Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/BruceLanLan/augurnpx agentmods add skills/brucelanlan/augur/knowledgeWrote 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/brucelanlan/augur/knowledge)<a href="https://agentmods.dev/skills/brucelanlan/augur/knowledge"><img src="https://agentmods.dev/badge/skills/brucelanlan/augur/knowledge/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/brucelanlan/augur/knowledge"><img src="https://agentmods.dev/badge/skills/brucelanlan/augur/knowledge.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 | $0.00075 | $0.02246 |
| Opus 5.5 | $0.00030 | $0.00898 |
| Sonnet 5.5 | $0.00015 | $0.00449 |
| Haiku 4.5 | $0.00007 | $0.00225 |
Grade A, and why
augur scanned grade A with 1 finding 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 1mo 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl "http://localhost:8000/api/analyze/NVDA?pe=45&gross_margins=0.75&roe=0.85&revenue_growth=0.78§or=Technology" How it starts
The opening of the file, as written. The whole thing — 168 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Augur — 多智能体投资分析系统
系统概览
Augur 是一个 18位虚拟投资大师的多智能体分析系统。每位投资人都有独立的人格、哲学框架、行为规范和评分逻辑，系统最终用多Agent共识机制（行业加权、机制感知、相关性惩罚）汇总出集体判断。
你可以：
- 单个投资人分析 —
augur-buffett、augur-zhang-lei等独立 Skill - 多Agent共识 — 全部18位大师同时分析，给出加权共识信号
- 部署到任意平台 — Telegram、Slack、WeChat、Claude、Hermes 都支持
18位投资大师
| Skill名称 | 投资人 | 风格 | 适合场景 | 推荐模型 |
|---|---|---|---|---|
augur-buffett |
Warren Buffett | 护城河价值投资 | 蓝筹、消费、金融 | claude-sonnet-4-6 |
augur-graham |
Benjamin Graham | 深度价值/安全边际 | 低估、破净、周期底 | claude-sonnet-4-6 |
augur-munger |
Charlie Munger | 格栅理论 | 跨学科分析、复杂企业 | claude-sonnet-4-6 |
augur-lynch |
Peter Lynch | GARP/PEG | 消费成长、行业轮动 | claude-sonnet-4-6 |
augur-dalio |
Ray Dalio | 宏观/全天候 | 宏观对冲、地缘 | claude-sonnet-4-6 |
augur-soros |
George Soros | 反身性/宏观交易 | 危机、货币、做空 | claude-sonnet-4-6 |
augur-marks |
Howard Marks | 周期/逆向 | 周期底部、风险管理 | claude-sonnet-4-6 |
augur-cathie-wood |
Cathie Wood | 颠覆性创新 | AI、生物、区块链 | claude-sonnet-4-6 |
augur-fisher |
Philip Fisher | 成长股/闲聊法 | 科技、细分成长 | claude-sonnet-4-6 |
augur-thiel |
Peter Thiel | 从0到1/垄断 | 科技垄断、平台 | claude-sonnet-4-6 |
augur-arps |
ARPS | Crypto/黄金宏观 | 数字资产、避险 | claude-sonnet-4-6 |
augur-aschenbrenner |
Leopold Aschenbrenner | AI地缘政治 | AI算力、半导体 | claude-opus-4-7 |
augur-dayu |
🇨🇳 大宇 (BTCdayu) | 信息差/情绪动量 | Crypto、Meme | deepseek-v4 |
augur-duan-yongping |
🇨🇳 段永平 | 本分/极度集中 | 消费电子、平台 | deepseek-v4 |
augur-zhang-lei |
🇨🇳 张磊 (高瓴) | 结构性价值 | 消费升级、医疗 | deepseek-v4 |
augur-li-lu |
🇨🇳 李录 (喜马拉雅) | 深度价值/安全边际 | 低估蓝筹、亚洲 | claude-sonnet-4-6 |
augur-dan-bin |
🇨🇳 但斌 (东方港湾) | 品牌护城河/时代β | 中国消费品牌 | kimi-k2 |
augur-serenity |
Serenity (@aleabitoreddit) | AI/半导体供应链瓶颈 | 半导体卡脖子、CPO | claude-sonnet-4-6 |
调用方式
方式一：在 Hermes / Claude / OpenClaw 中调用
# 加载主 Skill（18位大师共识）
/skill augur
"分析 AAPL，PE=32，毛利率46%，ROE=55%，科技板块"
# 或加载单个投资人
/skill augur-buffett
"用巴菲特框架分析可口可乐 KO，当前PE=26"
/skill augur-zhang-lei
"张磊视角分析拼多多PDD，营收增速86%，毛利率62%"
What ships with it
45 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.
- buffett-principles.md 5.3 KB
- cases/analysis-reports/Alphabet-GOOGL-纳斯达克-深度分析.md 25 KB
- cases/analysis-reports/example-analysis-costco.md 18 KB
- cases/analysis-reports/example-analysis-crcl.md 20 KB
- cases/analysis-reports/MSTR-纳斯达克-深度分析.md 19 KB
- cases/analysis-reports/宁德时代-300750-深度分析.md 20 KB
- cases/analysis-reports/腾讯-00700.HK-深度分析.md 20 KB
- example-prompts.md 1.4 KB
- personas/arps-crypto-gold.md 4.9 KB
- personas/buffett.md 3.3 KB
- personas/cathie-wood.md 4.0 KB
- personas/da-yu.md 9.0 KB
- personas/dan-bin.md 4.8 KB
- personas/duan-yongping.md 5.0 KB
- personas/george-soros.md 3.5 KB
- personas/graham.md 3.2 KB
- personas/howard-marks.md 3.8 KB
- personas/leopold-aschenbrenner.md 10 KB
- personas/li-lu.md 4.8 KB
- personas/munger.md 4.2 KB
- personas/peter-lynch.md 13 KB
- personas/philip-fisher.md 4.5 KB
- personas/ray-dalio.md 9.8 KB
- personas/serenity.md 12 KB
- personas/thiel.md 12 KB
- personas/zhang-lei.md 4.7 KB
- skills/arps/SKILL.md 7.3 KB
- skills/aschenbrenner/SKILL.md 8.2 KB
- skills/buffett/SKILL.md 5.4 KB
- skills/cathie_wood/SKILL.md 6.2 KB
- skills/dalio/SKILL.md 5.7 KB
- skills/dan_bin/SKILL.md 8.1 KB
- skills/dayu/SKILL.md 7.4 KB
- skills/duan_yongping/SKILL.md 6.3 KB
- skills/fisher/SKILL.md 7.7 KB
- skills/graham/SKILL.md 7.8 KB
- skills/li_lu/SKILL.md 5.3 KB
- skills/lynch/SKILL.md 7.3 KB
- skills/marks/SKILL.md 7.0 KB
- skills/munger/SKILL.md 6.2 KB
- skills/serenity/SKILL.md 9.2 KB
- skills/soros/SKILL.md 7.1 KB
- skills/thiel/SKILL.md 7.7 KB
- skills/zhang_lei/SKILL.md 5.8 KB
- valuation-methods.md 3.5 KB
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.
- 1mo ago Changed a9def2f2e552
- 1mo ago First seen · 168 lines · 75 tokens per session scan A 00359510611a
augur is a skill published in the GitHub repository BruceLanLan/augur (636 stars, last pushed 1mo ago), licensed MIT. It adds 75 tokens to every session and 2,246 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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