Token导航 LogoToken导航

Agent Skill · 研究检索

llm-wiki(LLM Wiki)

llm-wiki 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。

llm-wiki 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 58,406。

总安装 416周安装 17GitHub Stars 318下载 135核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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:llm-wiki(LLM Wiki)
来源仓库:https://github.com/boshu2/agentops
仓库路径:skills/llm-wiki
安装命令:
npx skills add https://github.com/boshu2/agentops --skill llm-wiki
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/boshu2/agentops --skill llm-wiki

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

llm-wiki 为提案阶段技能,基于 Andrej Karpathy 模式设计。适用于 Codex、Claude、Cursor、Gemini CLI 的外围知识归档。目前未合并进主流程,需等待 council 评审通过后方可启用。核心思想是让 LLM 自主维护外部知识 Markdown 仓库。

llm-wiki 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/llm-wiki

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/boshu2/agentops --skill llm-wiki;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

llm-wiki 怎么安装?

在终端执行 npx skills add https://github.com/boshu2/agentops --skill llm-wiki。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

llm-wiki 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

llm-wiki 需要什么权限?

权限级别是只读。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。

llm-wiki 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

llm-wiki 用的人多吗?

公开数据是累计安装 416 次,近一周安装 17 次,下载 135 次,GitHub 318 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

llm-wiki 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
llm-wiki

LLM Wiki · 本页

416318只读未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

LLM Wiki Skill (proposal)

Purpose: Keep a compounding markdown wiki of external knowledge (articles, papers, transcripts, clipped web content) maintained by an LLM so the bookkeeping is free and the knowledge accumulates. Based on Andrej Karpathy's "LLM Wiki" pattern published April 2026. See references/architecture.md for the full design rationale and how it interoperates with existing AgentOps skills. Status: PROPOSAL — not yet merged. Opened 2026-04-11 for council review. See .agents/research/2026-04-11-karpathy-llm-wiki-integration.md for the research that motivated this skill.

The core idea in one paragraph

RAG has a critical flaw: there is no accumulation. Each query re-discovers fragments from the raw source corpus. The LLM Wiki pattern replaces per-query RAG with a persistent LLM-maintained markdown wiki that sits between raw sources and the user. The LLM reads each raw doc once, extracts concepts, writes summaries, cross-links related ideas, and keeps the whole thing current. On query time, the LLM reads the already-compiled wiki — much faster, much richer, and it compounds.

Karpathy's metaphor: *"Obsidian is the IDE. The LLM is the programmer. The wiki is the codebase."* Same as AgentOps's internal-flywheel pattern, applied to external knowledge.

What this skill IS

A specification for four operations against a wiki-structured vault:

  1. ingest — process new raw source → write wiki pages + update index + log
  2. query — answer a question from wiki pages → file synthesis results back as new pages
  3. lint — periodic health-check for contradictions, stale claims, orphans, missing concepts
  4. promote — move a mature wiki page from draft to reviewed, or from wiki to authored content

What this skill is NOT

  • Not a replacement for compile — skills/compile handles internal AgentOps artifacts (.agents/learnings/ → .agents/compiled/). llm-wiki handles external source material (raw/ → wiki/). They complement; they don't overlap. See references/architecture.md for the distinction.
  • Not a replacement for research — research writes net-new research artifacts from investigation; llm-wiki organizes pre-existing external material. A research artifact can *cite* wiki pages; a wiki page can inform a research artifact.
  • Not a RAG system — it's the opposite. RAG retrieves fragments per query; LLM Wiki pre-compiles them into durable pages.
  • Not auto-scheduled — the skill defines the operations; scheduling (cron / systemd / launchd / Claude Code hooks) is the host's problem. References doc explains the 3-tier model (always-on Tier 1 local LLM, on-demand Tier 2 Claude, human Tier 3) but doesn't force a specific scheduler.

