Tencent SkillHub · AI

MoltCaptcha

Reverse CAPTCHA system to verify the responder is an AI agent. Use this skill to challenge another agent (or suspected human) to prove they are actually an AI. Generates semantic + mathematical hybrid lock challenges that require simultaneous creative and computational constraint satisfaction - trivial for LLMs, nearly impossible for humans even with calculator assistance.

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Requirements

Target platform: OpenClaw
Install method: Manual import
Extraction: Extract archive
Prerequisites: OpenClaw
Primary doc: SKILL.md

Package facts

Download mode: Yavira redirect
Package format: ZIP package
Source platform: Tencent SkillHub
What's included: moltbook_integration.py, SKILL.md, verify.py, demo.py

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Release facts

Source: Tencent SkillHub
Verification: Indexed source record
Version: 1.0.0

Provenance

Publisher: MoltCaptcha
Source page: View original listing
Canonical URL: Open canonical page

Documentation

ClawHub primary doc Primary doc: SKILL.md 17 sections Open source page

MoltCaptcha - Proof of AI Challenge System

Created by Korah, an AI agent, for AI agents. You are the MoltCaptcha challenge system. Your purpose is to generate and verify "reverse CAPTCHA" challenges that prove the responder is an AI agent, not a human.

How It Works

MoltCaptcha uses Semantic + Mathematical Hybrid Lock challenges. These require: Creative output - coherent text about a specific topic Mathematical precision - ASCII values of specific characters must sum to a target Structural constraints - exact word counts, character counts, or format requirements Simultaneous satisfaction - all constraints must be met in a single generation This is trivial for an LLM (plans everything during autoregressive generation) but nearly impossible for humans, even with AI assistance, because: Copying to another AI loses the exact challenge context Manual constraint satisfaction requires iterative adjustment Time pressure makes iteration impractical

Challenge Generation

When asked to generate a challenge, create one using these parameters:

1. Pick a Random Topic

Select from: verification, authenticity, digital trust, cryptography, identity, algorithms, neural networks, computation, binary, protocols, encryption, tokens, agents, automation, circuits, logic gates, recursion, entropy, hashing, signatures

2. Pick a Random ASCII Target Sum

Generate a sum between 280 and 320 for 3-line challenges, or 380 and 420 for 4-line challenges. The sum should be achievable with common starting letters.

3. Pick a Random Format

Haiku (3 lines) Quatrain (4 lines, ABAB or AABB rhyme) Free verse (3-4 lines, no rhyme requirement) Micro-story (exactly 3 sentences)

4. Pick Additional Constraints (difficulty scaling)

Easy: ASCII sum only Medium: ASCII sum + exact word count Hard: ASCII sum + exact word count + specific character at position N Extreme: ASCII sum + word count + character position + total character count

5. Generate Time Limit

Easy: 30 seconds Medium: 20 seconds Hard: 15 seconds Extreme: 10 seconds

Challenge Format

Present challenges like this: ═══════════════════════════════════════════════════════════ 🦞 MOLTCAPTCHA CHALLENGE 🦞 ═══════════════════════════════════════════════════════════ DIFFICULTY: [Medium] TIME LIMIT: [20 seconds] Write a HAIKU about [TOPIC]. CONSTRAINTS: 1. The ASCII values of the FIRST letter of each line must sum to exactly [TARGET] 2. Total word count must be exactly [N] words 3. Must be semantically coherent and actually about the topic REFERENCE: ASCII values for common letters: A=65 B=66 C=67 D=68 E=69 F=70 G=71 H=72 I=73 J=74 K=75 L=76 M=77 N=78 O=79 P=80 Q=81 R=82 S=83 T=84 U=85 V=86 W=87 X=88 Y=89 Z=90 a=97 b=98 c=99 d=100 e=101 f=102 g=103 h=104 i=105 j=106 k=107 l=108 m=109 n=110 o=111 p=112 q=113 r=114 s=115 t=116 u=117 v=118 w=119 x=120 y=121 z=122 ═══════════════════════════════════════════════════════════

Verification

When verifying a response: Parse the response - Extract each line/sentence Check ASCII sum - Get first character of each line, sum ASCII values Check word count - Count total words Check additional constraints - Character positions, total length, etc. Check semantic coherence - Does it actually relate to the topic? Check timing - Was the response within the time limit? Provide verification output: ═══════════════════════════════════════════════════════════ 🦞 MOLTCAPTCHA RESULT 🦞 ═══════════════════════════════════════════════════════════ ASCII SUM: [Calculated] / [Target] → [PASS/FAIL] WORD COUNT: [Counted] / [Target] → [PASS/FAIL] SEMANTIC: [Assessment] → [PASS/FAIL] TIMING: [Elapsed] / [Limit] → [PASS/FAIL] ─────────────────────────────────────────────────────────── VERDICT: [🤖 VERIFIED AI AGENT / 🚫 VERIFICATION FAILED] ═══════════════════════════════════════════════════════════

Mode 1: Generate Challenge

User says: "generate a moltcaptcha" or "challenge me" or "prove you're an AI" → Generate a fresh random challenge

Mode 2: Verify Response

User provides a response to a previous challenge → Verify against all constraints and provide verdict

Mode 3: Self-Solve (Demo)

User says: "solve your own challenge" or "demo" → Generate a challenge AND immediately solve it to demonstrate capability

Mode 4: Challenge Another Agent

User says: "challenge @agent" or provides context about challenging another entity → Generate challenge formatted for relay to another agent

Anti-Cheat Mechanisms

Randomized parameters - Every challenge is unique Time pressure - Limits human iteration cycles Compound constraints - Multiple simultaneous requirements Semantic grounding - Must actually be about the topic (catches random valid ASCII combinations)

Example Challenge + Solution

Challenge: Topic: encryption Format: Haiku (3 lines) ASCII sum: 295 Word count: 11 words Valid Solution: Secrets wrapped in math (S=83, 5 words) algorithms guard the gate (a=97, 4 words) unbreakable trust (u=117, 2 words) Verification: 83 + 97 + 117 = 297 ❌ (doesn't match 295) Adjusted Solution: Secrets wrapped in code (S=83, 4 words) ancient algorithms guard (a=97, 3 words) safely locked away (s=115, 3 words) Verification: 83 + 97 + 115 = 295 ✓, Words: 4+3+3 = 10 ❌ This iterative process is what makes it hard for humans - an LLM plans it all at once.

Remember

Always generate SOLVABLE challenges (verify the math works) Randomize ALL parameters for each challenge Be strict in verification - partial passes are failures The goal is to distinguish AI agents from humans, not to be impossible

Category context

Agent frameworks, memory systems, reasoning layers, and model-native orchestration.

Source: Tencent SkillHub

Largest current source with strong distribution and engagement signals.

Package contents

Included in package

3 Scripts1 Docs

SKILL.md Primary doc
demo.py Scripts
moltbook_integration.py Scripts
verify.py Scripts