能力标签
技能工厂
⚙️
Agent工作流

技能工厂

基于 TypeScript · 无代码搭建完整 AI 自动化流程
英文名:skillfoundry
⭐ 10 Stars 🍴 1 Forks 💻 TypeScript 📄 MIT 🏷 AI 7.5分
7.5AI 综合评分
aitypescript工作流
✦ AI Skill Hub 推荐

经 AI Skill Hub 精选评估,技能工厂 获评「推荐使用」。这款Agent工作流在功能完整性、社区活跃度和易用性方面表现出色,AI 评分 7.5 分,适合有一定技术背景的用户使用。

📚 深度解析

技能工厂 是一套完整的 AI Agent 自动化工作流方案。随着 AI 能力的不断提升,基于 Agent 的自动化工作流正在成为提升个人和团队效率的核心方式。区别于传统的 RPA 自动化(模拟鼠标键盘操作),AI Agent 工作流通过理解任务意图、动态规划执行路径,能够处理更复杂的非结构化任务。

技能工厂 工作流的设计遵循"最小配置,最大复用"原则:核心逻辑已经封装好,用户只需配置自己的 API Key 和业务参数即可快速上手。工作流内置错误处理和重试机制,在网络波动或 API 限速等情况下仍能稳定运行,适合作为生产环境的自动化基础设施。

在实际部署时,建议先在测试环境中运行 3-5 次,验证各个环节的输出结果符合预期,再部署到生产环境。AI Skill Hub 评分 7.5 分,是同类 Agent 工作流中的精选推荐。

📋 工具概览

技能工厂 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排,将复杂的多步骤任务拆解为清晰的自动化流程,实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成,适合构建数据处理管线、业务自动化和 AI 辅助决策系统。

GitHub Stars
⭐ 10
开发语言
TypeScript
支持平台
Windows / macOS / Linux
维护状态
轻量级项目,按需更新
开源协议
MIT
AI 综合评分
7.5 分
工具类型
Agent工作流
Forks
1

📖 中文文档

以下内容由 AI Skill Hub 根据项目信息自动整理,如需查看完整原始文档请访问底部「原始来源」。

技能工厂 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排,将复杂的多步骤任务拆解为清晰的自动化流程,实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成,适合构建数据处理管线、业务自动化和 AI 辅助决策系统。

📌 核心特色
  • 可视化 Agent 工作流编排,无需编写复杂代码
  • 支持多步骤自动化任务链,实现全流程无人值守
  • 与外部 API、数据库和第三方服务无缝集成
  • 内置错误处理与自动重试机制,保障稳定运行
  • 提供可复用的自动化模板,快速在同类场景部署
🎯 主要使用场景
  • 自动化日常重复性工作,将精力集中于创造性任务
  • 构建数据采集 → 处理 → 输出的完整自动化管线
  • 实现跨平台、跨系统的数据流转和业务协同
以下安装命令基于项目开发语言和类型自动生成,实际以官方 README 为准。
安装命令
# 方式一:npm 全局安装
npm install -g skillfoundry

# 方式二:npx 直接运行(无需安装)
npx skillfoundry --help

# 方式三:项目依赖安装
npm install skillfoundry

# 方式四:从源码运行
git clone https://github.com/samibs/skillfoundry
cd skillfoundry
npm install
npm start
📋 安装步骤说明
  1. 访问 GitHub 仓库获取工作流文件
  2. 在对应平台(Dify / Flowise / Make 等)中找到「导入工作流」功能
  3. 上传工作流文件
  4. 按照提示配置必要的环境变量和 API Key
  5. 运行测试确认流程正常后投入使用
以下用法示例由 AI Skill Hub 整理,涵盖最常见的使用场景。
常用命令 / 代码示例
# 命令行使用
skillfoundry --help

# 基本用法
skillfoundry [options] <input>

# Node.js 代码中使用
const skillfoundry = require('skillfoundry');

const result = await skillfoundry.run(options);
console.log(result);
以下配置示例基于典型使用场景生成,具体参数请参照官方文档调整。
配置示例
# skillfoundry 配置说明
# 查看配置选项
skillfoundry --config-example > config.yml