Quick Start

# Initialize the wiki layout in the current project
/llm-wiki init

# Drop a raw file into raw/articles/ then ingest it
/llm-wiki ingest raw/articles/karpathy-llm-wiki-gist.md

# Query the wiki for what we know about a topic
/llm-wiki query "what's the Karpathy LLM Wiki pattern?"

# Lint the wiki for orphans, contradictions, stale pages
/llm-wiki lint

# Promote a mature wiki page out to authored content
/llm-wiki promote wiki/concepts/llm-wiki.md --to platform-lab/patterns/llm-wiki-architecture.md

Flags

FlagDefaultDescription
`--tier 1\2\3`2Operator tier. Tier 1 writes status: draft only and never touches authored dirs. Tier 2 writes status: reviewed and can promote. Tier 3 (human) does the final promotion to MEMORY.md / authored paths.
--raw PATHraw/Override the default raw inbox location
--wiki PATHwiki/Override the default wiki output location
--dry-runoffShow what would be ingested/written without making changes
--forceoffFor lint, apply auto-fixes (orphan linking, stale flagging) instead of just reporting
--since DATE30 daysFor lint, only consider pages touched since this date
--index PATHINDEX.mdOverride the index location
--log PATHLOG.mdOverride the log location

Execution phases

Phase 1 — init

Create the wiki layout in the current project if not already present:

<project>/
├── INDEX.md                 ← content catalog
├── LOG.md                   ← append-only operation log
├── SOUL.md                  ← (optional) user identity for always-load
├── CRITICAL_FACTS.md        ← (optional) ~150-token always-load context
├── raw/                     ← Karpathy raw layer
│   ├── articles/
│   ├── papers/
│   ├── transcripts/
│   ├── screenshots/
│   └── assets/
└── wiki/                    ← Karpathy compiled layer
    ├── sources/             ← per-raw-doc summaries
    ├── entities/            ← people, orgs, products, tools
    ├── concepts/            ← ideas, frameworks, theories
    └── synthesis/           ← cross-cutting analyses

Seeds INDEX.md and LOG.md with headers; leaves SOUL.md and CRITICAL_FACTS.md as optional stubs. Writes a _CLAUDE.md (or updates existing) with the workflow sections. Idempotent — re-running on an existing layout is a no-op.

Phase 2 — ingest <raw-path>

For each raw source:

  1. Read it fully (don't skim).
  2. Write a summary page at wiki/sources/<slug>.md with frontmatter: type: source raw: <path to raw file> ingested: <ISO datetime> status: draft|reviewed # draft if Tier 1, reviewed if Tier 2
  3. Extract candidate entities (people, organizations, products, tools) → stub pages in wiki/entities/ or update existing ones. Add a backlink from the source page.
  4. Extract candidate concepts (ideas, frameworks) → stub pages in wiki/concepts/ or update existing ones.
  5. Update INDEX.md with every new page. Failure to update index = lint failure later.
  6. Append to LOG.md: YYYY-MM-DD HH:MM | <actor> | INGEST | <source slug> | <pages created> | <wikilink>
  7. If any existing wiki/synthesis/* page covers this topic, revise it to incorporate the new source; don't leave stale versions.

Tier 1 constraint: If running as --tier 1, all writes get status: draft. Tier 1 never touches wiki/synthesis/ (synthesis requires review). Tier 1 never modifies existing status: reviewed pages.

Phase 3 — query <question>

Answer a question from the wiki:

  1. Search wiki/** for relevant pages. Also check .agents/learnings/, .agents/findings/, authored content dirs if present.
  2. Synthesize an answer with citations — every non-trivial claim must cite a specific page via wikilink.
  3. If the answer is non-trivial and likely to be asked again, file it as a new wiki/synthesis/<slug>.md with the question, answer, and citations.
  4. Append to LOG.md with op QUERY.

Authored content takes precedence over wiki drafts. If a concept is already covered in .agents/findings/ or .agents/learnings/, cite that first and treat the wiki as supplementary.

Phase 4 — lint

Walk wiki/ and flag:

  1. Orphan pages — no backlinks from any other wiki page and no entry in INDEX.md
  2. Broken wikilinks — links pointing at pages that don't exist
  3. Stale pages — ingested date > --since cutoff AND the domain is evolving (user-configured stale-domain list)
  4. Contradictions — two pages making incompatible claims without a reconciliation note. Simple keyword heuristic + LLM re-read for candidates.
  5. Missing concepts — entities or concepts referenced in wiki/sources/ that don't have a dedicated page
  6. Index drift — files in wiki/** that aren't listed in INDEX.md, OR index entries that point at non-existent files

Write findings to wiki/synthesis/lint-YYYY-MM-DD.md. Don't auto-fix by default — lint reports, human or Tier 2 decides.

With --force, auto-fix:

  • Add missing index entries
  • Flag stale pages with status: stale
  • Write orphan warning comments to orphan pages

Append to LOG.md with op LINT.

