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Agent skill

Text Watermark Fountain

by cafe3310 in cafe3310/public-agent-skills

A specialized skill for embedding and extracting resilient watermarks in text by manipulating sentence lengths and using Fountain Codes.

MITAuto-check passedAI & LLM Engineering

Install Text Watermark Fountain

skills CLI
$ npx skills add cafe3310/public-agent-skills --skill text-watermark-fountain -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install cafe3310/public-agent-skills text-watermark-fountain --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/cafe3310/public-agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills_parked/text-watermark-fountain .claude/skills/text-watermark-fountain && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
text-watermark-fountain
GitHub stars
255
Token cost
~921 tokens
SKILL.md length
460 words
Files
5 (incl. scripts)
Skills in repo
29
Repo updated
First seen
Licence
MIT

At a glance

A specialized skill for embedding and extracting resilient watermarks in text by manipulating sentence lengths and using Fountain Codes.

  • Works in 3 steps: Sync Markers: The encoding script… → Self-Synchronization: The decoder… → Redundancy: By repeating these frames…
  • Wants to add a hidden
  • SKILL.md covers How it works (Robustness…, Workflow: Embedding a Watermark, Workflow: Extracting a Watermark and Guidelines for the Agent
  • Runs Python scripts from its folder

What it does

Text Watermark Fountain is an agent skill from cafe3310/public-agent-skills. A specialized skill for embedding and extracting resilient watermarks in text by manipulating sentence lengths and using Fountain Codes. Use this when the user wants to add a hidden, robust watermark to text or verify an existing one.

Its SKILL.md is about 920 tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts (for example `FOR_HUMAN.md`, `scripts/decode.py` and `scripts/encode.py`).

It sits in AI & LLM Engineering, covering Embeddings. The repository describes itself as: personal agent skills for better QoL. The licence is MIT.

When your agent uses it

  • Wants to add a hidden
  • Robust watermark to text
  • Verify an existing one

Example prompts

  • “/text-watermark-fountain”

Requirements

  • Python 3

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. Sync Markers: The encoding script periodically inserts a unique length pattern [19, 4, 19] (Sync Marker) followed by a Frame ID.
  2. Self-Synchronization: The decoder searches the entire text for these markers using a sliding window. Even if middle segments are removed…
  3. Redundancy: By repeating these frames throughout a long text, the watermark becomes extremely difficult to destroy.

What it can do on your machine

Read from SKILL.md and the folder at commit 6c45501. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 3 files in scripts/ (Python), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Text Watermark Fountain loads about 921 tokens when it runs. Until then it costs about 65 tokens; SKILL.md has 460 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~65
When it runs · the whole SKILL.md, loaded when a task matches
~921

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from cafe3310/public-agent-skills at commit 6c45501, republished under its MIT licence (© cafe3310). 460 words, ~921 tokens.

Download SKILL.mdSave it as .claude/skills/text-watermark-fountain/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
text-watermark-fountain
description
A specialized skill for embedding and extracting resilient watermarks in text by manipulating sentence lengths and using Fountain Codes. Use this when the user wants to add a hidden, robust watermark to text or verify an existing one.
license
MIT
author
github/cafe3310
depends_on_binary
python3

Text Watermark Fountain (Robust Sync-Frame Version)

This skill enables the Agent to embed a string watermark into a text such that it can be recovered even if the text is partially modified, segments are deleted, or new sentences are inserted. It uses a custom Luby Transform (LT) Fountain Code combined with Sync Frames to map the watermark into a sequence of target lengths.

How it works (Robustness Mechanism)

  1. Sync Markers: The encoding script periodically inserts a unique length pattern [19, 4, 19] (Sync Marker) followed by a Frame ID.
  2. Self-Synchronization: The decoder searches the entire text for these markers using a sliding window. Even if middle segments are removed, the decoder can resynchronize using the next Sync Marker and know exactly which symbols it is looking at.
  3. Redundancy: By repeating these frames throughout a long text, the watermark becomes extremely difficult to destroy.

Workflow: Embedding a Watermark

When a user asks to embed a watermark (e.g., "name_1") into a text:

  1. Generate Length Sequence:

    • Run the encoding script:
      bash
      python3 scripts/encode.py --mark "name_1" --count [TOTAL_DATA_SYMBOLS]
    • Note the Lengths output. It will contain periodic 19 4 19 [ID] headers.

  2. Precise Text Fine-tuning (Batch Processing): To ensure 100% accuracy, you MUST use a multi-stage approach:

    • Step 2.1: Redundancy & Looping: If the original text is significantly longer than the required length sequence, the script handles the symbol indexing. Just ensure you cover all target lengths.
    • Step 2.2: Segmentation: Split the source text into segments using allowed punctuation (，。！？；：、, . ! ? ; :).
    • Step 2.3: Batch Delegation: Use a subagent to rewrite segments in batches of 5-10.
      • Prompt for Subagent: "Rewrite these segments to match EXACT character lengths: [L1, L2, ...]. Maintain meaning. NO internal punctuation allowed within a segment. Count every character (Chinese, English, digits) as 1."
    • Step 2.4: Verification: After each batch, run a Python one-liner to verify:
      bash
      python3 -c "print([len(s.strip()) for s in [SEG1, SEG2, ...]])"

  3. Final Polishing & Formatting:

    • Step 3.1: Style Alignment: Compare the verified segments with the original text. Refine phrasing to match the original's tone, but STRICTLY maintain the verified character count.
    • Step 3.2: Paragraph Reconstruction: Re-insert original line breaks. Paragraph breaks (\n) do not affect length measurement.

  4. Output:

Show full SKILL.md (99 more words)Show less
  • Provide the final watermarked text to the user.

Workflow: Extracting a Watermark

  1. Run Decoder:
    • Pass the text to the decoding script:
      bash
      python3 scripts/decode.py --text "THE_TEXT_CONTENT"
    • The script will search for sync frames and use the LT decoder to recover the mark.

Guidelines for the Agent

  • Precision is Absolute: A single character error in a segment breaks that data symbol.
  • Punctuation is a Splitter: Do NOT use punctuation inside a segment unless you intend to split it.
  • Sync Frames are Sacred: The 19 4 19 [ID] sequence must be embedded exactly as specified in the output of encode.py.

© cafe3310, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (scripts) in skills_parked/text-watermark-fountain of cafe3310/public-agent-skills.

  • SKILL.md
  • FOR_HUMAN.md
  • scripts/decode.py
  • scripts/encode.py
  • scripts/lt_code.py

Open the folder on GitHubat commit 6c45501

Compare with similar skills

Text Watermark Fountain next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Text Watermark Fountain compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Text Watermark Fountain this skillcafe3310/public-agent-skills255—~921Automated safety check: PassMIT
Chroma Vector DatabaseOrchestra-Research/AI-Research-SKILLs13k7 repos~2.3kAutomated safety check: PassMIT
SageMaker Serving Image Selectionhuggingface/skills11k1 repos~4.6kAutomated safety check: PassApache-2.0
Codebase Managementgiancarloerra/SocratiCode3.3k1 repos~1.8kAutomated safety check: PassAGPL-3.0
CLIP Image-Text MatchingOrchestra-Research/AI-Research-SKILLs13k7 repos~1.7kAutomated safety check: PassMIT
Sentence-Transformers Training Routerhuggingface/skills11k1 repos~2.6kAutomated safety check: PassApache-2.0

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Categories

Questions about Text Watermark Fountain

What does Text Watermark Fountain do?

A specialized skill for embedding and extracting resilient watermarks in text by manipulating sentence lengths and using Fountain Codes. Text Watermark Fountain is an agent skill from cafe3310/public-agent-skills. A specialized skill for embedding and extracting resilient watermarks in text by manipulating sentence lengths and using Fountain Codes.

When should I use Text Watermark Fountain?

Text Watermark Fountain fits situations like: wants to add a hidden; robust watermark to text; verify an existing one.

How do I install Text Watermark Fountain in Claude Code?

Run `npx skills add cafe3310/public-agent-skills --skill text-watermark-fountain -a claude-code`. Or copy the skill folder (skills_parked/text-watermark-fountain in cafe3310/public-agent-skills) into .claude/skills/text-watermark-fountain in your project. Claude Code loads it when a task matches its description.

How do I install Text Watermark Fountain in Codex?

Run `npx skills add cafe3310/public-agent-skills --skill text-watermark-fountain -a codex`. Or copy the skill folder (skills_parked/text-watermark-fountain in cafe3310/public-agent-skills) into .agents/skills/text-watermark-fountain in your project. Codex loads it when a task matches its description.

Can I use Text Watermark Fountain in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add cafe3310/public-agent-skills --skill text-watermark-fountain -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/text-watermark-fountain, .gemini/skills/text-watermark-fountain, .github/skills/text-watermark-fountain and .opencode/skills/text-watermark-fountain in your project.

What does Text Watermark Fountain need to run?

Going by SKILL.md and its folder, Text Watermark Fountain needs Python for the scripts in its folder. Our summary lists: Python 3.

Does Text Watermark Fountain access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Text Watermark Fountain safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Text Watermark Fountain use?

Text Watermark Fountain is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Text Watermark Fountain use?

About 921 tokens (SKILL.md is roughly 3.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Text Watermark Fountain?

Skills that share tags, products or a category with Text Watermark Fountain: Chroma Vector Database (Orchestra-Research/AI-Research-SKILLs, 13k stars), SageMaker Serving Image Selection (huggingface/skills, 11k stars), Codebase Management (giancarloerra/SocratiCode, 3.3k stars) and CLIP Image-Text Matching (Orchestra-Research/AI-Research-SKILLs, 13k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Text Watermark Fountain?

cafe3310 (a GitHub user) maintains it in cafe3310/public-agent-skills, which has 255 GitHub stars. The repository holds 29 skills in this directory. The repository was last updated on June 26, 2026.

Source: cafe3310/public-agent-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.