From justokenmax
Compresses PDFs to Markdown, downscales large images, and digests verbose logs to reduce token costs. Run manually or let the Read hook auto-optimize heavy attachments.
How this skill is triggered — by the user, by Claude, or both
Slash command
/justokenmax:attachmentsThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
The silent token sinks in a session are the heavy things you feed in: PDFs
The silent token sinks in a session are the heavy things you feed in: PDFs (ingested as ~1,500-token page images per page), oversized screenshots, and verbose logs (thousands of near-identical lines). justokenmax turns each into a cheap, faithful equivalent.
.pdf whose contents are needed → PDF → page-delimited Markdown..png/.jpg/.jpeg/.webp over a couple hundred KB → downscale ≤1568px +
recompress + strip metadata..log or pasted build/test/CI output that's long and repetitive →
digest: ANSI stripped, repeated lines collapsed (×N), stack traces
folded, errors/warnings + head/tail kept.The Read hook does the common case automatically — a Read on a .pdf, large
image, or .log is transparently rewritten to read the cheap artifact. Use this
skill for manual/batch runs and to report savings.
justokenmax optimize spec.pdf screenshot.png build.log # auto-dispatch by type
justokenmax pdf report.pdf # force PDF → Markdown
justokenmax image diagram.png --max-edge 1280 # force image compression
justokenmax logs ci-output.log # force log digest
justokenmax stats # lifetime token savings
Add --json for machine-readable output. If justokenmax isn't on PATH, use
python3 -m justokenmax <args> with the plugin's python/ dir on PYTHONPATH.
Read the optimized artifact the command reports (.md, .log.txt, or the
compressed image), not the original. Everything is cached by content hash, so
re-running on an unchanged file is free and reversible — the original is one
read away.
npx claudepluginhub kalmantic/justokenmax --plugin justokenmaxConverts heavy document formats (PDF, Word, Excel, PowerPoint, and others) to token-efficient Markdown/CSV with structurally-aware digest compression. Use when Claude needs to read documents without excessive context budget.
Reads huge, dense, read-only text as rendered PNG pages to reduce token costs by ~60–75%. Use for skimming big files, vendored code, diffs, or logs you won't edit or byte-copy.
Compresses LLM-facing Markdown files like CLAUDE.md and ARCHITECTURE.md for token efficiency using lossless structural optimization or lossy semantic rewriting.