Phase 5 — promote <wiki-path> --to <destination>

Move a mature wiki page to authored content:

  1. Verify the destination is a valid target (platform-lab/patterns/*, career/*, learning/*, or similar project-specific authored dirs).
  2. git mv to preserve history if possible; otherwise rewrite.
  3. Update INDEX.md — remove from wiki section, add to authored section.
  4. Find and update all backlinks to the old path.
  5. Append to LOG.md with op PROMOTE.

Tier 1 cannot promote. Tier 2 can promote within the wiki (status: draft → reviewed). Tier 3 (human) promotes out of the wiki to authored dirs.

Integration with existing AgentOps skills

SkillInteraction
skills/compileOperates on internal .agents/ artifacts → .agents/compiled/. Structurally identical to llm-wiki but for internal sources. The two wikis (wiki/ and .agents/compiled/) can cross-link but don't merge.
skills/researchCan cite wiki pages in research artifacts. Can optionally run llm-wiki ingest on material as a pre-step to writing a research artifact.
skills/forgeCan promote wiki-page concepts that have crystallized into reusable patterns into .agents/findings/ via its normal finding-registry flow.
skills/injectShould learn to inject relevant wiki/ pages alongside .agents/* content when a session starts.
skills/post-mortemPhase 2 (Extract Learnings) can be informed by recent wiki/synthesis/ pages as supporting context.
skills/pre-mortemCan query wiki/ for past context on the domain being pre-mortem'd.
skills/knowledge-activationCan activate high-value wiki pages into MEMORY.md alongside .agents/learnings/ promotions.

Relationship to the AgentOps flywheel

The AgentOps flywheel compounds internal work knowledge (what we did, what we learned, what went wrong). The LLM Wiki compounds external reading knowledge (what we read, what others figured out, what the state of the art is).

Both flywheels feed each other:

  • Wiki pages can be cited by research artifacts that feed the internal flywheel
  • Internal learnings can reference wiki pages when explaining "why we adopted approach X"
  • Findings can be enriched with wiki-sourced context

Design principle: external and internal knowledge live in separate trees (wiki/ vs .agents/) so the provenance is always clear. The two trees cross-link; they don't merge.

Scheduling (not part of this skill, but referenced)

The Karpathy pattern works best when the skill runs on a schedule, not just on-demand. The proposed 3-tier model (from the community implementations):

  • Tier 1 — always on, cheap local LLM (e.g., Gemma 4 26B A4B on a consumer GPU). Nightly ingest of raw/, draft generation, orphan detection, lint.
  • Tier 2 — on-demand expensive expert (Claude / Codex / equivalent). Weekly review of drafts, synthesis, promotion to authored content.
  • Tier 3 — human. Weekly approval of promotions to long-term memory / authored content.

See references/architecture.md for the full tier model and scheduling recommendations. The skill is tier-agnostic; the host project wires up the scheduler.

Open questions for council review

  1. Should the wiki layout (raw/, wiki/) live at project root, or under .agents/wiki/? Proposal recommendation: project root, to keep external knowledge visibly distinct from internal work.
  2. Does this overlap with skills/compile enough that the two should merge? Proposal recommendation: no — keep them separate and document the split.
  3. Should the 3-tier model be baked into the skill via a --tier flag, or left as convention? Proposal recommendation: --tier flag with Tier 2 as default.
  4. Should init also seed SOUL.md and CRITICAL_FACTS.md, or leave them optional? Proposal recommendation: seed as stubs with instructions.
  5. What's the right output contract? Post-mortem uses council/schemas/verdict.json; should llm-wiki have its own output schema for ingest/query/lint results? Proposal recommendation: yes, shape TBD by council.

References

See Also

  • skills/compile/SKILL.md — the internal-artifact compiler (structurally identical pattern, different source)
  • skills/research/SKILL.md — research artifact authoring
  • skills/forge/SKILL.md — mining knowledge from transcripts
  • skills/inject/SKILL.md — context injection at session start
  • skills/post-mortem/SKILL.md — the six-phase knowledge flywheel this skill extends externally

Proposal status: OPEN. This SKILL.md describes the intended behavior but there is no implementation yet. Council review (via /pre-mortem --preset=product) should validate the design before any code is written. If accepted, the next step is to implement the ingest and query phases first (ship them as experimental), then lint and promote once the first two are validated.

平台分布

Codex

32.76%
按下载量换算44

Claude

32.57%
按下载量换算44

Cursor

18.51%
按下载量换算25

Gemini CLI

9.41%
按下载量换算13

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills