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knowledge-forge知识锻造

Agent Skill

knowledge-forge 用于查找、检索和筛选相关信息,适合在 OpenClaw 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

11,268

周安装

484

GitHub Stars

1

下载量

3,949
OpenClaw

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

MIT-0

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:knowledge-forge(知识锻造)
来源仓库:https://github.com/angjustinl/knowledge-forge
安装命令:
openclaw skills install knowledge-forge
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install knowledge-forge

简介

知识锻造工具将原始经验或文档转化为结构化、可复用的认知资产,便于跨场景迁移。

  • 适合经验沉淀、案例转化或知识资产化需求,常用于商业分析、项目复盘等场景。
  • 通过输入文本或文档触发处理流程,输出标准化知识条目供后续检索与使用。
  • 需确认输入数据来源的合法性,避免将敏感或未授权内容纳入结构化知识库。
  • 维护时注意版本控制,确保知识资产的更新与原始材料变更保持同步。

SKILL.md

name
knowledge-forge
description
>-

Knowledge Forge

Forge raw experience into transferable cognitive assets using a 4-step conversion engine.

Core Concept

Experience is abundant. Answers are scarce.

Most experts are strong inside their own world. But when they open a document or step on stage, others can't follow. The problem is not lack of experience -- it's that experience has not been modeled.

A modeled experience is one that has been abstracted into a structure that transfers across contexts. This skill performs that transformation.

Conversion Engine

When the user provides raw material (a case study, personal summary, business document, draft speech, or any form of experience narrative), execute these 4 steps sequentially:

Step 1: Perspective Flip -- "My experience" -> "Your challenge"

Identify what the user accomplished, then reframe it as a universal challenge the audience faces.

  • Extract the core problem the user solved
  • Abstract it away from domain-specific details
  • Restate it as a challenge the target audience recognizes in their own work
  • The audience should think "yes, I face this too" -- not "interesting, but that's your job"

Key question to answer: "What struggle does the audience already have that this experience speaks to?"

For modeling patterns and examples, see modeling-patterns.md.

Step 2: Experience Modeling -- Specific story -> Transferable structure

The raw experience is a story. Transform it into a model -- an abstraction that works across scenarios.

  • Find the structural pattern hidden in the specific case
  • Name it with a memorable, compact label (e.g., "The 100->10->1 Funnel")
  • Validate: does the model apply to at least 2-3 other domains the audience cares about?

Key question to answer: "What is the underlying structure that makes this experience work -- independent of the specific domain?"

For modeling archetypes and before/after examples, see modeling-patterns.md.

Step 3: Narrative Reconstruction

Rebuild the narrative using this sequence:

  1. Challenge alignment -- Present the universal challenge so the audience enters the tension. Spend substantial space here. Make old/obvious answers visibly insufficient.
  2. Model reveal -- Introduce the abstracted model as the new lens. Emphasize the shift in thinking (role change, mental model upgrade), NOT tool details or step-by-step procedures.
  3. Evidence from experience -- Use the original story as proof that the model works, not as the centerpiece.

Principle: Present the "Dao" (the judgment behind decisions), not the "Shu" (the operational steps). Tools and procedures are forgettable; the cognitive shift is what transfers.

For techniques on designing cognitive gaps, see challenge-design.md.

Step 4: Anchor Design -- The one sentence they carry away

Design a single, specific, portable judgment -- the anchor.

Requirements for a good anchor:

  • Specific -- not a vague platitude ("work smarter") but a concrete reframing ("AI doesn't save you time -- it changes which game you're playing")
  • Sticky -- compact enough to remember and repeat
  • Generative -- triggers new thinking when applied to the audience's own context

Key question to answer: "If the audience forgets everything else, what is the ONE sentence that, by itself, changes how they think?"

Place the anchor at the structural climax of the output. It must feel earned -- a culmination of the challenge and model, not a disconnected slogan.

Output

After completing the 4 steps internally, produce the final output.

Determining Output Format

If the user specifies a format, use it. Otherwise, infer from context:

SignalFormat
"presentation", "talk", "speech", "share"Presentation Script
"course", "training", "teach", "workshop"Course Outline
"article", "post", "essay", "document"Article / Document
"summary", "card", "one-pager", "memo"Knowledge Card
Ambiguous or unspecifiedKnowledge Card (default)

For output templates and structural guidance, see output-formats.md.

Output Structure

Every output, regardless of format, must contain these elements:

  1. The Challenge -- The universal problem, stated in the audience's language
  2. The Model -- The transferable structure, with a memorable label
  3. The Evidence -- The original experience, reframed as proof of the model
  4. The Anchor -- The one sentence to carry away

Transformation Log

After the main output, append a brief ## Transformation Log showing the key decisions made during conversion:

## Transformation Log

- **Perspective Flip**: [Original framing] -> [Audience-facing challenge]
- **Model Extracted**: [Model name and one-line description]
- **Narrative Shift**: [What was de-emphasized vs. elevated]
- **Anchor**: "[The one sentence]"

This log helps the user understand and iterate on the transformation.

适合场景

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OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

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需要根据任务场景推荐可安装能力包时

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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

补充不同宿主或平台的使用分布数据

能力 5

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

OpenClaw

94.06%
按下载量换算3,714

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

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

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