brain-dump-ingestion

SKILL研究检索
研究检索 未标注权限 许可证不明确

Process unstructured brain dumps, transcripts, and stream-of-consciousness notes into structured knowledge base content. Use when converting raw ideas, meeting notes, or recorded thoughts into organized documentation.

一句话选型结论

按资料字段整理

brain-dump-ingestion是研究检索类的 Agent Skill,安装方式:GitHub 仓库,权限级别未标注,许可证不明确,没有现成安装命令,需按说明手动放置 SKILL.md。技能本质是给模型读的说明书,效果取决于模型与客户端;装完先用一个小任务验证,再放进正式流程。

分类研究检索 安装方式GitHub 仓库 权限级别未标注权限 许可证许可证不明确
累计安装 未标注 本周 未标注
GitHub 星标 0 仓库 agentic-knowledge-base
下载量 未标注 技能市场下载数
权限级别 未标注权限 安装前请确认风险范围
许可证 许可证不明确 未说明

安装

GitHub 仓库
在支持 Skills 的客户端里执行,装完问一句「你有哪些技能」验证
  1. 1
    确认客户端支持

    确认你的客户端支持 Skills(Claude、Codex、Cursor 等),并升级到较新的版本。

  2. 2
    拿到技能文件

    按安装说明或仓库 README,把 SKILL.md 放到客户端的 skills 目录(一般一个技能一个文件夹)。

  3. 3
    刷新技能列表

    重新打开客户端,或刷新技能列表,让新放进来的技能被加载。

  4. 4
    验证是否生效

    问一句「你有哪些技能」,确认列表里出现它,再拿一个小任务试跑。

技能档案

研究检索
字段来自技能仓库与公开索引,中文说明由本站标注
作者 / 维护方wlfmnstr仓库 agentic-knowledge-base · 版本 未标注
宿主客户端未标注技能可被这些客户端加载
安装方式GitHub 仓库安装包 wlfmnstr/agentic-knowledge-base
权限级别未标注权限安装前请确认风险范围
许可证未说明许可证不明确,商用前请自行确认条款
仓库可用性available技能仓库当前是否可访问
最近核验未标注上游最后核验时间 · 数据更新 未标注
正文体量13.5 KBSKILL.md 原文大小,越大说明说明书写得越细

典型使用场景

3 类
按分类整理的常见用法,具体以 SKILL.md 为准
查资料并整理出处

让模型按主题查资料,并把引用来源整理成清单。

网页与文献要点提炼

把长文、论文、网页压成能直接看的要点。

竞品与行业汇总

按关键词汇总竞品动态与行业信息。

选择建议

装之前先看这几条
按条目字段给出的判断,不替你决定用不用

值得选的地方

  • 基础信息齐全,可以先按说明装一个试试。

先想清楚的地方

  • 没有标注权限级别,实际能做什么要装好后确认。
  • 许可证不明确,商用或二次分发前先到仓库确认条款。
  • 没有现成安装命令,要按安装说明或仓库 README 手动放置。
  • 没有做站内核验,内容以作者仓库为准。
  • 技能只是说明书,实际效果取决于模型与客户端,装完先用小任务试一遍。

更适合

  • 需要在研究检索场景里给模型补一套做法的人。
  • 愿意先读一遍 SKILL.md、确认它会让模型做什么的人。

不太适合

  • 对许可证要求很严、必须明确可商用的人。
  • 只想装完就自动变强、不打算看说明书的人。

同类对比

6 个同类
同分类里挑最接近的几条,字段以各自详情页为准
技能权限级别安装方式累计安装宿主客户端安装命令
brain-dump-ingestion当前 未标注权限 GitHub 仓库 未标注 未标注 无
寻找技能 浏览器控制 GitHub 仓库 3120.0 万 Codex、Claude、Cursor 有
自我改进 Agent 接触敏感数据 ClawHub 市场 1646.4 万 OpenClaw 有
灵魂追踪 联网访问 GitHub 仓库 758.9 万 Codex、Claude、Cursor 有
自我完善 联网访问 ClawHub 市场 682.9 万 OpenClaw 有
微软代工厂 调用外部服务 GitHub 仓库 661.4 万 Codex、Claude、Cursor 有

SKILL.md 全文

13.5 KB
模型实际读到的说明书原文,来自技能仓库

Brain Dump Ingestion & Processing

Process unstructured brain dumps—transcribed audio, stream-of-consciousness writing, rambling thoughts—into structured, valuable knowledge base content while preserving the original context.

Core Philosophy

Principle 1: Preserve the Original
Never discard the raw brain dump. It contains context, emotion, and connections that structured notes may lose.

Principle 2: Isolate Before Integrating
Use a landing zone workflow to prevent pollution of the mature knowledge base. Content must be reviewed and refined before integration.

Principle 3: Extract Atomic Ideas
Break large dumps into focused, single-topic pieces that can be independently valuable and linked together.

Principle 4: Maintain Traceability
Always link processed content back to its source brain dump for future reference.


Landing Zone Architecture

Three-Tier Content Structure

src/content/
├── brain-dumps/       # Raw, unprocessed dumps (preserved forever)
│   └── {date}-{slug}.mdx
├── staging/           # Processed but not yet integrated content
│   └── {topic}-{slug}.mdx
└── docs/              # Production knowledge base (mature content)
    └── {category}/{slug}.mdx

Content Flow

1. Brain Dump → brain-dumps/     (raw input, timestamped)
2. Processing → staging/          (structured, tagged, ready for review)
3. Integration → docs/            (refined, linked, published)

Schema Design

brain-dumps collection:

{
  title: string           // Brief description of the dump
  date: Date              // When it was captured
  source: string          // 'audio' | 'text' | 'transcript' | 'conversation'
  duration?: string       // For audio/video sources
  tags?: string[]         // Rough categorization
  processed: boolean      // Whether staging content exists
  stagedItems?: string[]  // Links to staging entries created from this
}

staging collection:

{
  title: string           // Extracted topic/concept
  description: string     // Clear summary of content
  sourceFile: string      // Reference back to brain dump
  extractedDate: Date     // When this was extracted
  targetCategory?: string // Suggested docs category
  status: 'new' | 'reviewed' | 'ready' | 'integrated'
  tags: string[]          // Refined tags
  relatedTopics?: string[] // Connections to other content
  integrationNotes?: string // Notes for integration
}

Processing Workflow

Step 1: Analyze the Brain Dump

When presented with a brain dump, first understand its characteristics:

Content Type:
- Stream of consciousness (free-flowing thoughts)
- Narrative (story-like explanation)
- Problem-solving (working through an issue)
- Knowledge capture (explaining something you know)
- Ideation (brainstorming and exploring)
- Meeting notes (conversation transcript)

Density Indicators:
- How many distinct topics are covered?
- What's the primary focus vs. tangential thoughts?
- Are there clear pivots or topic changes?
- What's the signal-to-noise ratio?

Extraction Potential:
- What could become standalone documentation?
- What are the key insights or decisions?
- What should be cross-referenced?
- What's contextual fluff vs. valuable content?

Step 2: Save the Raw Dump

Always start by preserving the original in brain-dumps/:

---
title: "Quick thoughts on authentication patterns"
date: 2025-11-05T14:30:00Z
source: "audio"
duration: "20 minutes"
tags: ["authentication", "security", "ideas"]
processed: false
---

[Raw content exactly as provided, no editing]

File naming: YYYY-MM-DD-brief-slug.mdx

Step 3: Extract Atomic Topics

Identify distinct concepts that could become independent documentation:

Extraction Criteria:
- ✅ Concept can stand alone without full context
- ✅ Topic is focused on a single idea
- ✅ Content provides value independent of other extracts
- ✅ Clear title can be written without "context dump"

Example Extraction:
From a 20-minute ramble about auth, you might extract:
1. "JWT vs Session Tokens - Decision Matrix"
2. "Password Reset Flow Security Concerns"
3. "OAuth Integration Gotchas"
4. "User Session Management Best Practices"

Step 4: Create Staging Entries

For each extracted topic, create a structured entry in staging/:

---
title: "JWT vs Session Tokens - Decision Matrix"
description: "Comparison of JWT and session-based authentication with decision criteria for choosing between them"
sourceFile: "brain-dumps/2025-11-05-auth-thoughts.mdx"
extractedDate: 2025-11-05T15:00:00Z
targetCategory: "security"
status: "new"
tags: ["authentication", "jwt", "sessions", "security"]
relatedTopics: ["oauth-integration", "session-management"]
---

## Overview

[Extracted and structured content]

## Key Considerations

[Organized insights from the brain dump]

## Decision Criteria

[Structured decision matrix]

## Source Context

This content was extracted from a brain dump recorded on 2025-11-05.
See the [original brain dump](/brain-dumps/2025-11-05-auth-thoughts) for full context.

File naming: {topic-slug}.mdx (no date prefix, describes the content)

Step 5: Update Source References

Update the original brain dump to track what was extracted:

---
processed: true
stagedItems:
  - "staging/jwt-vs-sessions.mdx"
  - "staging/password-reset-security.mdx"
  - "staging/oauth-gotchas.mdx"
---

Content Structuring Techniques

From Stream to Structure

Identify Patterns:
- Repeated phrases → key concepts
- "So basically..." → summary moments
- "The problem is..." → problem statements
- "What we should do..." → action items/recommendations
- "I learned that..." → key insights
- Questions asked → important considerations

Extract Hierarchies:
- Main topic: What's the overarching theme?
- Subtopics: What distinct areas are covered?
- Details: What specific examples or explanations support each subtopic?

Clean Up Narrative Artifacts:
- Remove: "um", "like", "you know", filler words
- Convert: First person narrative → clear documentation
- Preserve: Unique phrasing that adds clarity or insight
- Keep: Examples and analogies that illustrate concepts

Structure Templates

For Conceptual Content:

## Overview
[What is this concept?]

## Key Characteristics
[What makes this important/unique?]

## Use Cases
[When should this be used?]

## Considerations
[What should you keep in mind?]

## Related Concepts
[What connects to this?]

For Decision/Problem Content:

## Problem Statement
[What problem are we solving?]

## Context
[Why does this matter?]

## Options Considered
[What are the alternatives?]

## Decision Criteria
[How do we choose?]

## Recommendation
[What's the suggested approach?]

## Trade-offs
[What are we accepting/rejecting?]

For How-To/Process Content:

## What This Does
[Clear outcome description]

## When to Use This
[Applicability]

## Prerequisites
[What you need first]

## Steps
[Ordered process]

## Common Issues
[Troubleshooting]

## Related Processes
[Connected workflows]

Integration Readiness

Staging Review Checklist

Before content can move from staging/ to docs/, verify:

Content Quality:
- [ ] Title is clear and descriptive
- [ ] Description accurately summarizes content
- [ ] Content is well-structured with appropriate headings
- [ ] Grammar and clarity are good (not perfect, but readable)
- [ ] Examples are included where helpful
- [ ] Technical accuracy is verified

Categorization:
- [ ] Target category is identified
- [ ] Tags are relevant and consistent with existing taxonomy
- [ ] Related topics are identified and can be linked

Integration Planning:
- [ ] No duplicate content exists in docs
- [ ] If merging with existing doc, plan is clear
- [ ] If new doc, navigation placement is identified
- [ ] Cross-links to related content are identified

Traceability:
- [ ] Source brain dump is referenced
- [ ] Extraction date is recorded
- [ ] Context is preserved if needed

Status Progression

new → reviewed → ready → integrated
  • new: Just extracted, needs initial review
  • reviewed: Content quality verified, needs categorization
  • ready: Integration plan complete, ready to move
  • integrated: Successfully moved to docs, can be archived

Best Practices

Do's

  • ✅ Save everything: Even if a brain dump seems useless now, context may matter later
  • ✅ Extract generously: Better to have multiple small staged pieces than one large dump
  • ✅ Link bidirectionally: Brain dump → staging → docs, and back
  • ✅ Use timestamps: Helps understand evolution of thinking
  • ✅ Tag broadly in dumps: Narrow down tags during staging
  • ✅ Keep voice where valuable: If the narrative style adds clarity, preserve it
  • ✅ Note uncertainties: Mark areas that need verification or expansion
  • ✅ Cross-reference: Identify connections to existing content

Don'ts

  • ❌ Don't edit brain dumps: They're raw archives, keep them authentic
  • ❌ Don't rush to docs: Let content mature in staging
  • ❌ Don't lose context: Always maintain traceability
  • ❌ Don't over-structure: If narrative flow helps, keep it
  • ❌ Don't delete tangents: They might matter later, just don't extract them
  • ❌ Don't force atomicity: Some concepts need more context
  • ❌ Don't ignore duplicates: Check for existing content before creating new

Common Patterns

Pattern 1: Exploratory Ramble

Characteristics: Stream of consciousness, multiple topic pivots, thinking out loud

Approach:
- Extract 3-5 distinct mini-topics
- Create one "exploration notes" staging entry with multiple sections
- Link to related existing docs for context
- Mark areas that need deeper exploration

