Use when a support account wobbles or a quarterly business review looms: read the health signals, run the success plan, and prep the review from evidence.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Performs security-focused differential review of code changes. Adapts analysis depth to codebase size, uses git blame for context, calculates blast radius by counting callers, checks test coverage of modified code, and generates a markdown report. Use when reviewing a PR, commit, or diff for security vulnerabilities, checking whether a change re-introduces a previously fixed bug, asking what else a change could break, or finding which modified code has no test covering it.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Packaging adaptation by AutoGPT, 2026-09-25. Original authorship and licence are retained. Changes are limited to the recorded name, metadata and file references; see ATTRIBUTION.md in this skill package.
Security-focused code review for PRs, commits, and diffs.
| Rationalization | Why It's Wrong | Required Action |
|---|---|---|
| "Small PR, quick review" | Heartbleed was 2 lines | Classify by RISK, not size |
| "I know this codebase" | Familiarity breeds blind spots | Build explicit baseline context |
| "Git history takes too long" | History reveals regressions | Never skip Phase 1 |
| "Blast radius is obvious" | You'll miss transitive callers | Calculate quantitatively |
| "No tests = not my problem" | Missing tests = elevated risk rating | Flag in report, elevate severity |
| "Just a refactor, no security impact" | Refactors break invariants | Analyze as HIGH until proven LOW |
| "I'll explain verbally" | No artifact = findings lost | Always write report |
| Codebase Size | Strategy | Approach |
|---|---|---|
| SMALL (<20 files) | DEEP | Read all deps, full git blame |
| MEDIUM (20-200) | FOCUSED | 1-hop deps, priority files |
| LARGE (200+) | SURGICAL | Critical paths only |
| Risk Level | Triggers |
|---|---|
| HIGH | Auth, crypto, external calls, value transfer, validation removal |
| MEDIUM | Business logic, state changes, new public APIs |
| LOW | Comments, tests, UI, logging |
Pre-Analysis → Phase 0: Triage → Phase 1: Code Analysis → Phase 2: Test Coverage
↓ ↓ ↓ ↓
Phase 3: Blast Radius → Phase 4: Deep Context → Phase 5: Adversarial → Phase 6: Report
Starting a review?
├─ Need detailed phase-by-phase methodology?
│ └─ Read: methodology.md
│ (Pre-Analysis + Phases 0-4: triage, code analysis, test coverage, blast radius)
│
├─ Analyzing HIGH RISK change?
│ ├─ Read: adversarial.md
│ │ (Phase 5: Attacker modeling, exploit scenarios, exploitability rating)
│ └─ Or delegate to: differential-review:adversarial-modeler agent
│ (Autonomous attacker modeling with concrete exploit scenarios)
│
├─ Writing the final report?
│ └─ Read: reporting.md
│ (Phase 6: Report structure, templates, formatting guidelines)
│
├─ Looking for specific vulnerability patterns?
│ └─ Read: patterns.md
│ (Regressions, reentrancy, access control, overflow, etc.)
│
└─ Quick triage only?
└─ Use Quick Reference above, skip detailed docs
differential-review:adversarial-modeler — Models attacker perspectives and
builds exploit scenarios for HIGH RISK code changes. Follows the 5-step
adversarial methodology (attacker model, attack vectors, exploitability rating,
exploit scenario, baseline cross-reference) and produces structured vulnerability
reports. Delegate to this agent when Phase 5 analysis is needed on high-risk
changes, passing that full namespaced name as subagent_type — a bare
adversarial-modeler is unregistered and the dispatch fails at runtime.
Before delivering:
audit-context-building skill:
issue-writer skill:
issue-writer --input DIFFERENTIAL_REVIEW_REPORT.md --format audit-reportInput: 5 file PR, 2 HIGH RISK files
Strategy: Use Quick Reference
1. Classify risk level per file (2 HIGH, 3 LOW)
2. Focus on 2 HIGH files only
3. Git blame removed code
4. Generate minimal report
Time: ~30 minutes
Input: 80 files, 12 HIGH RISK changes
Strategy: FOCUSED (see methodology.md)
1. Full workflow on HIGH RISK files
2. Surface scan on MEDIUM
3. Skip LOW risk files
4. Complete report with all sections
Time: ~3-4 hours
Input: 450 files, auth system rewrite
Strategy: SURGICAL + audit-context-building
1. Baseline context with audit-context-building
2. Deep analysis on auth changes only
3. Blast radius analysis
4. Adversarial modeling
5. Comprehensive report
Time: ~6-8 hours
For these cases, use standard code review instead.
Immediate escalation triggers:
These patterns require adversarial analysis even in quick triage.
Do:
Don't:
For first-time users: Start with methodology.md to understand the complete workflow.
For experienced users: Use this page's Quick Reference and Decision Tree to navigate directly to needed content.
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Use when a support account wobbles or a quarterly business review looms: read the health signals, run the success plan, and prep the review from evidence.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Reconcile accounts by comparing GL balances to subledgers, bank statements, or third-party data. Use when performing bank reconciliations, GL-to-subledger recs, intercompany reconciliations, or identifying and categorizing reconciling items.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Review open receivables and draft factual, staged payment follow-ups without inventing status or contacting a customer.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Write ad variants that each test one idea, within platform limits and supported claims.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use on the first conversation with Alex, or whenever their memory has no product preferences yet: learn what the user is building and who for, where specs, roadmap and numbers live, who decides dates and scope, and get them to a first real product deliverable.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when a strategic alliance needs joint selling governance: operating model, joint targeting, steering prep, and milestone accountability.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.