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Read huge dense read-only text as PNG pages via pxpipe export: ~60-75% fewer input tokens. Lossy on exact strings; never for files you will edit.
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
| name | honey-px |
| description | Read huge dense read-only text as PNG pages via pxpipe export: ~60-75% fewer input tokens. Lossy on exact strings; never for files you will edit. |
| homepage | https://github.com/Green-PT/honey-for-devs |
| license | MIT |
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.
% saved, skip if it's low. Sparse prose loses money.old_string must be byte-exact; imaged reads
aren't. Read the real file (with offset/limit) before any edit.Grep the source first.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:
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.percentSaved as the go/no-go — if it printed low,
read the text instead.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.
Compress-Cache-Retrieve huge repetitive array tool output before it hits context: keep a sample, cache the rest, leave a hash.
Compress-Cache-Retrieve for huge, repetitive array tool output (logs, scan results, time series, event streams) before it enters context. Keeps an informative sample — endpoints, anomalies/change-points, head/tail — drops the redundant rest to a local cache, and leaves a retrievable hash. Use when a tool returns a long uniform JSON array you must read but mostly skim, and the full set is one command away if needed. Lossy-but-recoverable.
Write less code and say less about it: YAGNI, stdlib-first, terse prose. Cuts agent token cost on every coding and writing task.
Write less code and say less about it. Applies YAGNI and stdlib/native-first so the agent writes the minimum code that needs to exist, and responds tersely — stripping filler, hedging, and pleasantries while keeping code, identifiers, and technical terms exact. Use whenever writing, modifying, refactoring, reviewing, or explaining code, or any response where output volume drives token cost — even if the user never says "minimal" or "concise". Especially in agentic coding, where the volume of generated code and prose runs up the bill.
Honey for plain Claude — the terse-prose core with no agent-harness features. Paste into a claude.ai Project's custom instructions, a Style, or an API system prompt. Strips filler, hedging, and pleasantries from every response while keeping facts, names, numbers, steps, and code exact. No tools required.
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.