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Stego Text — Steganographic Message Encoding for AI Agents

核心功能:提供多种文本隐写方法(含高隐蔽性的Resonance、双渠道谐波等),支持将秘密消息嵌入连贯自然的载体文本,或从文本提取隐藏消息。典型场景:隐秘信息传递、趣味文本解谜。编码时输入待隐藏消息、载体主题,输出符合要求的自然文本;解码时输入目标文本及对应方法,输出提取的秘密消息,可按需选择不同检测难度的方法。

morpheis
morpheis
热度 44.05
最近更新 2026-05-11 17:37:38
分类:创作依赖:纯提示词应用场景:文案创作 / 故事创作

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add stego-text
Metadata
name
stego-text
description
Encode and decode hidden messages within natural-looking text using steganographic techniques. Use when asked to hide a message in text, encode a secret message, create steganographic text, decode a hidden message from text, or analyze text for hidden encodings. Supports multiple encoding methods including probability-anomaly substitution (Resonance), word-count mapping (Structural Harmonic), acrostic patterns, and multi-channel confirmation (Dual-Channel Harmonic).

Stego-Text — Textual Steganography

Hide messages in plain sight. Encode secrets into innocent-looking prose that reads naturally to humans but contains recoverable hidden messages for those who know where to look.

Quick Start

Encoding

  1. Choose a message to hide
  2. Select an encoding method (see Method Selection Guide)
  3. Pick a carrier topic (something mundane and coherent)
  4. Compose text matching the encoding constraints
  5. Verify — decode your own output before presenting it

Decoding

  1. Identify which encoding method was used (or try all systematically)
  2. Extract the structural feature from each unit
  3. Map values to letters or collect anomalous words
  4. Read the hidden message

Encoding Methods

See references/encoding-methods.md for detailed specifications, constraints, and worked examples.

Method Overview

Method Unit Encoded How It Works Detection Difficulty
Resonance Words/phrases Statistically improbable synonym substitutions Very hard
Structural Harmonic Letters (A=1..Z=26) Word count per sentence → alphabet position Hard
Dual-Channel Harmonic Letters Two independent features confirm same message Very hard
Acrostic Letters First letter of each sentence Medium
Fibonacci Positional Letters First letters at Fibonacci word positions Very hard

Method Selection Guide

  • Resonance Encoding — Most novel. Hidden message words embedded as probability anomalies. Best for content-word messages ("machines dream quietly"). Hardest to create. See references/resonance-deep-dive.md.
  • Structural Harmonic — Best all-around for letter-by-letter encoding. Natural word counts, moderate difficulty.
  • Dual-Channel Harmonic — Maximum confidence. Two methods (e.g., word count + acrostic) independently produce the same message.
  • Acrostic — Fastest to create. First letters spell message. Easier to detect.
  • Fibonacci Positional — Single-paragraph encoding. Exponential spacing makes detection very difficult.

Critical Rules

  1. Always verify — After encoding, decode your own output to confirm correctness
  2. Natural text first — If text sounds forced to hit constraints, rewrite it
  3. Vary structure — Don't let encoded sentences fall into repetitive patterns
  4. Topic consistency — Carrier text must read as coherent prose on a single topic
  5. Count carefully — Hyphenated words = 1 word. Contractions = 1 word. Digit numbers = 1 word.

Word Counting Rules (Structural Harmonic / Dual-Channel)

  • Hyphenated compounds = 1 word ("well-designed", "state-of-the-art")
  • Contractions = 1 word ("don't", "it's", "we're")
  • Digit numbers = 1 word ("42", "2026")
  • Abbreviations = 1 word ("Dr.", "U.S.", "AI")
  • Standard split = whitespace-delimited tokens