
→ anchored outputs and fenced Coverage Ledger
→ trusted receipts and assurance-aware gates
→ release, recovery, rollback, or learning quarantineTen cooperating systems
| System | What it controls |
|---|---|
| Skill Intelligence Router | Outcome retrieval, technique scoring, anti-triggers, hard policy, provider selection, and explainable RoutePlans |
| Global Context Kernel v2 | One total token budget across policy, task, skill sections, symbols, artifacts, memory, tool output, references, and output reserve |
| Deterministic Skill Fabric | Hybrid graphs containing deterministic nodes, agent nodes, reflection nodes, approvals, anchors, and stop conditions |
| Coverage Ledger | Work-unit ownership, leases, fencing tokens, completion coverage, stale-worker rejection, and resumability |
| Trust Kernel | Evidence freshness, artifact lineage, approval authority, assurance levels, and release decisions |
| Agent Surface Security | Prompt-injection patterns, dangerous package scripts, secret-to-egress paths, permissions, and adapter capability honesty |
| Brokered Local Execution | Shell-free comma |
... (truncated at the site's per-page length limit; see the source link below for the full text.)
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