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assumption-buster假设破坏者

Agent Skill

assumption-buster 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

612

周安装

25

GitHub Stars

1

下载量

196
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:assumption-buster(假设破坏者)
来源仓库:https://github.com/wojons/skills
仓库路径:skills/assumption-buster
安装命令:
npx skills add https://github.com/wojons/skills --skill assumption-buster
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/wojons/skills --skill assumption-buster

简介

assumption-buster 主动挑战项目中的隐藏假设,通过反例生成与对抗性思维暴露潜在风险。

  • 适用于高成本失败场景,如安全、财务或声誉相关决策。
  • 采用系统性方法识别信念漏洞,防止确认偏误。
  • 输出包含被质疑的假设列表与验证建议。
  • 建议在重大投资前强制使用此技能。assumption-buster 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Assumption Buster

Aggressively identify, challenge, and attempt to disprove assumptions through systematic counterexample generation, edge case exploration, and adversarial thinking to reveal hidden weaknesses and false beliefs.

When to use me

Use this skill when:

  • Critical decisions rely on untested assumptions
  • Systems have high failure costs (safety, financial, reputation)
  • You suspect team is suffering from confirmation bias
  • Preparing for adversarial environments (security, competition, regulation)
  • Testing resilience of core system beliefs
  • Validating fundamental premises before major investments
  • Challenging "industry best practices" that may not apply
  • Stress-testing architectural decisions
  • Preparing for audits, penetration tests, or regulatory reviews

What I do

1. Assumption Aggression

  • Actively seek to disprove rather than just test assumptions
  • Generate counterexamples that break the assumption
  • Find edge cases where assumption fails catastrophically
  • Identify contradiction patterns in evidence
  • Pressure-test boundary conditions until they break

2. Disproof Methodology

  • Attempt falsification using Popperian scientific method
  • Search for black swans - rare but catastrophic counterexamples
  • Construct stress scenarios that maximize assumption failure
  • Apply Murphy's Law - "anything that can go wrong, will"
  • Explore combinatorial explosions of failure modes

3. Adversarial Testing

  • Think like an attacker trying to break the system
  • Adopt competitor mindset looking for weaknesses to exploit
  • Simulate hostile environments (limited resources, malicious actors)
  • Test under extreme conditions beyond design specifications
  • Provoke failure cascades and ripple effects

4. Cognitive Bias Countermeasures

  • Target confirmation bias by seeking disconfirming evidence
  • Challenge availability heuristic by looking for rare cases
  • Counter anchoring effect by exploring extreme values
  • Overcome overconfidence with rigorous stress testing
  • Break groupthink by introducing dissenting perspectives

Assumption Busting Techniques

For Technical Assumptions:

  • Load to failure: "What load breaks this assumption?"
  • Resource starvation: "What happens with minimal resources?"
  • Dependency failure: "What if every dependency fails simultaneously?"
  • Version hell: "What if all versions are mismatched?"
  • Data corruption: "What if data is intentionally malformed?"

For Business Assumptions:

  • Market reversal: "What if customer preferences change overnight?"
  • Competitor innovation: "What if a competitor solves this better/cheaper?"
  • Regulatory shock: "What if regulations completely change?"
  • Economic collapse: "What if funding disappears?"
  • Team dissolution: "What if key people leave?"

For Process Assumptions:

  • Communication breakdown: "What if all communication fails?"
  • Tool failure: "What if primary tools become unavailable?"
  • Knowledge loss: "What if institutional knowledge disappears?"
  • Timeline compression: "What if deadlines move up 90%?"
  • Quality erosion: "What if quality standards steadily decline?"

Examples

# Aggressively test a technical assumption
npm run assumption-buster:disprove -- --assumption "database-always-available" --method "chaos-engineering"

# Find counterexamples for a business assumption
npm run assumption-buster:counterexamples -- --assumption "users-prefer-mobile" --data "analytics-export.csv"

# Stress-test architectural decisions
npm run assumption-buster:stress-test -- --architecture "event-driven" --scenario "complete-network-partition"

# Generate failure scenarios for a process
npm run assumption-buster:failure-scenarios -- --process "ci-cd-pipeline" --intensity extreme

# Comprehensive assumption busting
npm run assumption-buster:all -- --criticality high --thoroughness maximum

Output format

Assumption Busting Report
──────────────────────────────
Target: Payment Processing System
Assumptions Targeted: 14
Busting Duration: 2 hours
Busting Intensity: Aggressive

Assumption Busting Results:

1. Assumption: "Payment gateway responses always within 2 seconds"
   Status: ❌ BUSTED (Catastrophically)

   Counterexamples Found:
   - Network partition causes indefinite hangs (no timeout)
   - Gateway DDoS attack results in 30+ second responses
   - SSL certificate expiration causes silent failures
   - DNS poisoning redirects to malicious endpoints
   - Gateway vendor bankruptcy (no responses at all)

   Stress Test Results:
   - Under simulated attack: 85% of requests exceed 2 seconds
   - Failure cascade: timeouts cause thread pool exhaustion
   - Worst-case latency: 47 seconds (complete system stall)

   Impact if Believed:
   - Payment system becomes unresponsive during attacks
   - Financial losses from failed transactions
   - Customer trust destroyed
   - Recovery requires complete system restart

   Recommendation:
   Implement circuit breakers, aggressive timeouts, fallback providers

2. Assumption: "Users always complete checkout in single session"
   Status: ⚠️ PARTIALLY BUSTED (Significant weaknesses)

   Counterexamples Found:
   - Mobile network drops during payment (common)
   - Browser crashes after cart creation (frequent)
   - Users comparison shop across tabs (standard behavior)
   - Payment requires external verification (bank 2FA)
   - Users interrupted by real-world events (constant)

   Stress Test Results:
   - 41% of simulated users experience session-breaking events
   - Recovery rate without persistence: 12%
   - Data loss probability: 29%

   Impact if Believed:
   - Significant abandoned cart revenue loss
   - User frustration and negative reviews
   - Competitive disadvantage against persistent carts

   Recommendation:
   Implement cart persistence, resume functionality, email reminders

3. Assumption: "Fraud detection catches 99% of fraudulent transactions"
   Status: ❌ BUSTED (Dangerously false)

   Counterexamples Found:
   - New fraud patterns not in training data (always emerging)
   - Low-and-slow attacks evade threshold detection
   - Synthetic identity fraud has no historical patterns
   - Insider threats bypass external detection
   - Collusion attacks distribute suspicious activity

   Adversarial Testing Results:
   - Simulated novel fraud: 67% detection rate (not 99%)
   - Adaptive attackers: detection degrades over time
   - False positive rate forces threshold lowering
   - Detection latency allows transaction completion

   Impact if Believed:
   - Financial losses from undetected fraud
   - Regulatory penalties for inadequate controls
   - Reputation damage from fraud incidents

   Recommendation:
   Implement multi-layered fraud detection, continuous model updates

4. Assumption: "Database transactions always rollback on failure"
   Status: ✅ WITHSTOOD TESTING (But edge cases found)

   Stress Test Results:
   - Normal failures: proper rollback (assumption holds)
   - Edge Cases Discovered:
     * Connection pool exhaustion during rollback
     * Deadlock during distributed transaction cleanup
     * Storage engine corruption preventing rollback
     * Partial network failure leaving transactions dangling

   Recommendation:
   Implement transaction monitoring, orphan detection, manual cleanup procedures

Assumption Survival Rate:
- Completely Busted: 6 assumptions (43%)
- Partially Busted: 5 assumptions (36%)
- Withstood Testing: 3 assumptions (21%)

Critical Vulnerabilities Exposed:
1. Payment timeout handling (catastrophic failure possible)
2. Session persistence (significant revenue loss)
3. Fraud detection gaps (financial and regulatory risk)
4. Transaction cleanup (data consistency risk)

Busting Effectiveness Metrics:
- Novel failure modes discovered: 23
- Catastrophic scenarios identified: 7
- Previously unknown risks: 11
- Testing time vs value: Extremely high ROI
- Confidence adjustment: From 85% to 42% (more realistic)

Actionable Insights:
1. IMMEDIATE: Implement circuit breakers for payment gateway
2. HIGH PRIORITY: Add cart persistence and resume functionality
3. HIGH PRIORITY: Enhance fraud detection with behavioral analysis
4. MEDIUM PRIORITY: Add transaction monitoring and cleanup
5. MEDIUM PRIORITY: Create assumption registry with busting schedule

Next Busting Cycle Recommendations:
- Schedule: Monthly for critical assumptions
- Focus: New features and changed assumptions
- Method: Rotate between technical, business, process assumptions
- Participants: Include external perspectives for fresh eyes

Philosophical Notes:
- The assumptions that hurt most are those we don't know we're making
- A busted assumption is a gift - it reveals a hidden risk
- The goal isn't to prove assumptions wrong, but to find where they fail
- The most dangerous assumption is "our assumptions are mostly correct"
- Assumption busting creates antifragility - systems that improve when stressed

Notes

  • Assumption busting is intentionally aggressive - it tries to break things
  • Balance between thorough busting and practical constraints
  • Document both busted assumptions and those that withstand testing
  • Use busting findings to improve systems, not just criticize them
  • The value is in discovering unknown unknowns
  • Some assumptions should remain (but now you know their limits)
  • Busting creates knowledge about system boundaries and failure modes
  • Share busting results transparently to build organizational learning
  • Regular assumption busting prevents accumulation of false beliefs
  • The best busting often comes from outsiders with different perspectives

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

35.56%
按下载量换算70

Claude

28.21%
按下载量换算55

Cursor

18.94%
按下载量换算37

Gemini CLI

10.29%
按下载量换算20

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

安装前确认

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