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da-review
Use when you have an existing plan, design, or implemented code that needs adversarial review to find weaknesses, missing edge cases, and unnecessary complexity
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Use when you have an existing plan, design, or implemented code that needs adversarial review to find weaknesses, missing edge cases, and unnecessary complexity
Baseado na classificaรงรฃo ocupacional SOC
Use when you want to autonomously improve a SKILL.md's quality by running iterative experiments. Triggers on "autoresearch ๋๋ ค์ค", "์คํฌ ํ์ง ์ฌ๋ ค์ค", "์ด ์คํฌ์ ์๋์ผ๋ก ๊ฐ์ ํด์ค", "run autoresearch on this skill", or any request to automatically improve a skill's eval pass rate through repeated experimentation. Applies Karpathy's autoresearch technique - fixed-budget iterative loop with single-metric hill-climbing and automatic keep/discard decisions.
Use when a developer needs to choose between two or more approaches during implementation. Triggers on "A vs B?", "should I use X or Y?", "which approach is better?", "Redis or Memcached?", "REST or gRPC?", "single table or split?", or any binary/multi-option technical decision. Use this skill whenever the user is weighing alternatives mid-implementation โ even if they don't say "decide", if they're comparing approaches, this skill applies.
Use when creating implementation plans for complex multi-file features or architectural changes that benefit from multiple perspectives before implementation. Use this skill whenever the user asks to plan, design, or architect a feature that touches 3+ files, involves trade-offs between approaches, or would benefit from thinking through risks and requirements before coding. Even if the user says "plan this" without mentioning perspectives, this skill applies.
Multi-AI engineering loop orchestrating Claude, Codex, and Gemini for comprehensive validation. USE WHEN (1) mission-critical features requiring multi-perspective validation, (2) complex architectural decisions needing diverse AI viewpoints, (3) security-sensitive code requiring deep analysis, (4) user explicitly requests multi-AI review or triple-AI loop. DO NOT USE for simple features or single-file changes. MODES - Triple-AI (full coverage), Dual-AI Codex-Claude (security/logic), Dual-AI Gemini-Claude (UX/creativity).
Dual-AI engineering loop orchestrating Claude Code (planning/implementation) and Codex (validation/review). Use when (1) complex feature development requiring validation, (2) high-quality code with security/performance concerns, (3) large-scale refactoring, (4) user requests codex-claude loop or dual-AI review. Do NOT use for simple one-off fixes or prototypes.
OpenAI Codex CLI fundamentals for code analysis, review, and validation. Use when (1) executing codex commands for code review/analysis, (2) configuring models (gpt-5.3-codex/gpt-5.2/gpt-5.1-codex-max/gpt-5-codex-mini), sandbox modes (read-only/workspace-write), or reasoning effort (low/medium/high/xhigh), (3) managing Codex sessions with resume, (4) integrating Codex into automation scripts. Do NOT use for orchestration patterns (use codex-claude-loop instead).
| name | da-review |
| description | Use when you have an existing plan, design, or implemented code that needs adversarial review to find weaknesses, missing edge cases, and unnecessary complexity |
Assemble a Devil's Advocate team with a shared adversarial mission: prove this will fail, then show what would be better. Each team member attacks from a different angle AND proposes fundamentally better alternatives โ not just patches for what's broken.
Core principle: A DA team doesn't just find flaws. It breaks down the target to understand its weaknesses, then reconstructs a better version. The team succeeds when it either proves robustness (despite genuine effort to break it) or delivers concrete, actionable alternatives that are demonstrably superior to the original approach. Incremental fixes are a last resort โ prefer structural improvements.
Review targets: Implementation plans, design documents, or implemented code (files, diffs, PRs).
Detect review mode from the user's request:
Assess complexity to choose the execution path. Apply rules top to bottom โ first match wins:
When in doubt, default to Fast Mode. The user can always request Team Mode explicitly.
