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免费Security audit, hardening, threat modeling (STRIDE/PASTA), Red/Blue Team, OWASP checks, code review, incident response, and infrastructure security for any project.
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[32] ANALYZE. Ensure every critical claim has verifiable evidence with confidence levels. Each fact must have source + confidence percentage. If confidence <85%, enter Loop150 to find more sources. Use for critical decisions, factual claims, legal/compliance work, or any situation where unverified claims are dangerous.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
Core Principle: No claim without proof. Every critical fact needs: source + confidence level. If unsure, keep digging until confident or escalate to user.
When you invoke this skill, you're asking AI to:
| Dimension | 100% Core | +50% Enhancement |
|---|---|---|
| Source | Primary source identified | + Independent confirmation |
| Confidence | Percentage stated | + Reasoning documented |
| Verification | Single source check | + Multi-source cross-validation |
| Gaps | Note uncertainties | + Active Loop150 to fill gaps |
| Level | % Range | Description | Action Required |
|---|---|---|---|
| Verified | 95-100% | Multiple primary sources, no contradictions | Use in critical decisions |
| Strong | 85-94% | Reliable sources, minor uncertainties | Safe for most purposes |
| Moderate | 75-84% | Limited sources, some gaps | Flag for verification |
| Weak | 50-74% | Insufficient evidence, major gaps | Do not use without confirmation |
| Insufficient | <50% | Contradictory or missing | Reject, research further |
State the fact clearly:
🔍 **Claim:** [Precise factual statement]
**Context:** [Why this matters]
**Critical Level:** [High/Medium/Low]
Find the original source:
Find independent corroboration:
Calculate confidence:
**Evidence Evaluation:**
├── Primary Source: [Quality assessment]
├── Secondary Sources: [Count and quality]
├── Contradictions: [Any found?]
└── Gaps: [What's missing?]
**Confidence:** [X]%
**Reasoning:** [Why this percentage]
Confidence ≥85%?
├─ YES → Use fact with stated confidence
└─ NO → Enter Loop150
When confidence <85%:
🔄 **LOOP150 ACTIVATED** (Current: [X]%)
ITERATION 1: EXPAND SOURCES
├── Identify new source types
├── Use alternative research methods
├── Broaden search scope
↓
ITERATION 2: DEEPER ANALYSIS
├── Drill into source details
├── Verify source credibility
├── Check contextual factors
↓
ITERATION 3: CROSS-VALIDATION
├── Compare against known facts
├── Test logical consistency
├── Seek expert corroboration
↓
RECALCULATE: New confidence = [Y]%
Continue loop until:
├─ ≥90% achieved → EXIT, proceed with confidence
└─ Sources exhausted → ESCALATE to user
🔍 RELIABILITY FACTORS:
📊 EVIDENCE STRENGTH:
| Type | Strength | Example |
|---|---|---|
| Primary | High | Original data, first-hand |
| Secondary | Medium | Analysis of primary |
| Tertiary | Low | Summaries, reviews |
| Statistical | High | Large sample, proper method |
| Anecdotal | Variable | Personal experience |
🔍 **PROOF-GRADE 150 VERIFICATION**
**Claim:** [Precise factual statement]
**Primary Source:**
- [File/location/date]
- "[Direct quote or data]"
**Secondary Sources:**
- [Source 2]: [Confirmation]
- [Source 3]: [Confirmation]
**Confidence Level:** [X]%
**Reasoning:** [Why this level]
**Validation Method:** [How verified]
**Outstanding Issues:** [Any uncertainties]
**Status:** ✅ VERIFIED | ⚠️ NEEDS CONFIRMATION | ❌ INSUFFICIENT
| Failure | Detection | Recovery |
|---|---|---|
| Unverified Claims | Facts without sources | Immediate verification, Loop150 |
| Overconfidence | Inflated percentages | Recalculate with scrutiny |
| Source Bias | Only confirming sources | Actively seek contradictions |
| Incomplete Docs | Missing source trail | Document all sources now |
AI: "The API response time is fast enough"
Source: "Feels fast to me"
Result: Performance issues in production
🔍 PROOF-GRADE 150 VERIFICATION
Claim: "API response time is consistently under 200ms"
Primary Source:
- /tests/performance/load_test_results.json
- "p99 latency: 187ms across 10,000 requests"
Secondary Sources:
- Production monitoring (last 7 days): avg 156ms
- APM dashboard: p95 = 178ms
Confidence Level: 95%
Reasoning: Multiple measurement sources, consistent results,
production data confirms test environment findings.
Validation Method: Cross-referenced test data with production metrics
Status: ✅ VERIFIED FOR USE
Remember: Proof-grade isn't about being slow — it's about being trustworthy. A 95% confidence claim is more valuable than an unverified assertion. When stakes are high, proof-grade protects everyone.
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Security audit, hardening, threat modeling (STRIDE/PASTA), Red/Blue Team, OWASP checks, code review, incident response, and infrastructure security for any project.
中文简介正在准备中。当前显示原文说明。
Guides the creation of agile user stories and Gherkin feature files. Use when the user wants to create a user story, write acceptance criteria, define Gherkin scenarios, or author BDD feature files. This should trigger for requests such as Create a user story; Write a user story; I need to write a user story. Part of cursor-rules-java project
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Facilitates conversational discovery to create Architectural Decision Records (ADRs) for non-functional requirements using the ISO/IEC 25010:2023 quality model. Use when the user wants to document quality attributes, NFR decisions, security/performance/scalability architecture, or design systems with measurable quality criteria. This should trigger for requests such as Create ADR for Non-functional requirements; Document Non-functional requirements; Capture Non-functional requirements; Generate Non-functional requirements in an ADR. Part of cursor-rules-java project
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Run a health check on an existing project: dependency audit, security scan, test runner detection, CI/CD evaluation, and missing configuration analysis. Maps the three execution gates (pre/in/post) from /10x-bootstrapper to an assessment framework for existing codebases. Reads optional context/foundation/stack-assessment.md from /10x-stack-assess to focus checks on identified gaps. Writes context/foundation/health-check.md with findings, prioritized fixes, and an agent-readiness verdict. Use when the user has an existing project and wants to verify its health before working with an agent. Trigger phrases: "health check", "check my project", "audit my project", "is my project healthy", "sprawdź projekt", "audyt projektu", "health-check", "project health". Use AFTER /10x-stack-assess (brownfield chain), BEFORE agent onboarding (m1-l4).
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You MUST use this when building projects end-to-end. Orchestrates all 12 team roles — automatically switches between CTO, architect, PM, engineers, SRE, security, DBA, QA, and EM based on the current phase of work. Starts with brainstorming before any implementation.
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Use when you need to add or configure Maven plugins in your pom.xml — including quality tools (enforcer, surefire, failsafe, jacoco, pitest, spotbugs, pmd), security scanning (OWASP), code formatting (Spotless), version management, container image build (Jib), build information tracking, and benchmarking (JMH) — through a consultative, modular step-by-step approach that only adds what you actually need. This should trigger for requests such as Add Maven plugins in pom.xml; Improve Maven plugins in pom.xml. Part of cursor-rules-java project
中文简介正在准备中。当前显示原文说明。