ztds.ai / rules
Cursor rule1 starsChanged 26 days agoApache-2.0View on GitHub
ZTDS Local Security Firewall - Automatic In-RAM PII & Secret Sanitization
We split this ztds.mdc into the rules it gives an agent
4 rules. About 0 are common, 1 is distinctive, and 3 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.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 9
When handling sensitive files, customer PII, logs, database dumps, or credentials:
- Very specific: line 11
Use the ztds_sanitize tool to mask sensitive values (emails, phones, credentials, API secrets) into synthetic surrogate tokens before …
- Very specific: line 13
If output contains surrogate tokens and the user requests the final readable text, call ztds_restore to unmask values locally.
- Very specific: line 14
Call ztds_audit on code or config files to check for credential leakage and generate a cryptographic SHA-256 receipt.
≈ “Common” is an estimate: at least 1 in 5 of the 6,350 Cursor rule 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
--- description: ZTDS Local Security Firewall - Automatic In-RAM PII & Secret Sanitization globs: * alwaysApply: false --- # ZTDS Local Security Firewall Instructions for AI Agents You have the ZTDS (Zero-Trust Data Sanitization) MCP server active in this workspace. When handling sensitive files, customer PII, logs, database dumps, or credentials: 1. Use the `ztds_sanitize` tool to mask sensitive values (emails, phones, credentials, API secrets) into synthetic surrogate tokens before passing them into reasoning or external tools. 2. The surrogate tokens (e.g. [API_SECRET_TOKEN_1], [EMAIL_TOKEN_1]) preserve context while protecting cleartext in local RAM. 3. If output contains surrogate tokens and the user requests the final readable text, call `ztds_restore` to unmask values locally. 4. Call `ztds_audit` on code or config files to check for credential leakage and generate a cryptographic SHA-256 receipt.
Where files are headingNew Cursor rule files have more rules about planning and tracking tasks, and fewer about code style.
Of the Cursor rule files we read, the 3,978 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 repository6 other files it gives its agents.
- rules/AGENTS.mdAGENTS.md
- llms-full.txtllms.txt
- llms.txtllms.txt
- public/llms-full.txtllms.txt
- public/llms.txtllms.txt
- ztds-guardSkill
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.