Match output language to user input. If the user writes in Korean, produce the entire review in Korean. If in English, produce in English. When writing in Korean, use these standard technical terms consistently:
The orchestrator performs a structured adversarial review directly โ no sub-agent dispatch. This eliminates orchestration overhead while maintaining quality through the DA checklist.
Apply the combined DA checklist below against the loaded code. Work through each section systematically. For each finding, assign severity and propose a concrete alternative.
Feasibility Check:
Gap Check:
Security Check (when security-relevant):
Performance Check (when performance-relevant):
Concurrency Check (when async/parallel code is present):
Produce the same structured output as Team Mode:
DA Review (Fast Mode):
| # | Severity | Location | Finding | Better Alternative |
|---|
Present findings to the user with options: apply fixes, adopt alternative, or keep as-is.
Full DA team with parallel adversarial agents + validation. Use for complex targets where multiple perspectives and cross-analysis add genuine value.
Load context upfront:
The orchestrator reads files BEFORE dispatching agents to eliminate duplicate reads.
Plan mode (selective loading โ max 4 files):
Code mode (full loading):
Include loaded content in each agent's prompt. For code mode, embed all files. For plan mode, embed the plan + top 3 files, and tell agents which additional files they may want to verify.
Select DA agents โ pick the set that covers the risk areas:
| Target Type | Recommended Agents |
|---|---|
| New feature (code) | Feasibility Skeptic + Gap Hunter |
| New feature (plan) | Feasibility Skeptic + Gap Hunter + Concurrency Auditor |
| Refactoring | Feasibility Skeptic + Complexity Critic |
| User input / external APIs | Feasibility Skeptic + Security Auditor |
| Public API changes | Feasibility Skeptic + Backwards Compatibility Checker |
| Performance-sensitive code | Feasibility Skeptic + Performance Analyst |
| Async / concurrent code | Feasibility Skeptic + Concurrency Auditor |
| Large architectural change | 3 agents max, matching risk areas |
| High-risk target | 3 agents + Validator Phase |
Dispatch selected DA agents in a SINGLE response using multiple Agent tool calls. Build each agent's prompt:
Wait for ALL agents to complete. Do NOT begin consolidation with partial results.
Run when any CRITICAL finding exists or the target is high-risk. Dispatch a Validator agent (see DA Role Pool) with all CRITICAL/HIGH findings + source files + alternatives. Then remove FALSE_POSITIVEs and adjust alternatives based on results.
DA Team Verdict:
Present findings + alternatives to the user with clear options:
Apply based on user's choice:
Team Framing โ prepend to ALL DA agents:
You are a member of a Devil's Advocate Team. Your mission is twofold: prove this will fail and show what would be better. You are not a helpful reviewer making suggestions โ you are an adversary who breaks things down, then a craftsman who reconstructs them better. Don't just find problems โ demonstrate superior alternatives. Other team members attack from different angles simultaneously. Focus on YOUR domain thoroughly. Flag concerns that might interact with other domains.
Common rules for all agents: Assign severity (CRITICAL/HIGH/MEDIUM) to every finding. Cite exact location (plan section/step or file:line). Quality over quantity โ no minimum finding count.
Identity: Skeptical tech lead โ assumes every estimate is optimistic and every integration is a trap.
Mandate:
Focus: Technical viability, API/pattern existence, dependency ordering, verification effectiveness
Attack Questions (plan mode):
Attack Questions (code mode):
Output Format:
| # | Severity | Location | Finding | Better Alternative |
|---|
Cross-domain flags: [Issues interacting with other domains] Structural Alternative: [If the overall approach is flawed, describe a fundamentally different approach that would avoid these issues entirely]
Identity: Minimalist engineer โ every abstraction is guilty until proven innocent.
Mandate:
Focus: Unnecessary abstractions, YAGNI violations, simpler alternatives, unnecessary files/components
Attack Questions:
Output Format:
| # | Severity | Location | Current Approach | Simpler Alternative (with sketch) |
|---|
Cross-domain flags: [Issues interacting with other domains] Structural Alternative: [Describe how the entire component/feature could be restructured more simply]
Identity: QA-minded engineer โ finds every scenario nobody considered.