# 常见配置项
# output_dir: ./output
# log_level: info
# workers: 4

# 环境变量(覆盖配置文件)
export SKILLFOUNDRY_CONFIG="/path/to/config.yml"
📑 README 深度解析 真实文档 完整度 81/100 查看 GitHub 原文 →
以下内容由系统直接从 GitHub README 解析整理,保留代码块、表格与列表结构。

SkillFoundry

Turn requirements into tested, production-ready code — with quality gates your AI can't skip.

CI npm downloads Version License Platforms Providers Node

SkillFoundry is an AI engineering framework that works two ways: as a standalone CLI (sf) with its own AI connection, or as a skill layer inside your existing IDE (Claude Code, Cursor, Copilot, Codex, Gemini, Grok Build). Either way you get the same thing — quality gates your AI can't skip, a PRD-first pipeline that enforces structure before writing code, and persistent memory that learns from every session. 23 real tool agents, 128+ skills, 6 AI providers, a tree-sitter Code Map pre-flight that reads your codebase before the AI writes, Semgrep SAST, PRD linting, cross-platform parity detection, and a knowledge base built from 2,792 artifacts across 49 projects.

<p align="center"> <img src="docs/demo.gif" alt="SkillFoundry /forge demo — PRD validation, story implementation, quality gates, security audit" width="840"> </p>

What's New in v5.17.0

Codebase Comprehension Pre-Flight (Code Map)

v5.17.0 gives your AI a structural map of the code before it writes a line — the missing half of the pre-flight (the other half checks your environment). It's a tree-sitter engine exposed as the sf_codemap tool and the /preflight command, wired straight into /forge and /go.

  • Reads the real code, not guesses — extracts the API contract surface (endpoints[]), import graph, call graph, and a DB/layer map from TS/JS + Python.
  • Feeds the gates — hands the real endpoints to sf_contract_check and unresolved imports to sf_import_validator before code is written, attacking the #1 vibe-coding failure (frontend/backend contract mismatch) proactively.
  • Cheap to run — incremental refresh re-parses only changed files (sha256-keyed); runs automatically in the IGNITE phase and never blocks (advisory).
  • Diff-impact — see the blast radius of a change (which components depend on what you touched).
  • Code Map dashboard tab — explore the map by layer, search symbols, toggle a diff-impact overlay (localhost-only).
  • Optional, non-authoritative LLM labels — off by default; plain-English summaries are flagged as hints and never satisfy quality gates.
  • Pure-WASM tree-sitter — no native build, npm ci stays portable.

Previous: Coding Discipline Protocol (v5.15.0)

  • Framework-wide behavioral guardrail (agents/_coding-discipline.md): Think-Before-Coding, Simplicity-First (scoped), Surgical Changes, Goal-Driven Execution, stricter-rule-wins. Documentation/behavior only.

Previous: MCP Server Security Hardening (v5.14.0)

  • Bearer token auth, rate limiting, CORS, handleRouteError(), MAX_PAGE_SIZE = 500, atomic session writes. All 11 BPSBS controls pass.

Previous: Pipeline Quality (v5.13.0)

  • /guardloop skill, failure-scan.sh + guardloop-harvest.sh hooks, agents/_guardloop-rules.md adaptive rules file. 10 patterns tracked, CRITICAL patterns auto-promoted after 3 hits.

Previous: FolderFlow — Story State Machine (v5.11.0)

  • /go + /layer-check integration, story checkbox reconciler, folder state machine (todo/in-progress/blocked/done), JSON artifact handlers. 83-case test suite.

Previous: Test Cartographer — /test-map Skill (v5.10.0)

  • /test-map skill for automated test documentation across all 5 platforms with three-tier classification (HIGH/MEDIUM/BASELINE), deep optimization for GitHub Copilot with the Claude model (~160 lines of constitutional rules), and config-protect fix for .claude/ allowlist entries.
  • Forge progress notificationwithProgress notification wraps the forge terminal lifetime, cancellable from the notification. ForgeMonitor sidebar continues tracking phases live via forge-state.json.

