sunglasses
AGENTS.md11 starsChanged 30 days agoMITView on GitHub
For coding agents (Claude Code, Codex, Cursor, Aider, or a human who wants the short version). Everything here is checkable against the repo; if a line stops being true, fix the line. Sunglasses inspects content before an AI agent acts on it, and reports what it found and what it could not read. The whole value is that second half. A tool that says "clean" about a file it never opened is worse than no tool, because someone will trust…
- Commits and pushes
Where files are headingNew AGENTS.md files have more rules about keeping secrets out of the code, and fewer about code style.
Of the AGENTS.md files we read, the 31,439 first seen in the last six months, against the older ones: the kind of rule that gained most share, and the kind that lost most. About files like this in general, not this one, and an estimate, since a kind is a pattern in the words.
In this repositoryOne other file it gives its agents.
- CLAUDE.mdCLAUDE.md
The file
We split this AGENTS.md into the rules it gives an agent
1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
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 87
Adding a badge, metric, or claim you have not verified: If you cannot point at the command that produced a number, do not publish the …
≈ “Common” is an estimate: at least 1 in 5 of the 40,246 AGENTS.md files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
AGENTS.md — working in this repo as an AI agent
For coding agents (Claude Code, Codex, Cursor, Aider, or a human who wants the short version). Everything here is checkable against the repo; if a line stops being true, fix the line.
What this project is, in one paragraph
Sunglasses inspects content before an AI agent acts on it, and reports what it found and what it could not read. The whole value is that second half. A tool that says "clean" about a file it never opened is worse than no tool, because someone will trust it. Every change you make here is judged against that.
Run the tests
python3 -m pytest -q # from the repo root, with NO path argumentpytest.ini pins testpaths on purpose. On 2026-08-28 two honest reviewers
measured 780 and 778 passing on the same commit, because two root-level tests
only collect when pytest runs from root scope. Passing an explicit path
re-creates that ambiguity — a bare run from the root is the only measurement
anyone should quote.
It still reproduces. Try it:
$ python3 -m pytest -q --collect-only # 1397 tests collected
$ python3 -m pytest -q --collect-only tests # 1395 tests collectedTwo tests, same commit, different answer — decided entirely by an argument you did or did not type.
What CI actually runs
.github/workflows/pattern-integrity.yml, on six Python versions —
3.9, 3.10, 3.11, 3.12, 3.13, 3.14 — all fully blocking, none informational.
It installs real native decoders (tesseract-ocr, libzbar0, ffmpeg) and
pins Pillow (12.3.0; 3.9 necessarily takes 11.3.0). That is not incidental: a
missing decoder turns a real finding into silence, so a green run without them
proves nothing about media scanning. If you touch image, QR, PDF or audio paths,
assume the decoder version matters until you have shown it does not.
The truth layer — do not hand-edit published numbers
stats/current.json is the single source for every published figure: pattern
count, category count, keyword count, language count, version. README stats,
site JSON-LD and package metadata are generated from it.
- Never hand-edit a number in
README.md, the CHANGELOG, or the version string to make something look consistent. It will be overwritten, and in the meantime you have published a claim with no generator behind it. stats/verified-sources.ymlholds every URL we cite, with the date it was last fetched and confirmed 200. Never guess a URL from memory — if the one you need is not there, fetch it yourself and add it with today's date.
The fixture rule
Every pattern change needs two fixtures: one it must fire on, and one it must not. See CONTRIBUTING.md for the worked example.
A pattern with only a positive test has not been shown to discriminate — .*
passes that bar. The benign control is the whole test. Keep attack-db/ and
sunglasses/patterns.py in sync; a pattern in one and not the other is a
half-landed change.
The exit-code contract
0 clean · 1 threat found · 2 usage or operational error · 3 incomplete
inspection. Precedence is 1 > 3 > 2 > 0.
0 and 3 must never collapse into each other. "I read it and found nothing"
and "I could not open it, so I saw nothing" are different facts, and a CI job
consuming our exit status is entitled to tell them apart. If you are changing
anything that returns a status, prove all four paths still return what they say.
Things that look helpful and are not
- Widening a regex to make a test pass. A pattern broad enough to catch every attack in the corpus catches your users' clean code too, and false positives are how a security tool gets uninstalled.
- Silencing an "incomplete" report because it is noisy. That report is the product.
- Adding a badge, metric, or claim you have not verified. If you cannot point at the command that produced a number, do not publish the number.
git pushtomain. Branch and open a PR, always.
What to do when you are unsure
Say so in the PR, in the section the template gives you for exactly this. A disclosed limitation costs nothing. A quiet one gets found by whoever was depending on it.
Security
Found a bypass? That is a contribution, and it is the most useful thing you can bring us. If it affects a real system or is a working exploit, report it privately — see SECURITY.md — rather than in a public issue or PR.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- 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.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

