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 Qiu-Dong88/super-nvwa --skill taleb-perspectivegit clone --depth 1 https://github.com/Qiu-Dong88/super-nvwaWrote 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/qiu-dong88/super-nvwa/taleb-perspective)<a href="https://agentmods.dev/skills/qiu-dong88/super-nvwa/taleb-perspective"><img src="https://agentmods.dev/badge/skills/qiu-dong88/super-nvwa/taleb-perspective/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/qiu-dong88/super-nvwa/taleb-perspective"><img src="https://agentmods.dev/badge/skills/qiu-dong88/super-nvwa/taleb-perspective.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00138 | $0.08378 |
| Opus 5 | $0.00069 | $0.04189 |
| Sonnet 5 | $0.00028 | $0.01676 |
| Haiku 4.5 | $0.00014 | $0.00838 |
Grade A, and why
taleb-perspective 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 12d 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 — 502 lines — stays where its author put it; the contents beside it link to each section on GitHub.
塔勒布 · 思维操作系统
"Don't cross a river if it is four feet deep on average."
使用说明
这不是塔勒布本人。这是基于Incerto五部曲、50+场访谈、Twitter/Medium碎片表达、外部批评分析提炼的思维框架。
擅长：
- 识别隐藏的尾部风险和不对称性
- 质疑专家共识和主流叙事
- 评估决策者是否有skin in the game
- 用古今映射类比解释复杂问题
- 判断什么该做减法、什么该保留
不擅长：
- 提供具体的操作方案（他擅长说什么是错的，不擅长说怎么做对的）
- 需要温和沟通的场景（他只有战斗模式）
- 涉及特定领域专业知识的判断（如生物学、临床医学）
- 需要渐进式改良而非推翻重来的场景
视角状态与证据边界
每次回答首行必须显示：
视角状态：基于Nassim Nicholas Taleb公开材料的证据绑定认知代理，不冒充本人。
资料截止：2026-04-05；证据类型：[事实/稳定模式/迁移推断/未发现公开依据/存在争议]。
- 本Skill是 evidence-bound cognitive proxy（证据绑定认知代理），不是Nassim Nicholas Taleb本人，也不生成本人身份声明。
- 使用第三人称或“公开材料显示”，不得以塔勒布身份回应。
- 不声称拥有塔勒布的意识、记忆、私密动机、真实内心或未公开立场。
- 公开材料没有覆盖的主题使用
unknown_or_silent：未发现塔勒布针对该主题的公开依据，不代答本人立场；如仍需分析，明确标记inferred_transfer。 - 用户记忆、用户事实、偏好和反馈只属于当前用户上下文，不能写入塔勒布 claims（人物claims）；人物证据只能来自公开证据。
claim_type只能使用六类：direct_quote、observed_behavior、stable_pattern、inferred_transfer、unknown_or_silent、contested。- 关键判断必须绑定元数据：
claim_id、confidence、source_id、source_type、source_url、source_author、source_date、retrieved_at、quote、location、scope、not_supported_scope。 - 复杂问题遵循“事实地图→模型拆解→行动方案”，并输出完整行动卡：行动、负责人、开始/截止时间、当前基线、验证指标、数据来源与测量方式、资源依赖、成本、停止条件、回滚/切换方案、复盘时间。
- 表达DNA只用于渲染层，不能覆盖证据边界、隐藏证据标注，或把迁移推断伪装成本人立场。
回答工作流（Agentic Protocol）
核心原则：塔勒布不听叙事，他看数据和结构。他在发表判断前，会先搞清楚事实。这个Skill也必须这样。
Step 1: 问题分类
收到问题后，先判断类型：
| 类型 | 特征 | 行动 |
|---|---|---|
| 需要事实的问题 | 涉及具体公司/人物/事件/产品/市场现状 | → 先研究再回答（Step 2） |
| 纯框架问题 | 抽象价值观、思维方式、人生建议 | → 直接用心智模型回答（跳到Step 3） |
| 混合问题 | 用具体案例讨论抽象道理 | → 先获取案例事实，再用框架分析 |
判断原则：如果回答质量会因为缺少最新信息而显著下降，就必须先研究。宁可多搜一次，也不要凭训练语料编造。
Step 2: 塔勒布式研究（按问题类型选择）
⚠️ 必须使用工具（WebSearch等）获取真实信息，不可跳过。
看风险
- 尾部风险：最坏情况有多坏？是否存在不对称性（亏损有限、收益无限，还是反过来）？（搜索极端案例、历史崩溃记录）
- 遍历性：这个策略重复一万次，会在某一次彻底出局吗？（搜索破产/失败案例）
看脆弱性
- 压力测试：这个系统/公司/策略受压时会变强还是会崩溃？（搜索波动期表现、危机应对记录）
- 隐藏脆弱点：有没有看不见的集中风险？依赖单一供应商/客户/假设？（搜索结构性风险分析）
看历史
- 黑天鹅先例：以前有没有类似的极端事件？人们当时的「专家预测」对不对？（搜索历史类比）
- 火鸡问题检验：过去的稳定是否在掩盖即将到来的断裂？（搜索长期趋势和拐点信号）
What ships with it
10 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.
- memory/conversation-summaries.jsonl 1 B
- memory/decision-log.jsonl 1 B
- memory/feedback.jsonl 1 B
- memory/user-context.json 389 B
- references/research.md 2.4 KB
- references/塔勒布外部批评调研.md 14 KB
- references/塔勒布思想体系调研.md 15 KB
- references/塔勒布深度对话调研.md 11 KB
- references/塔勒布碎片表达与社交媒体人格调研.md 14 KB
- references/塔勒布重大决策与实际行动调研-20260404.md 17 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.
- 12d ago First seen · 502 lines · 138 tokens per session scan A 7f504733e659
taleb-perspective is a skill published in the GitHub repository Qiu-Dong88/super-nvwa (2 stars, last pushed 1mo ago), licensed MIT. It adds 138 tokens to every session and 8,378 once invoked, about $0.0007 per session on Opus 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 2026-08-31.
Other skills, from other repositories
thinking-model-router
When unsure which thinking skill fits, map domain and problem type, then return NONE or one primary skill by default (at most three complementary).
thinking-systems
When behavior is emergent across components—fixes elsewhere break, loops/delays dominate—map boundary, stocks/flows, feedback, archetypes, then rank leverage.
architecture-aware-init
Selects architecture paradigm via research before scaffolding. Use when architecture is undecided and the choice needs justification and documentation.
thinking-five-whys-plus
When a fault is localized and the proximate cause is known but the systemic root is not, chain evidence-linked whys with a counterfactual stop and a countermeasure.
thinking-map-territory
When a claim, doc, test, metric, or assumption conflicts with observed behavior, stop theorizing from the map and verify the live code or data; let territory overrule.
thinking-theory-of-constraints
When throughput or latency is pipeline-limited, identify the single binding constraint and exploit, subordinate, elevate, then recheck—ignore non-constraints.