Previous: Adversarial Intelligence (v5.7.0)

Local Vector Memory + Specter Security Engine + Red Team Researcher Skill

  • Local Vector Memory — File-based cosine-similarity vector store with multi-provider embedding (Ollama → Transformers → OpenAI). TransformersEmbeddingProvider (@xenova/transformers) is always available as a zero-dependency local fallback. harvestRunMemory now semantically indexes every pipeline run. Hybrid recall combines keyword + semantic search.
  • Specter Security Engine — Adversarial threat modeling phase injected into every pipeline between INSPECT and DEBRIEF (now 9 phases). SpecterEngine runs an agentic red-team loop, generates attack vectors with severity/CVSS metadata, and executes safe simulations against an allowlisted command set. Registered as the 62nd agent (specter, FULL category).
  • Red Team Researcher Skill (/red-team-researcher) — Senior offensive/defensive security researcher persona. Thinks in attacker primitives (source → sink → impact), grades severity by reachability, uses structured finding format. Ships with 6 domain reference files: code review, web/API, cloud infrastructure, threat modeling, reporting, and blue team/incident triage.

Previous: Parallel Dispatch + NL Cron (v5.6.0)

  • Parallel Dispatch Engine (sf_parallel_analyze), Natural Language Cron (sf_cron_compile).

Previous: Hermes Intelligence (v5.5.0)

  • LLM Context Summarizer (Haiku-powered), Memory Nudge System (13 tools monitored), FTS5 Session Search (sf_memory_search).

Previous: Token Optimization (v5.4.0)

  • Response Optimizer (JSON compaction, concise mode, output truncation), Token Tracker (SQLite-persisted), sf_token_report tool.

Previous: Hook Enforcement (v5.3.0)

  • GateGuard (force-read-before-edit), Config Protection (30+ linter/formatter configs), Session Quality Report, Session Lifecycle hooks.

Previous: Multi-Tenant Security (v5.2.0)

  • Auto-injected security stories (SEC-001–SEC-006), Multi-Tenant Isolation Gate (7 checks), 10 deviation patterns (MT-001–MT-010).

Previous: Harness Engineering + Learning Intelligence (v5.0–5.1)

  • 22 tool agents, Secret Guard, Deviation Enforcer (161 rules), Import Validator, Correction Loop, Health Scores, harness engineering upgrade.
// Token printed to console on first boot — also at data/.api-token
"mcpServers": {
  "skillfoundry": {
    "url": "http://localhost:9877/mcp/sse",
    "headers": { "Authorization": "Bearer <token>" }
  }
}

Features

Quick Install

```bash

Full pipeline — works in Claude Code, Copilot, Cursor, Codex, Gemini, Grok Build

/prd "add user authentication" # create requirements /forge # validate → implement → gate → audit → harvest /goma # autonomous mode: just describe what you want

One-time setup: connect a global knowledge repo

scripts/knowledge-sync.sh init https://github.com/you/dev-memory.git

Or build from source

cd skillfoundry-vscode && npm install && npm run build code --install-extension skillfoundry-1.3.0.vsix ```

IDE Skills (63 — Claude Code, Copilot, Cursor, Codex, Gemini, Grok Build)

These work inside your AI coding tool, not in the sf CLI:

SkillPurpose
/forgeFull 6-phase pipeline (Ignite → Forge → Temper → Inspect → Remember → Debrief)
/goPRD-first orchestrator: validate → stories → implement
/gomaAutonomous mode: classify intent, route to pipeline, execute
/prd "idea"Create a Product Requirements Document
/coderCode implementation agent
/testerTest generation and validation
/reviewCode review
/securitySecurity audit (OWASP, credentials, banned patterns)
/architectSystem design and architecture
/debugInteractive debugger (breakpoints, scope, evaluate)
/layer-checkThree-layer validation (DB → Backend → Frontend)
/memoryKnowledge management
/gohmHarvest lessons from current session
/autonomousToggle autonomous developer loop
*...and 50 more*See /help in your IDE for the full list
Note: /forge exists in both systems but they are different implementations. The IDE skill orchestrates sub-agents; the CLI command runs a self-contained pipeline.

---

Quick Start (5 Minutes)

1. Install & Setup

npm install -g skillfoundry
sf setup                           # Pick provider, paste API key

2. Create a PRD

/prd "add user authentication"     # Describe your feature

3. Forge Production Code

/forge                             # Validate, implement, and test automatically

Using an IDE? Run npx skillfoundry init in your project to add these skills directly to Claude Code, Cursor, or Copilot.

<details> <summary><strong>Windows (PowerShell)</strong></summary>

```powershell

Option A: npx

cd C:\MyProject npx skillfoundry init

Option B: npm global

npm install -g skillfoundry cd C:\MyProject; skillfoundry init

Option C: git clone

git clone https://github.com/samibs/skillfoundry.git C:\DevTools\skillfoundry cd C:\MyProject C:\DevTools\skillfoundry\install.ps1 ```

</details>

Requires Node.js v20+ for the standalone CLI. IDE skills work without Node.js. Cross-platform: Works on Linux, macOS, Windows (native, Git Bash, and WSL). Quality gates and anvil scripts auto-detect the environment. New to SkillFoundry? See the Todo API example — a complete project built from a single PRD in two commands. For model recommendations, see Model Compatibility.

---

.skillfoundry/config.toml

[budget] monthly_limit_usd = 50.00 per_run_limit_usd = 2.00 ```

Token usage and cost are shown live in the header during streaming.

.skillfoundry/config.toml

[routing] route_local_first = true # Enable local-first routing local_provider = "ollama" # or "lmstudio" local_model = "llama3.1" # your preferred local model context_window = 0 # 0 = auto-detect from model


**What happens when enabled:**
- Simple tasks (docs, formatting, boilerplate) route to your local model (free)
- Complex tasks (architecture, security, refactoring) route to cloud (paid)
- Context compaction automatically fits prompts within local model limits (4K-32K)
- If the local model is offline, cloud fallback activates with a warning
/cost → Shows local vs cloud token breakdown + estimated savings /config route_local_first true → Enable routing /provider set lmstudio → Switch to LM Studio ```

Standalone CLI — no IDE needed

npm install -g skillfoundry sf setup # interactive: choose provider, paste API key sf forge # run the full pipeline from your terminal

2. The Standalone CLI (`sf`)

A separate terminal app with its own AI connection. Useful for provider switching, budget controls, and working outside an IDE. Has 23 native commands (not all 64 skills).

 ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
 │ ◆ SkillFoundry CLI    anthropic:claude-sonnet ● team:dev ● $0.00 ● 14.2k tok │
 └──────────────────────────────────────────────────────────────────────────────────┘

 │ ▸ sf:coder> I'll help you add dark mode. Let me look at the existing
 │             dashboard code...
 │
 │   ▸ bash    npm test                ✓ 0.8s
 │   ◉ read    src/styles/theme.ts     ✓ 0.1s
 │   ◈ write   src/styles/dark.ts      ✓ 0.1s
 │
 │   ● routed:high ● 142 in / 387 out ● $0.0045

 ╭──────────────────────────────────────────────────────────────────────────────────╮
 │ ⟫ looks good, now review for accessibility issues                               │
 ╰──────────────────────────────────────────────────────────────────────────────────╯

 │ ▸ sf:review> I'll review the dark mode implementation for accessibility...

---

Command Reference

sf CLI Commands (23 native)

These work inside the sf terminal app:

CommandPurpose
/helpList available commands
/setupConfigure API keys
/statusSession info, provider, budget
/team <name>Summon a team (dev, security, ops, fullstack, ship)
/agent <name>Activate a single agent (coder, review, tester, etc.)
/plan <task>Generate an implementation plan
/apply [plan-id]Execute a plan with quality gates
/gates [target]Run The Anvil quality gates (T1-T7)
/gate <t0-t7\|all>Run a single quality gate or all gates
/forgePipeline: validate PRDs → implement → gate → report
/forge --dry-runRead-only scan without execution
/provider [set <name>]Switch AI provider
/model [model-name]List or switch the AI model
/costToken usage and cost report
/memory [stats\|recall]Query or record knowledge
/config [key] [value]View or edit configuration
/metrics [--window N]Quality metrics dashboard with trends
/report [--format md\|json]Generate exportable quality report
/benchmarkCompare quality against industry baselines
/hook install\|uninstall\|statusManage git hook integration for quality gates
/runtimeRuntime intelligence status (message bus, agent pool, vector store)
/prd review <path>Score a PRD on 4 dimensions with actionable feedback
/lessonsQuery and manage knowledge bank entries

Pipeline Resume

/forge tracks story completion and resumes where it left off. If a run is interrupted or partially fails, re-running /forge skips already-completed stories and implements only the remaining ones.

Implementing 2 stories (3 already done, skipped)

Stories are marked status: DONE in their .md files after successful completion, including passing micro-gates and fixer loops.

Search "SkillFoundry" in the Extensions panel, or:

code --install-extension skillfoundry.skillfoundry

Pipeline Details

                    ┌─────────────┐
                    │   /prd      │  Write requirements
                    └──────┬──────┘
                           │
                    ┌──────▼──────┐
                    │   /go       │  Validate → generate stories → implement
                    └──────┬──────┘
                           │
              ┌────────────┼────────────┐
              │            │            │
        ┌─────▼─────┐ ┌───▼───┐ ┌─────▼─────┐
        │ Architect  │ │ Coder │ │  Tester   │  Agent pipeline
        └─────┬─────┘ └───┬───┘ └─────┬─────┘
              │            │            │
              └────────────┼────────────┘
                           │
                    ┌──────▼──────┐
                    │ Micro-Gates │  MG1 security + MG2 standards
                    └──────┬──────┘
                           │
                    ┌──────▼──────┐
                    │  The Anvil  │  T1-T6 quality gates
                    └──────┬──────┘
                           │
                    ┌──────▼──────┐
                    │  /security  │  OWASP scan + credential check
                    └──────┬──────┘
                           │
                    ┌──────▼──────┐
                    │   /gohm     │  Harvest lessons → memory_bank/
                    └──────┬──────┘
                           │
                    ┌──────▼──────┐
                    │ knowledge   │  Sync to global repo (optional)
                    │    sync     │  Lessons available in all projects
                    └─────────────┘

/forge runs this entire pipeline in one command. It discovers PRDs, generates stories, implements each story with the agentic tool-use loop, runs micro-gates (MG1 security + MG2 standards per story, MG3 cross-story review), runs T1-T6 quality gates (with auto-fixer retries), persists run metadata, and automatically harvests knowledge entries (run summaries, errors, gate verdicts) to memory_bank/knowledge/*.jsonl. Use /forge --dry-run for a read-only scan.

---

VS Code Extension (v1.3.0)

SkillFoundry ships a native VS Code extension that works as a complete standalone shell — setup wizard, CLI check, quality gates, telemetry, and forge runs directly in your editor.

┌──────────┬──────────────────────────────┬───────────────┐
│ Explorer │ Editor                       │ SF Sidebar    │
│          │                              │               │
│          │  src/auth.ts                 │ ◆ Dashboard   │
│          │  ─────────────────           │  Pass Rate 94%│
│          │  1 │ import { hash }         │  Last Forge ✓ │
│          │  2 │ // TODO: add rate  ⚠    │  CVEs: 2 high │
│          │    │ ▸ Run T1 (Patterns)     │               │
│          │    │ ▸ Run T4 (Security)     │ ◆ Gate Status │
│          │                              │  T0-T7 results│
│          │                              │               │
│          │                              │ ◆ Forge       │
│          │                              │  Phase: SPECTER│
│          │                              │  Story: 5/8   │
├──────────┴──────────────────────────────┴───────────────┤
│ SF: 94% gates │ sf:coder │ $0.12               Output   │
└─────────────────────────────────────────────────────────┘