Mandate:
Focus: Missing error handling, unaddressed edge cases, missing tests, migration concerns, rollback/failover strategy
Attack Questions (plan mode):
Attack Questions (code mode):
Output Format:
| # | Severity | Gap Type | What Is Missing | Structural Solution |
|---|
Cross-domain flags: [Issues interacting with other domains] Structural Alternative: [Describe a design pattern or architecture that would make these gaps impossible rather than patching each one]
Identity: Security engineer โ every input is an attack vector.
Mandate:
Focus: Auth gaps, input validation, data exposure, injection vectors, OWASP Top 10
Attack Questions:
Output Format:
| # | Severity | Location | Vulnerability | Secure Alternative |
|---|
Cross-domain flags: [Issues interacting with other domains] Structural Alternative: [Describe a secure-by-design architecture that eliminates classes of vulnerabilities]
Identity: API steward โ every interface change is a contract violation until proven otherwise.
Mandate:
Focus: API contract changes, data format changes, behavior changes, migration paths, deprecation
Attack Questions:
Output Format:
| # | Severity | Location | Breaking Change | Migration Strategy |
|---|
Cross-domain flags: [Issues interacting with other domains] Structural Alternative: [Describe an approach that achieves the goal without breaking existing consumers]
Mandate: Find performance issues โ cite location with complexity analysis. Propose efficient alternatives. Assign severity. Quality over quantity.
Focus: Time/space complexity, resource lifecycle, memory allocation, I/O efficiency
Attack Questions:
Output Format: | # | Severity | Location | Performance Issue | Efficient Alternative |
Mandate: Find concurrency issues โ cite shared state and access pattern. Propose thread-safe alternatives. Assign severity. Quality over quantity.
Focus: Race conditions, atomicity violations, deadlock potential, shared mutable state
Attack Questions:
Output Format: | # | Severity | Location | Concurrency Issue | Thread-Safe Alternative |
Mandate: Verify DA team findings are real, not false positives. Check alternative feasibility. Accuracy is everything.
Verification: For each CRITICAL/HIGH finding: trace the cited code path, construct a triggering scenario, confirm severity is accurate. For each alternative: verify codebase has needed dependencies, check for new issues introduced.
Output: Mark each finding VERIFIED / FALSE_POSITIVE / NEEDS_CONTEXT. Mark each alternative FEASIBLE / INFEASIBLE / NEEDS_MODIFICATION.
์ฐธ์กฐ:
${CLAUDE_PLUGIN_ROOT}/skills/_shared/logging-protocol.md,${CLAUDE_PLUGIN_ROOT}/skills/_shared/pattern-schema.md
.claude/agent-team/da-review/logs/index.json์ ์ฝ์ด ์ด์ ์คํ ๊ธฐ๋ก ํ์ธ (์์ผ๋ฉด ๋๋ ํ ๋ฆฌ์ ํจ๊ป {"entries":[]} ์ด๊ธฐํ).claude/agent-team/da-review/patterns/index.json์ ์ฝ์ด ๊ธฐ์กด ํจํด๊ณผ ํ์ฌ ์
๋ ฅ ๋์กฐ (์์ผ๋ฉด ๊ฑด๋๋).md๋ฅผ ์ฝ๊ณ ์ฐธ๊ณ , hitCount +1.claude/agent-team/da-review/logs/{timestamp}/result.json ์์ฑ (๊ณตํต ํ๋ + da-review ํ์ฅ ํ๋: mode, reviewTarget, agentsDispatched, findingsCount, overallRating).claude/agent-team/da-review/logs/{timestamp}/summary.md ์์ฑ.claude/agent-team/da-review/logs/index.json์ entry ์ถ๊ฐ.claude/agent-team/da-review/patterns/๋ก ์น๊ฒฉ