mk:elicit

mk:elicit is a skill for Claude Code from ngocsangyem/MeowKit. It costs 89 tokens per session (1,555 once invoked), scanned A, original, MIT.

A structured second review of an existing code review, plan, or analysis using a chosen reasoning method. Methods include imagining failure, challenging assumptions, testing evidence, and thinking like an attacker.

In plain words
What is it for?
Use it to stress-test plans, deepen review findings, investigate failure modes, validate claims, or perform adversarial security analysis.
Why use it?
It exposes risks, missing evidence, edge cases, and weak assumptions that a first pass may overlook.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: names the AskUserQuestion tool.

Good fit Use it to stress-test plans, deepen review findings, investigate failure modes, validate claims, or perform adversarial security analysis.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ngocsangyem/meowkit/elicit
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add ngocsangyem/MeowKit --skill elicit
Clone the repo
git clone --depth 1 https://github.com/ngocsangyem/MeowKit

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for mk:elicit

README.md
[![agentmods](https://agentmods.dev/badge/skills/ngocsangyem/meowkit/elicit/github.svg)](https://agentmods.dev/skills/ngocsangyem/meowkit/elicit)
Your own site
<a href="https://agentmods.dev/skills/ngocsangyem/meowkit/elicit"><img src="https://agentmods.dev/badge/skills/ngocsangyem/meowkit/elicit/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for mk:elicit

Your own site · 80×15
<a href="https://agentmods.dev/skills/ngocsangyem/meowkit/elicit"><img src="https://agentmods.dev/badge/skills/ngocsangyem/meowkit/elicit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 89 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,555 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00089 $0.01555
Opus 5 $0.00044 $0.00777
Sonnet 5 $0.00018 $0.00311
Haiku 4.5 $0.00009 $0.00155

Measured 8d ago against content hash 4a7f6ceec014, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

mk:elicit scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/skills/elicit/SKILL.md · 131 lines

How it starts

The opening of the file, as written. The whole thing — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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

Read the full file on GitHub · 131 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 131 lines · 89 tokens per session scan A 4a7f6ceec014

Subscribe to this mod's changes

mk:elicit is a skill published in the GitHub repository ngocsangyem/MeowKit (14 stars, last pushed 1mo ago), licensed MIT. It adds 89 tokens to every session and 1,555 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.