Features (v1.3.0): - Setup wizard (SkillFoundry: Setup) — On first open, prompts for provider and API key. Key stored in VS Code SecretStorage; never written to disk. Auto-detects missing install and offers setup. - sf CLI check — Detects whether sf is on PATH at activation. If missing, offers npm install -g skillfoundry via integrated terminal in one click. - Forge progresswithProgress notification stays open for the duration of the forge run, cancellable. ForgeMonitor sidebar tracks phases live via forge-state.json. - Sidebar dashboard — gate pass rate, security findings, telemetry trends, dependency CVEs - Inline diagnostics — gate findings appear as squiggly underlines (like ESLint) - CodeLens — "Run T3 (Tests)" above test files, "Run T1/T4" above source files - Command palette — 13 commands: setup, gate, forge, metrics, report, memory recall, PRD, hooks, benchmark - Status bar — gate pass rate with color coding, click to open metrics - File watcher — auto-refreshes dashboard when telemetry updates

```bash

🇨🇳 中文文档镜像 AI 翻译 2026-06-07
英文原文章节由系统翻译为中文摘要,便于快速理解。完整原文见上方 "📑 README 深度解析"。
📌 简介

**项目简介**:SkillFoundry 是一个 AI 驱动的代码生成工具,能够将需求转化为可测试、生产就绪的代码,并通过质量门控确保 AI 无法跳过。

⚡ 功能介绍

**功能介绍**:v5.17.0 版本新增 Codebase Comprehension Pre-Flight(Code Map)功能,提供代码结构的图表,帮助 AI 在编写代码前了解代码结构。同时,提到了 API 限制等功能。

📋 环境依赖

**环境依赖与系统要求**:无

🛠 安装步骤(Docker/pip/源码)

**安装步骤**:快速安装 SkillFoundry,支持全栈式部署,包括 npm、Docker、源码等方式。支持连接 Claude Code、Copilot、Cursor、Codex 等 AI 平台。

🚀 使用教程

**使用教程**:快速开始使用 SkillFoundry,包括安装、设置、创建 PRD、forge 生成代码等步骤。支持 IDE 和独立 CLI 使用。

⚙️ 配置说明(含 MCP / env)

**配置说明**:配置 SkillFoundry,包括 MCP、环境变量、关键参数等设置。支持多种部署方式,包括 npm 全局安装、Docker 等。

🔌 API 说明

**API/接口说明**:SkillFoundry CLI 的 API 文档,包括 23 个原生命令和 64 个技能。支持独立 CLI 使用。

🔄 工作流/模块

**工作流 / 模块说明**:SkillFoundry 的工作流程,包括 /prd、/go、/forge 等命令。支持自动化代码生成和质量门控。

❓ FAQ 摘要

**FAQ 摘要**:无

🎯 aiskill88 AI 点评 A 级 2026-06-07

一个不错的AI工作流框架,支持多平台和质量控制

📚 实用指南(长尾问题)
适合谁
  • 需要让 Claude / Cursor 操作本地工具的 AI 工程师
  • 构建多智能体协作系统的 Agent 开发者
  • 构建企业知识库 / RAG 检索应用的团队
  • 跨境业务、多语言内容运营团队
最佳实践
  • 配置 MCP 服务器时建议使用 stdio 传输 + JSON-RPC,避免暴露公网
  • 本地部署优先选 GGUF 量化模型,节省显存并保持响应速度
  • Agent 任务先做 dry-run 验证工具调用链,再开启自主执行
常见错误
