# Mk:elicit > Structured second-pass reasoning after code review or plan evaluation. Offers named reasoning methods (pre-mortem, inversion, red team, Socratic, etc.) to re-examine findings through a specific lens. Use after /mk:review verdict or any time deeper analysis is needed on an existing output. NOT for initial review (see mk:review); NOT for creating implementation plans (see mk:plan-creator). - **Type:** Skill - **Install:** `agentstack add skill-ngocsangyem-meowkit-elicit` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [ngocsangyem](https://agentstack.voostack.com/s/ngocsangyem) - **Installs:** 0 - **Category:** [Agent Skills](https://agentstack.voostack.com/c/agent-skills) - **Latest version:** 0.1.0 - **License:** MIT - **Upstream author:** [ngocsangyem](https://github.com/ngocsangyem) - **Source:** https://github.com/ngocsangyem/MeowKit/tree/main/.claude/skills/elicit - **Website:** https://docs.meowkit.dev/ ## Install ```sh agentstack add skill-ngocsangyem-meowkit-elicit ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About # 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 `/mk:review` 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 | Method | Lens | Best 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: | Context | Suggested Method | | -------------------------------------- | ------------------- | | Review found security issues | Red Team | | Review found low coverage | Pre-mortem | | Plan has many assumptions | First Principles | | Architecture decision | Inversion | | Complex feature with many stakeholders | Stakeholder Mapping | | Default / unclear | Socratic | ## Output Format ```markdown ## 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 ## Source & license This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code. - **Author:** [ngocsangyem](https://github.com/ngocsangyem) - **Source:** [ngocsangyem/MeowKit](https://github.com/ngocsangyem/MeowKit) - **License:** MIT - **Homepage:** https://docs.meowkit.dev/ Install and usage instructions live in the source repository linked above. ## Pricing - **Free** — Free ## Security capabilities Automated source analysis of v0.1.0 — what this tool can access: - **Network access:** no - **Filesystem access:** no - **Shell / process execution:** no - **Environment & secrets:** no - **Dynamic code execution:** no *"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.* ## Versions - **0.1.0** — security scan: passed — Imported from the upstream source. ## Links - Listing page: https://agentstack.voostack.com/l/skill-ngocsangyem-meowkit-elicit - Seller: https://agentstack.voostack.com/s/ngocsangyem - Browse the marketplace: https://agentstack.voostack.com/browse --- Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.