Claude Code Skills Marketplace is a collection and marketplace of skills, plugins, agents, and instructions that extend Claude Code with specialized development workflows. It is for developers who want to install existing workflows or create, validate, and package their own Claude Code skills.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add daymade/claude-code-skills --skill llm-wiki-setupgit clone --depth 1 https://github.com/daymade/claude-code-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/daymade/claude-code-skills/llm-wiki-setup)<a href="https://agentmods.dev/skills/daymade/claude-code-skills/llm-wiki-setup"><img src="https://agentmods.dev/badge/skills/daymade/claude-code-skills/llm-wiki-setup/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/daymade/claude-code-skills/llm-wiki-setup"><img src="https://agentmods.dev/badge/skills/daymade/claude-code-skills/llm-wiki-setup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00106 | $0.01634 |
| Opus 5.5 | $0.00042 | $0.00654 |
| Sonnet 5.5 | $0.00021 | $0.00327 |
| Haiku 4.5 | $0.00011 | $0.00163 |
Grade A, and why
llm-wiki-setup scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 24d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LLM Wiki Setup（投研第二大脑共创）
帮用户搭一个金融投研专用 LLM Wiki（Karpathy 模式）：纯 markdown 文件 + [[wikilink]] 互联 + LLM 维护，知识随用复利。
但核心不是给一份投研模板——是引导用户把他自己的投资判断方式，提炼成他专属的 CLAUDE.md。
★ 先读这一条（这个 skill 的灵魂）
每个人用自己的语言、自己的投资偏好，建自己的 CLAUDE.md。
两个投资者看同一家公司，关注点可能完全不同——一个看「下季度订单能否超市场预期」，另一个看「管理层电话会上的语气和信心」。给他们同一份模板，就抹掉了让 wiki 有用的那个东西。
- ✅ 你的工作 = 访谈用户 → 提炼他的关注维度 → 用他的话写进 CLAUDE.md
- ❌ 你的失败 = 套一份「标准投研 schema」让他填空，或让他照抄
examples/
examples/investment-research-CLAUDE.md 是一个人长成的样子，给用户看可能性，禁止照抄。它像模板一样被搬走，这个 skill 就失败了。
不碰的红线（Karpathy 原意，别 over-engineer）
纯 markdown + wikilink。不用检索替代编译：知识靠预编译进结构化页「复利」，不是每次 query 重新检索原始文档——这是本模式相对 RAG 的根本区别，也是 Karpathy 的核心 idea。搜索层不在禁区：他的 gist 写明百来个来源靠 index.md 就够，wiki 长大后要正经搜索，并点名 qmd（本地 BM25 + 向量 + 重排）——搜的是编译好的 wiki 页，不是拿原始文档的片段替代编译。别加 knowledge graph / 自动 health-check 之类机制（社区有些版本加了，那是 over-engineer）。
机制层 vs 规则层（贯穿全程的区分）
| 内容 | 处置 | |
|---|---|---|
| 机制层 | 三层目录 + wikilink + lint + git hook | ✅ 通用工程结构，scripts/init_vault.py 直接装 |
| 规则层 | 看哪些维度 / 怎么记观点 / 要不要分析师归属 / 怎么复盘 / 要长报告还是三行 | ❌ 用户的投资大脑，访谈长出来，绝不给模板 |
机制层照抄没问题（它是 Karpathy 模式的工程卫生，跟「你怎么投资」无关）。规则层照抄 = 背叛方法论。
工作流
Phase 0 — 判断意图
- 新建 vault → Phase 1
- 已有 vault，ingest 一份源 → 直接读
references/ingest_sop.md - 已有 vault，财报后复盘某标的 →
references/fulfillment_sop.md - query → 读 vault 的
index.md+ 相关页，带 citation 综合答；好答案回填 synthesis
Phase 1 — scaffold 机制层
python scripts/init_vault.py <目标目录>
建空骨架（三层目录 + lint + hook 占位 + 空 index/log + CLAUDE 骨架）。这一步只装机制层，不写任何 schema。
Phase 2 — 访谈共创 CLAUDE.md ★核心步骤
读 references/interview.md，按它的 8 个维度一条条访谈用户，把回答用他自己的话写进 <vault>/CLAUDE.md 规则层的占位。
- 一次问一个维度，别一口气灌
- 用户不在乎的维度直接砍（极简 > 全面）
- 卡住才翻
examples/给灵感，明说「别抄，挑你戳中的」 - 自检：写好的 CLAUDE.md 像不像「这个人」？像通用模板就重来
Phase 3 — 启用防腐
cd <vault> && git init
git config core.hooksPath .githooks # local 配置，换机/重 clone 要重设
PYTHONUTF8=1 uv run --no-project --with pyyaml python3 scripts/lint-vault.py wiki # 确认绿灯
What ships with it
18 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- examples/investment-research-CLAUDE.md 13 KB
- references/counter_review.md 1.2 KB
- references/fulfillment_sop.md 2.1 KB
- references/ingest_sop.md 1.7 KB
- references/interview.md 7.1 KB
- references/prune_discipline.md 1.4 KB
- scripts/init_vault.py 5.3 KB runs code
- scripts/lint-vault.py 6.2 KB runs code
- templates/CLAUDE-skeleton.md 4.2 KB
- templates/pre-commit.snippet 1.1 KB
- templates/vault/raw/.gitkeep 0 B
- templates/vault/wiki/analysts/.gitkeep 0 B
- templates/vault/wiki/companies/.gitkeep 0 B
- templates/vault/wiki/industries/.gitkeep 0 B
- templates/vault/wiki/macro/.gitkeep 0 B
- templates/vault/wiki/synthesis/.gitkeep 0 B
- templates/vault/wiki/themes/.gitkeep 0 B
- tests/test_vault_tooling.py 8.8 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 24d ago Changed · +5 lines · -107 tokens per session 94c1b3f767c6
- 29d ago Changed · +6 tokens per session 58cd12686d28
- 1mo ago First seen · 95 lines · 207 tokens per session scan A f7768451fc01
llm-wiki-setup is a skill published in the GitHub repository daymade/claude-code-skills (1,473 stars, last pushed today), licensed MIT. It adds 106 tokens to every session and 1,634 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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