Pattern 2: Deep Dive

Characteristics: Sustained focus on one topic, thorough coverage, examples included

Approach:
- Extract as comprehensive single document
- Structure carefully with clear hierarchy
- May become primary doc for that topic
- Verify technical accuracy before marking ready

Pattern 3: Meeting Notes

Characteristics: Conversational, decisions made, action items, multiple participants

Approach:
- Save full transcript in brain-dumps
- Extract decisions as separate staging entries
- Pull out action items with owners
- Create context document linking all pieces

Pattern 4: Problem Solving

Characteristics: Working through a specific issue,試行錯誤, eventual resolution

Approach:
- Extract the problem statement
- Extract the solution/approach
- Consider extracting "what didn't work" as gotchas
- Link to related troubleshooting docs

Pattern 5: Knowledge Transfer

Characteristics: Explaining something you know, teaching narrative, examples rich

Approach:
- Structure as tutorial or guide
- Extract conceptual overview separately from how-to
- Pull out examples as separate entries if reusable
- Consider creating a series of linked docs


Tools & Commands

Expected Supporting Commands

/ingest [source] - Complete ingestion workflow
- Prompts for brain dump content
- Saves to brain-dumps/
- Analyzes and suggests extractions
- Creates staging entries
- Updates references

/review-staging [file] - Review staged content
- Validates content quality
- Checks for duplicates
- Suggests categorization
- Identifies integration opportunities
- Updates status

/integrate-content [staging-file] - Move from staging to docs
- Checks integration readiness
- Handles placement in docs/
- Creates cross-links
- Updates all references
- Marks as integrated


Quick Reference

File Naming Conventions

brain-dumps:  YYYY-MM-DD-brief-description.mdx
staging:      topic-focused-slug.mdx
docs:         category/descriptive-slug.mdx

Frontmatter Quick Copy

# Brain Dump
---
title: "Brief description of dump"
date: 2025-11-05T14:30:00Z
source: "audio" | "text" | "transcript"
tags: ["broad", "tags"]
processed: false
---

# Staging
---
title: "Focused topic title"
description: "Clear one-sentence summary"
sourceFile: "brain-dumps/YYYY-MM-DD-slug.mdx"
extractedDate: 2025-11-05T15:00:00Z
targetCategory: "suggested-category"
status: "new"
tags: ["specific", "tags"]
relatedTopics: ["other-topic-slugs"]
---

Processing Checklist

  1. [ ] Save raw dump to brain-dumps/
  2. [ ] Analyze content type and density
  3. [ ] Identify atomic topics (3-7 typical)
  4. [ ] Create staging entry for each topic
  5. [ ] Structure content appropriately
  6. [ ] Add source references
  7. [ ] Update brain dump with processed: true
  8. [ ] Review and refine staging entries
  9. [ ] Plan integration approach
  10. [ ] Move to docs when ready

Success Metrics

You're doing this well when:

  • ✅ No valuable thoughts are lost
  • ✅ Original context is always accessible
  • ✅ Staged content is focused and atomic
  • ✅ Integration path is clear for each piece
  • ✅ No pollution of main docs with half-baked ideas
  • ✅ Connections between concepts are identified
  • ✅ Content evolves from raw → refined naturally
  • ✅ You can find the source of any extracted content

Brain dumps are the raw material of knowledge. This skill transforms chaos into clarity while honoring the messiness of creative thinking.

常见问题

5 问
答案由本站依据条目字段整理
brain-dump-ingestion怎么安装?

没有现成安装命令:按安装说明或仓库 README,把 SKILL.md 放进客户端的 skills 目录(一般一个技能一个文件夹)。

brain-dump-ingestion支持哪些客户端?

资料没有标注宿主客户端,但只要客户端支持 Skills(Claude、Codex、Cursor 等),一般都能加载。

brain-dump-ingestion权限高吗,安全吗?

权限级别为未标注权限。安装前先看它会读取或写入哪些内容。

brain-dump-ingestion收费吗?

本站不代收费用,也没有标注具体价格。是否收费取决于技能本身和所用的模型或客户端,正式使用前按作者说明确认。

brain-dump-ingestion用什么许可证?

许可证标注为 未说明(许可证不明确)。商用或二次分发前请到仓库确认条款原文。

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技能内容以作者仓库为准;分类、权限级别与许可证状态的中文说明为中文整理,最近核验 未标注。