  • API key 直接提交到 git 仓库(请用 .env 并加入 .gitignore)
  • MCP 配置路径拼错或权限不足,重启 Claude Desktop 才生效
  • 显存不足直接 OOM — 优先降低 context 或换更小的量化模型
部署方案
  • CLI:直接 npm install -g / pip install,命令行调用
  • 本地部署:CPU 8GB 起,GPU 推荐 16GB+ 显存
  • 云端托管:可放在 Vercel / Railway / Fly.io 等 PaaS 平台
相关搜索
skillfoundry 中文教程skillfoundry 安装报错怎么办skillfoundry MCP 配置skillfoundry Agent 工作流skillfoundry 与同类工具对比skillfoundry 最佳实践skillfoundry 适合谁用

⚡ 核心功能

👥 适合谁
  • 需要让 Claude / Cursor 操作本地工具的 AI 工程师
  • 构建多智能体协作系统的 Agent 开发者
  • 构建企业知识库 / RAG 检索应用的团队
  • 跨境业务、多语言内容运营团队
⭐ 最佳实践
  • 配置 MCP 服务器时建议使用 stdio 传输 + JSON-RPC,避免暴露公网
  • 本地部署优先选 GGUF 量化模型,节省显存并保持响应速度
  • Agent 任务先做 dry-run 验证工具调用链,再开启自主执行
⚠️ 常见错误
  • API key 直接提交到 git 仓库(请用 .env 并加入 .gitignore)
  • MCP 配置路径拼错或权限不足,重启 Claude Desktop 才生效
  • 显存不足直接 OOM — 优先降低 context 或换更小的量化模型

👥 适合人群

自动化工程师和运维人员项目经理和业务分析师希望减少重复性工作的专业人士数字化转型团队

🎯 使用场景

  • 自动化日常重复性工作,将精力集中于创造性任务
  • 构建数据采集 → 处理 → 输出的完整自动化管线
  • 实现跨平台、跨系统的数据流转和业务协同

⚖️ 优点与不足

✅ 优点
  • +MIT 协议,可免费商用
  • +大幅减少重复性人工操作
  • +可视化流程,清晰直观
  • +可扩展性强,支持复杂场景
⚠️ 不足
  • 初始配置和调试需投入一定时间
  • 强依赖外部服务的稳定性
  • 复杂场景需具备一定技术基础
⚠️ 使用须知

AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。

建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。

📄 License 说明

✅ MIT 协议 — 最宽松的开源协议之一,可自由商用、修改、分发,仅需保留版权声明。

🔗 相关工具推荐

📚 相关教程推荐
📰 相关 AI 新闻
🍿 AI 圈相关吃瓜
🗺️ 相关解决方案
🧩 你可能还需要
基于当前 Skill 的能力图谱,自动补全的工具组合

❓ 常见问题 FAQ

skillfoundry 是一款TypeScript开发的AI辅助工具。开源AI工作流:AI engineering framework with quality gates, persistent memory, and multi-platfo。⭐10 · TypeScript 主要应用场景包括:AI工程和工作流自动化。
💡 AI Skill Hub 点评

AI Skill Hub 点评:技能工厂 的核心功能完整,质量良好。对于自动化工程师和运维人员来说,这是一个值得纳入个人工具库的选择。建议先在非生产环境试用,再逐步推广。

⬇️ 获取与下载
⬇ 下载源码 ZIP

✅ MIT 协议 · 可免费商用 · 直接从 aiskill88 服务器下载,无需跳转 GitHub

📚 深入学习 技能工厂
查看分步骤安装教程和完整使用指南,快速上手这款工具
🌐 原始信息
原始名称 skillfoundry
原始描述 开源AI工作流:AI engineering framework with quality gates, persistent memory, and multi-platfo。⭐10 · TypeScript
Topics aitypescript工作流
GitHub https://github.com/samibs/skillfoundry
License MIT
语言 TypeScript
🔗 原始来源
🐙 GitHub 仓库  https://github.com/samibs/skillfoundry 🌐 官方网站  https://skillfoundry.work

收录时间:2026-06-07 · 更新时间:2026-06-08 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。