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knowledge-capture知识获取

Agent Skill

knowledge-capture 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

282

周安装

12

GitHub Stars

25

下载量

99
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:knowledge-capture(知识获取)
来源仓库:https://github.com/noobygains/godmode
仓库路径:skills/knowledge-capture
安装命令:
npx skills add https://github.com/noobygains/godmode --skill knowledge-capture
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/noobygains/godmode --skill knowledge-capture

简介

knowledge-capture 用于查找、检索和筛选相关信息,适合基于关键词快速定位内容。

  • 适用于 Codex、Claude、Cursor 和 Gemini CLI,支持多种任务场景下的信息聚合。
  • 可通过来源仓库和原始 README 进一步验证功能细节。
  • 安装前应确认是否会触发联网、命令执行或文件读写操作。
  • 建议在测试环境中验证后再用于关键知识管理任务。

SKILL.md

Knowledge Capture

Overview

Every substantial interaction yields signal. A debugging session exposes a hidden codebase convention. A user correction reveals a preference. A failed plan uncovers a blind spot. Recording these observations is not overhead -- it is compound interest on capability.

Core principle: Solving a difficult problem without recording what you discovered means solving it from zero next time.

No exceptions. No workarounds. No shortcuts.

The Prime Directive

EXTRACT INSIGHT FROM EVERY MEANINGFUL INTERACTION

An interaction that ends without reflection is a wasted investment. You possessed the context, found the answer, observed what succeeded -- then discarded all of it.

No excuses:

  • Do not skip capture because the task felt "routine"
  • Do not skip capture because you are "about to switch contexts"
  • Do not skip capture because the lesson seems "self-evident"
  • What feels obvious with full context becomes invisible from a cold start

Reflect. Distill. Persist. Full stop.

When to Use

Mandatory after:

  • Delivering a complex feature (which patterns proved effective?)
  • Resolving a stubborn defect (what was the root-cause signature?)
  • Receiving review feedback that surfaced issues (what should differ next time?)
  • Being corrected by the user (new preference discovered)
  • Revising a plan significantly (what was misjudged?)
  • Discovering a codebase convention through trial and error (spare the next session that journey)

Exceptions (confirm with the human):

  • One-line trivial fixes
  • Interactions that produced no new information
  • When the user explicitly declines

Tempted to think "there is nothing to capture here"? Pause. That is rationalization.

The Entry Protocol

AFTER completing any meaningful task:

1. REFLECT: What succeeded? What failed? What was unexpected?
2. DISTILL: What generalizable pattern or insight emerges?
3. DEDUPLICATE: Is this already recorded? Does it contradict something stored?
4. PERSIST: Write it to the appropriate memory file with date and context
5. PRUNE: Remove any prior entries that newer evidence invalidates

Omit any step = insight permanently lost

The Capture Lifecycle

digraph capture_lifecycle {
    rankdir=TB;
    node [shape=box style=filled];

    task [label="Meaningful Task\nCompleted" fillcolor=lightyellow shape=doublecircle];

    reflect [label="REFLECT\nWhat occurred?\nWhat surprised me?" fillcolor="#ccccff"];
    distill [label="DISTILL\nAbstract the insight\nfrom the specifics" fillcolor="#ccccff"];
    exists [label="Already\nrecorded?" shape=diamond fillcolor="#fff3e0"];
    conflicts [label="Contradicts\nan existing entry?" shape=diamond fillcolor="#fff3e0"];
    persist [label="PERSIST\nSave to memory\nwith date + context" fillcolor="#ccffcc"];
    prune [label="PRUNE\nRemove outdated\nentry" fillcolor="#ffcccc"];
    cluster [label="CLUSTER\n3+ related insights?\nForm a conviction" fillcolor="#ccffcc"];
    promote [label="PROMOTE\nHigh-confidence conviction\n-> CLAUDE.md rule" fillcolor="#e8f5e9"];
    skip [label="Skip\n(already known)" fillcolor="#eeeeee"];

    task -> reflect;
    reflect -> distill;
    distill -> exists;
    exists -> skip [label="yes, identical"];
    exists -> conflicts [label="no"];
    conflicts -> prune [label="yes"];
    prune -> persist;
    conflicts -> persist [label="no"];
    persist -> cluster;
    cluster -> promote [label="3+ confirmations"];
    cluster -> task [label="await further\nevidence" style=dashed];
}

Categories of Insight

Effective Patterns

Code approaches, debugging tactics, and architectural choices that led to clean results. These are positive signals to reinforce.

Sample entry:
  Date: 2025-04-10
  Context: Built retry logic for third-party webhook delivery
  Insight: Exponential backoff with random jitter eliminated thundering-herd spikes
  Confidence: medium (validated once)

Failures and Their Remedies

What went wrong, how it was resolved, how to prevent recurrence. Failures yield the highest-signal lessons.

Sample entry:
  Date: 2025-04-12
  Context: Logging middleware silently swallowed request bodies after refactor
  Insight: Any change to middleware ordering demands a full integration test pass -- blast radius is total
  Confidence: high (validated by production incident)

User Preferences

Stylistic choices, tool preferences, and conventions the user follows. Discovered through corrections and direct statements.

Sample entry:
  Date: 2025-04-13
  Context: User corrected my naming approach
  Insight: User requires camelCase for variables, PascalCase for types, and no abbreviations anywhere
  Confidence: high (direct correction)

Project-Specific Knowledge

Architecture details, hidden gotchas, critical files, tribal knowledge that lives nowhere in documentation.

Sample entry:
  Date: 2025-04-14
  Context: Spent 15 minutes searching for runtime config
  Insight: All runtime configuration lives in src/config/runtime.ts, not in .env files
  Confidence: high (verified in source)

Storage Mechanism

Leverage Claude Code's memory system: ~/.claude/projects/[project]/memory/

Memory File Taxonomy

FilePurposeExample Entry
effective-patterns.mdCode approaches and strategies that produced clean outcomes"Zod schemas at API boundaries catch malformed data before it propagates"
failure-analysis.mdRoot-cause patterns and diagnostic techniques"Tests passing locally but failing in CI usually indicate timezone or locale assumptions"
project-map.mdArchitecture, key files, and codebase conventions"Database migrations reside in db/migrations/ and execute via pnpm db:migrate"
human-preferences.mdStylistic choices, tooling preferences, and conventions the user enforces"User demands explicit error types; string-based errors are rejected"

Entry Structure

Every captured insight must include:

### [Concise title]
- **Date:** YYYY-MM-DD
- **Context:** What was happening when this was discovered
- **Insight:** The generalized takeaway
- **Confidence:** low / medium / high
- **Confirmations:** Number of times this has been validated

Deduplication Protocol

Before writing a new entry, scan the target memory file. If the insight already exists:

  • Same insight, same confidence level -> skip entirely
  • Same insight, elevated confidence -> update confidence and increment confirmation count
  • Contradicting insight -> replace the old entry, note the contradiction

The Maturation Cycle

Isolated insights become powerful when they converge into convictions.

From Insight to Conviction

Insight 1: "This project validates forms with zod" (medium confidence)
Insight 2: "API route handlers also validate payloads with zod" (medium confidence)
Insight 3: "User corrected me for using manual validation instead of zod" (high confidence)

    Converge into conviction

Conviction: "This project ALWAYS validates at every boundary using zod"
Confidence: high (confirmed across 3 interactions)

From Conviction to Rule

When a conviction reaches high confidence (confirmed across 3+ interactions), it becomes eligible for promotion to a project CLAUDE.md rule:

Conviction: "This project always validates with zod"
  -> Confirmed 3+ times
  -> Propose to user: "I have observed that this project consistently
    uses zod for validation. Should I codify this as a project rule in CLAUDE.md?"
  -> User approves -> add to CLAUDE.md

Never auto-promote. Always obtain user consent before adding entries to CLAUDE.md. The human is the final authority on permanent rules.

Session-Start Review

When beginning a new session on a project:

  1. Read all memory files for the project
  2. Identify clusters of related insights that have not been synthesized
  3. Flag entries that may be stale (old date, low confidence, never reconfirmed)
  4. Surface convictions ready for promotion

Confidence Tiers

TierMeaningOriginAction
LowTentative signalSingle occurrence, unconfirmedRecord, watch for confirmation
MediumProbable patternConfirmed twice, or one strong indicatorRecord, apply when relevant
HighEstablished truthConfirmed 3+ times, or explicit user declarationRecord, apply consistently, consider promotion

Cognitive Traps

RationalizationTruth
"There is nothing to capture here"Every task produces signal. You are not examining closely enough.
"I will recall this naturally"You will not. The next session starts with a blank slate. Memory files are your continuity.
"Too minor to bother recording"Minor insights accumulate. Three small observations become one powerful conviction.
"It is self-evident"Self-evident to you now, with full context. Not self-evident when cold-starting next week.
"Recording takes too long"Thirty seconds to write an entry. Thirty minutes to rediscover the same insight.
"The user did not request this"They requested quality. Learning from experience IS how quality improves over time.
"Memory files are getting cluttered"That is a pruning problem, not a recording problem. Prune more; never stop capturing.
"This only applies to this one project"Project-specific knowledge is the MOST valuable kind. That is precisely why it is stored per-project.

Guardrails

Prohibited actions:

  • Skipping reflection after a difficult debugging session
  • Storing entries without date and context (undated insights decay)
  • Auto-adding rules to CLAUDE.md without user approval
  • Recording the same insight twice without deduplication
  • Retaining entries that newer evidence contradicts
  • Recording implementation minutiae instead of generalizable patterns

Required actions:

  • Reflect after completing any significant work
  • Check memory before persisting (deduplicate)
  • Attach confidence levels to every entry
  • Obtain user consent before promoting convictions to CLAUDE.md rules
  • Prune entries invalidated by newer evidence
  • Organize entries by topic, not chronologically

Integration

This skill feeds INTO other skills:

  • godmode:fault-diagnosis -- Historical failure analysis informs current troubleshooting
  • godmode:pattern-matching -- Captured conventions reinforce code conformity
  • godmode:test-first -- Past test failures shape future test strategy
  • godmode:task-planning -- Past plan failures prevent repeating misjudgments
  • godmode:quality-enforcement -- Captured quality patterns elevate the baseline

This skill is fed BY other skills:

  • godmode:review-response -- Review feedback becomes captured insights
  • godmode:completion-gate -- Verification failures become recorded lessons
  • godmode:comprehension-check -- Walkthrough findings become stored observations
  • godmode:task-runner -- Plan execution reveals what works and what does not

The virtuous cycle:

Work -> Capture -> Persist -> Apply -> Work better -> Capture more

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

35.83%
按下载量换算35

Claude

28.41%
按下载量换算28

Cursor

18.76%
按下载量换算19

Gemini CLI

8.82%
按下载量换算9

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。

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