본문으로 건너뛰기
cccskills
무료GitHub에 공개

mk-elicit

Structured second-pass reasoning after a review or plan verdict: pre-mortem, inversion, red team, Socratic lens, etc. NOT for initial review (mk:review) or new plans (mk:plan-creator).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

설치 방법 보기

포함된 파일(1)

  • SKILL.md6.4 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Elicitation — Structured Second-Pass Reasoning

Re-examine an existing output (review verdict, plan, analysis) through a named reasoning method. Surfaces insights that generic "make it better" requests miss.

When to Use

  • After the review skill verdict — deepen analysis before Gate 2
  • After plan creation — stress-test assumptions before Gate 1
  • After any agent output — when user wants a specific angle of analysis
  • When user says "dig deeper", "what am I missing", "challenge this"

NOT this skill if: you have no existing artifact to re-examine — use mk:brainstorming for open exploration, or mk:problem-solving for approach-stuck situations.

Reasoning Methods

MethodLensBest For
Pre-mortem"Assume this shipped and failed. Why?"Risk discovery, failure mode analysis
Inversion"What would make this maximally wrong?"Assumption testing, edge cases
Red Team"You are an attacker. How do you exploit this?"Security analysis, adversarial thinking
Socratic"What evidence supports each claim?"Logic validation, gap detection
First Principles"Strip assumptions. What's fundamentally true?"Architecture decisions, design simplification
Constraint Removal"What if [constraint X] didn't exist?"Innovation, scope exploration
Stakeholder Mapping"Who else is affected? What do they need?"Impact analysis, requirements gaps
Analogical"What similar system solved this differently?"Alternative approaches, pattern matching

Workflow

  1. Load context — Read the output being re-examined (verdict file, plan file, or conversation context)
  2. Present methods — Show the table above; ask user to pick one (or suggest based on context)
  3. Apply method — Re-examine the output through the chosen lens
  4. Produce analysis — Structured output with:
    • Method applied
    • Key findings (numbered, actionable)
    • Severity: CRITICAL / IMPORTANT / INFORMATIONAL
    • Recommendations (what to change, if anything)
  5. Optional repeat — User may pick another method for multi-lens analysis

Auto-Suggestion Logic

When invoked without a method choice, suggest based on context:

ContextSuggested Method
Review found security issuesRed Team
Review found low coveragePre-mortem
Plan has many assumptionsFirst Principles
Architecture decisionInversion
Complex feature with many stakeholdersStakeholder Mapping
Default / unclearSocratic

Output Format

## Elicitation: [Method Name]

**Target:** [what was re-examined]
**Method:** [brief description of the lens applied]

### Findings

1. **[CRITICAL]** [finding] — [recommendation]
2. **[IMPORTANT]** [finding] — [recommendation]
3. **[INFORMATIONAL]** [finding] — [observation]

### Summary

[1-2 sentence synthesis of what this method revealed]

### Action Required

- [ ] [specific action items, if any]

Integration with mk:review

After the review verdict (step-04), the reviewer MAY offer elicitation:

Review complete. Verdict: WARN (2 warnings).

Would you like to run elicitation on this verdict?
Pick a method: pre-mortem | inversion | red-team | socratic | first-principles | skip

Elicitation output appends to the verdict file as a supplementary section. It does NOT change the verdict (PASS/WARN/FAIL) — it adds depth.

Gotchas

  • Reasoning methods are not commutative — order changes the output — running Red Team then Socratic surfaces attack vectors first and then validates them with evidence, producing a security-focused analysis; reversing to Socratic then Red Team validates assumptions before probing attacks, and often kills the adversarial framing entirely; always apply methods in the order that matches the user's primary concern.
  • Socratic method loops indefinitely without a termination criterion — "What evidence supports this claim?" applied recursively has no natural stopping point; without an explicit depth limit (e.g., stop at 3 levels of questioning or when no new claims emerge), the agent keeps decomposing until the context window fills; set a max depth before starting Socratic elicitation.
  • Inversion only works reliably on binary decisions, not multi-option trade-offs — "What would make this maximally wrong?" applied to a 3-option architectural choice produces a vague worst-case mix; inversion is sharp when the decision is yes/no (ship vs don't ship, add vs remove); for multi-option decisions, use Constraint Removal or Stakeholder Mapping instead.
  • Pre-mortem degenerates to a generic worry list without a concrete ship date and scope — "Assume this shipped and failed" requires a specific artifact (the plan, the feature, the migration) to be meaningful; if the target is vague ("our auth system"), the pre-mortem produces abstract risks ("scalability", "security") that don't map to actionable mitigations; always attach pre-mortem to a specific, scoped output.
  • Elicitation output appended to the verdict file does NOT change the gate decision — users sometimes interpret a CRITICAL finding from Red Team elicitation as requiring a Gate 2 re-evaluation; the skill explicitly does not change verdicts; if the elicitation reveals a CRITICAL issue, the user must manually trigger a new mk:review pass to produce a revised verdict before proceeding to Phase 5.

What This Skill Does NOT Do

  • Does NOT replace the review — it supplements it
  • Does NOT change verdicts or gate decisions
  • Does NOT generate code — analysis only
  • Does NOT run automatically — always user-triggered

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

Use this skill to generate well-branded interfaces and assets for MeowKit (AI Agent Toolkit for Claude Code), either for production or throwaway prototypes/mocks/etc. Contains essential design guidelines, colors, type, fonts, assets, and UI kit components for prototyping.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

ngocsangyem/MeowKit152026년 7월 28일 업데이트

mk-advise

무료

Turn a raw idea into ONE honest recommendation: interview one question at a time until confirmed, then give a verdict with trade-offs and a checklist. Not for options or debate.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

ngocsangyem/MeowKit152026년 7월 28일 업데이트

Browser automation CLI for agents: navigate, click/fill, screenshot, extract data, test apps, Electron/Slack, cloud browsers. NOT for the user's real Chrome profile/cookies (mk:chrome-profile).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

ngocsangyem/MeowKit152026년 7월 28일 업데이트

Detects the right agent and complexity tier at Phase 0 orient; runs first in every workflow. NOT for runtime agent routing inside a single skill.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

ngocsangyem/MeowKit152026년 7월 28일 업데이트

Angular v20+ patterns: components, signals, services, forms, routing, HTTP, testing, SSR. Auto-activates on .ts files in Angular projects (angular.json detected).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

ngocsangyem/MeowKit152026년 7월 28일 업데이트

Design and review durable REST, GraphQL, RPC, or event API contracts: shape, compatibility, pagination, error semantics. Discovers existing consumers first. Not implementation, schema, or release.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

ngocsangyem/MeowKit152026년 7월 28일 업데이트

ngocsangyem의 스킬 모두 보기

이 스킬의 문제 신고