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skill-system-foundry技能系统铸造厂

Agent Skill

skill-system-foundry 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

447

周安装

19

GitHub Stars

1

下载量

157
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:skill-system-foundry(技能系统铸造厂)
来源仓库:https://github.com/milanhorvatovic/skill-system-foundry
仓库路径:skills/skill-system-foundry
安装命令:
npx skills add https://github.com/milanhorvatovic/skill-system-foundry --skill skill-system-foundry
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/milanhorvatovic/skill-system-foundry --skill skill-system-foundry

简介

用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。

  • 支持基于关键词、任务场景或来源线索进行信息筛选与整理。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装使用。
  • 安装前需确认权限范围、维护状态及是否触发联网或文件操作。
  • skill-system-foundry 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Skill System Foundry

A meta-skill for constructing and evolving AI-agnostic skill systems.

This skill governs the creation and maintenance of a two-layer architecture: skills (with optional capabilities) and roles. All skills produced by this system follow the Agent Skills specification. They incorporate authoring best practices from official vendor guides. Role contracts align with tool integration guidance for seamless deployment across platforms.

Important: Capabilities are optional, granular sub-skills within a parent skill. Do not create capabilities by default. Only introduce them when the integrator explicitly asks for them or when the domain clearly demands decomposition (3+ distinct operations with different trigger contexts). Start with a standalone skill; evolve to router+capabilities only when justified.

Architecture Overview

The skill system follows a strict two-layer architecture — skills and roles. Dependencies flow strictly downward — never the reverse. A capability must never know it's being orchestrated. A role references skills but never other roles.

The dependency direction governs references between layers, not where orchestration begins. Two valid orchestration paths exist:

Path 1:  orchestration skill → roles → skills (with optional capabilities)
Path 2:  skill (standalone or router) → role(s) → skill's capabilities
  • Path 1 — Coordination-only skill. A lean standalone skill sequences roles across domains. Contains no domain logic.
  • Path 2 — Self-contained skill. A domain skill loads one or more roles for interactive workflow logic. The skill owns capabilities; roles provide responsibility, authority, and constraints, plus handoff rules, sequencing, and interaction patterns.

See references/architecture-patterns.md for decision checklists and constraints per path.

Each layer has a clear responsibility:

  • Skills — Canonical, AI-agnostic knowledge and logic. Conform to the Agent Skills specification. A skill handles a task directly (standalone) or optionally routes to capabilities for complex domains that warrant decomposition.
  • Roles — Canonical, AI-agnostic orchestration contracts. A role defines responsibility, authority, and constraints, plus handoff rules and workflow sequencing while composing multiple skills/capabilities.

Capabilities

Route to the appropriate capability based on the task:

CapabilityTriggerPath
skill-designCreate a skill, capability, role, or manifest; decide architecture; write descriptionscapabilities/skill-design/capability.md
validationValidate a skill against the spec; audit system consistencycapabilities/validation/capability.md
migrationMigrate flat skills to the router+capabilities patterncapabilities/migration/capability.md
bundlingPackage a skill as a zip bundle for distributioncapabilities/bundling/capability.md
deploymentDeploy to tools; set up wrappers or symlinks; use tool-specific extensionscapabilities/deployment/capability.md

Read only the relevant capability file. Do not load multiple capabilities unless the task explicitly spans them.

Shared Resources

Shared resources live at the skill root and are referenced by capabilities via relative paths. Individual files are listed in each capability's Key Resources section — the router indexes directories, capabilities index files.

references/ — Guidance loaded on demand by capabilities

Cross-cutting reference material shared across capabilities. Capabilities reference these by relative path.

assets/ — Templates for scaffolding new components

Skill, capability, role, and manifest templates copied and filled in when creating new components.

scripts/ — Validation, scaffolding, and bundling tools

Four entry points (validate_skill.py, audit_skill_system.py, scaffold.py, bundle.py) and shared library modules. All entry points support --json for machine-readable output.

Core Principles

1. Agent Skills Specification Compliance

All skills must conform to the Agent Skills specification (agentskills.io). Every registered skill directory contains a SKILL.md with valid YAML frontmatter. The name field matches the parent directory name, lowercase + hyphens only, max 64 chars. The description field is max 1024 chars and describes both what the skill does and when to trigger it. Third-person voice is a foundry convention, not a spec requirement.

Note: capabilities are discovery-internal sub-skills. Their entry point is capability.md. Capability frontmatter is optional (use it when portability/promotion to standalone is likely).

Progressive disclosure is respected at all levels:

  • Level 1: Metadata (~100 tokens) — name + description, always in context
  • Level 2: Instructions (<5000 tokens / recommended max 500 lines) — loaded when triggered
  • Level 3: Resources (unlimited) — scripts, references, assets, on demand

2. Token Economy

Discovery tokens are always present and expensive. Execution tokens are only paid when activated. Register one skill per domain, not one per capability. Keep router SKILL.md files lean. Push detail into capabilities or references. Prefer a standalone skill until the domain justifies capabilities.

3. Conciseness

The model is already smart. Only add context it doesn't already have. Challenge each piece of information: "Does the model really need this explanation?" See references/authoring-principles.md for detailed guidance.

4. Degrees of Freedom

Match specificity to the task's fragility. High freedom for flexible tasks, low freedom for fragile operations. See references/authoring-principles.md.

5. Write Once, Adapt Everywhere

Domain knowledge is authored exactly once in the canonical layer (skills and roles). When domain knowledge changes, one file changes. Tool-specific deployment pointers, if needed, are optional user-managed customizations — implemented as wrapper files or symlinks. When deploying, always ask the user which mechanism to use. See references/tool-integration.md for the decision guide.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

35.63%
按下载量换算56

Claude

30.41%
按下载量换算48

Cursor

20.29%
按下载量换算32

Gemini CLI

10.02%
按下载量换算16

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills