Honey Px logo

Honey Px

Organization
Green-PT
honey-px

Read huge, dense, read-only text as rendered PNG pages instead of raw text — image tokens scale with pixels, not characters, so token-dense bulk (big files, vendored code, diffs, logs) costs ~60–75% less as an image. Use when you must skim or reason over thousands of lines you will NOT edit or byte-copy. Lossy on exact strings: never for files you'll Edit, secrets, hashes, or byte-exact values. Fable-class readers only.

Overview

PublisherGreen-PT
Repositoryhoney-for-devs
Skill namehoney-px
Stars
342
Forks
22
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Green-PT on GitHub. Read the source before you install it.

Installation

Install the Honey Px AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Green-PT/honey-for-devs/tree/main/plugins/honey/skills/honey-px
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Green-PT/honey-for-devs.git /tmp/honey-for-devs
mkdir -p .claude/skills
cp -r /tmp/honey-for-devs/plugins/honey/skills/honey-px .claude/skills/honey-px
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Honey Px in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Honey Px on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Honey Px is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Honey PX

An image's token cost is fixed by its pixel area, not its character count. Dense text packs ~3 chars per image-token vs ~1 as text, so a 90k-char file read as PNG pages costs a fraction of the text read. pxpipe export (teamchong/pxpipe) does the rendering; the agent Reads the pages.

Lossy by design — misreads of exact strings are silent confabulations, not errors. The export writes a factsheet.txt carrying the verbatim precision tokens (paths, SHAs, ids, numbers) as text alongside the images; always read it too.

When to use

  • Bulk is read-only reference: skimming a big vendored file, a large diff for review context, docs, generated code — content you reason over, not byte-copy.
  • Dense (code, JSON, logs) and big — worth it above ~6k chars; the export prints % saved, skip if it's low. Sparse prose loses money.
  • The reader is Fable-class. Opus misreads ~7% of renders; other models degrade — read as text there.

Don't use

  • Files you will Edit — old_string must be byte-exact; imaged reads aren't. Read the real file (with offset/limit) before any edit.
  • Secrets, hashes, ids, numeric values you'll act on — treat anything exact recalled from an image as unverified; re-Grep the source first.
  • Anything the user asked to see verbatim, or that gets written back.
  • Small or sparse content — the fixed pixel cost loses.

How

sh
npx pxpipe-proxy export --json --out <scratchpad> <file-or-dir>   # or --git / --diff <ref> / --stdin

Output dir pxpipe-export-<hash>/ contains page-*.png, factsheet.txt, manifest.json (token report). Then:

  1. Read every page-*.png and factsheet.txt. If instead you pass the renders to a model over the raw API (subagent prompt, panel), include the export's prompt.txt banner — naked dense renders can trip stop_reason: refusal on Fable-class models; the banner prevents it.
  2. Treat the manifest's percentSaved as the go/no-go — if it printed low, read the text instead.
  3. Before acting on any exact string seen only in an image, verify it against the source with Grep.

Cheaper still is not reading at all — Grep/offset/limit (Lever 3b) and eson crush (CCR) come first. PX is for when you genuinely need the whole bulk in view.

Frequently asked questions

What does the Honey Px AI skill do?

Read huge, dense, read-only text as rendered PNG pages instead of raw text — image tokens scale with pixels, not characters, so token-dense bulk (big files, vendored code, diffs, logs) costs ~60–75% less as an image. Use when you must skim or reason over thousands of lines you will NOT edit or byte-copy. Lossy on exact strings: never for files you'll Edit, secrets, hashes, or byte-exact values. Fable-class readers only.

Why use Honey Px on TypingMind?

Because you install it once and use it with any model. Honey Px is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Honey Px in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Green-PT/honey-for-devs/tree/main/plugins/honey/skills/honey-px. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Honey Px?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Honey Px?

As many as you like. As long as a model supports skills, you can use Honey Px with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Honey Px AI skill free?

Yes. It is published on GitHub by Green-PT under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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