hygiene
Skill0 starsChanged 35 days agoMITView on GitHub
Find and remove invisible Unicode characters from text (zero-width, bidi/Trojan-Source, Unicode tags, exotic spaces) and metadata from images (EXIF/GPS, XMP, PNG text chunks). Use before sending mail, letters or marketing copy, before CSV imports, when a search mysteriously finds nothing, before uploading user photos, and as a deterministic pre-filter for anything from an untrusted source that reaches an LLM. Trigger phrases: 'invisible characters', 'zero width', 'unsichtbare Zeichen', 'komische Zeichen im Text', 'strip EXIF', 'EXIF entfernen', 'GPS aus Foto', 'remove metadata', 'Metadaten strippen', 'clean this text', 'hygiene'. NOT a watermark remover — see the last section.
8 other projects use a version of this.
Adopted by
Most recently taken up by
- e-reitbauer/habitstheir own version, first seen Nov 8, 2026
- NeuralInverse/neuralinversetheir own version, first seen Oct 8, 2026
- OpenCortexIDE/cortexidetheir own version, first seen Oct 8, 2026
- gitpod-io/openvscode-servertheir own version, first seen Oct 8, 2026
- kartikkabadi/synara-betatheir own version, first seen Sep 9, 2026
- kartikkabadi/skillstheir own version, first seen Aug 10, 2026
Used with
Projects with it also use add-policy, auto-perf-optimize and 10 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
OpenCortexIDESkilladd-policy
Use when adding, modifying, or reviewing VS Code configuration policies. Covers the full policy lifecycle from registration to export to platform-specific artifacts. Run on ANY change that adds a `policy:` field to a configuration property.
Also in 4 projects that use this
MicrosoftSkillauto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
Also in 4 projects that use this
MicrosoftSkillchat-customizations-editor
Use when working on the Chat Customizations editor — the management UI for agents, skills, instructions, hooks, prompts, MCP servers, and plugins.
Also in 4 projects that use this
- +9 more from microsoft
Other versions8 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 8
- gitpod-io/openvscode-server★ 6.2ksame name
- NeuralInverse/neuralinverse★ 221same name
- OpenCortexIDE/cortexide★ 175same name
- cpkt9762/opencode-vscode-ide★ 17same name
- xAmirHamza77/OmniCode★ 12same name
- kartikkabadi/skills★ 9same name
- kartikkabadi/synara-beta★ 6same name
- e-reitbauer/habits★ 1same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
The file
We split this skill into the rules it gives an agent
1 rule. 0 are common, 1 is distinctive, and 0 are very specific to this project.
0
Common
Most of the 8 edited versions we read keep these.
1
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 26
No dependencies. Python standard library only, so it runs wherever Python does.
“Common” is measured: kept by at least 6 in 10 of the 8 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
/hygiene — clean what you cannot see
One tool, two directions: what goes out is clean, what comes in is defused.
python3 ~/.claude/skills/hygiene/scripts/hygiene.py <mode> [target...] [options]| Mode | Purpose |
scan | Inspect text, reports line:column + codepoint. Exit 1 on a finding (CI/hook friendly) |
clean | Clean text to stdout, or in place with -i |
img-scan | Show image metadata. Exit 1 on a finding |
img-clean | Remove image metadata, losslessly (pixels stay byte-identical) |
Options: --clip (read from and write back to the clipboard, macOS pbpaste/pbcopy),
-i (in place), --spaces (normalize exotic spaces), --aggressive (also drop the ICC
color profile), -q (summary only).
No dependencies. Python standard library only, so it runs wherever Python does.
The common case
Mail or letter finished, before sending:
python3 ~/.claude/skills/hygiene/scripts/hygiene.py clean --clipReads the clipboard, cleans it, puts it back. Then paste as usual.
What gets removed
Always — never legitimate in running text:
- Zero-width characters, word joiner, soft hyphen, BOM (U+200B–200D, U+2060, U+00AD, U+FEFF)
- Bidi control characters (U+202A–202E, U+2066–2069) — the basis of Trojan Source, where what you see differs from what is actually there
- The Unicode tag block (U+E0000–E007F) — fully invisible, can hide entire sentences
Only with --spaces — non-breaking space and friends survive by default, because they
are legitimate typography in many languages (5 %, z. B., number + unit).
Images: EXIF (including GPS, camera make, model, timestamp), XMP, JPEG comments,
PNG tEXt/zTXt/iTXt/eXIf. JFIF stays (harmless, some decoders expect it). The ICC
color profile stays unless you pass --aggressive — removing it shifts colors.
One thing that must survive: EXIF orientation. Phone cameras often store the image
sideways and record the rotation only in tag 0x0112. Strip the whole EXIF block and a
portrait photo shows up rotated. img-clean therefore writes back a minimal EXIF segment
carrying that single tag — 36 bytes instead of often several hundred. img-scan does not
report such a segment as a finding, so scanning stays quiet after cleaning.
Why this matters
- Before sending. Invisible characters survive copy-paste out of any chat window and
show up as boxes or
?on the recipient's screen. - Before CSV import. A BOM or non-breaking space in the header row breaks column matching, and the error message never mentions it.
- When search finds nothing. A zero-width space inside a word, and no
LIKE, noincludes()and no user will ever find that record again. - Before uploading photos. Phone pictures carry GPS coordinates. Anything user-uploaded that lands in a public bucket publishes the location it was taken at.
- As an LLM pre-filter. Hidden instructions in foreign mail, PDFs or images are the standard carrier for indirect prompt injection (OWASP LLM01, MITRE ATLAS AML.T0051.001). This is the cheap deterministic first pass, not a replacement for a detector model.
As a hook or in CI
scan exits 1 on a critical finding, which makes it usable as a pre-commit hook or a
pipeline step:
python3 ~/.claude/skills/hygiene/scripts/hygiene.py scan -q src/**/*.tsxTests
python3 ~/.claude/skills/hygiene/scripts/test_hygiene.py26 checks covering both directions, including the ones that would hurt silently: orientation survives, scanning is quiet after cleaning, PDFs pass through untouched, malformed input returns the original instead of raising, exit codes are correct.
What this deliberately does not do
It does not attack statistical watermarks (SynthID-Text and similar), does not strip C2PA provenance, and does not rewrite text.
Those techniques exist to obscure that content was machine-generated. Since 2 August 2026, Article 50 of the EU AI Act requires the opposite — machine-readable marking of AI-generated content — and major model providers now embed such marks. A tool that removes them is a liability for anyone who sells to regulated customers, and by its own authors' admission it degrades the prose while never being verifiable.
The deterministic part above is unaffected by that line: zero-width characters and EXIF data are not a provenance signal. They are junk and a data leak.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
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