Postgres Rls
CheckedEnforces granular row-level security policies in PostgreSQL databases using reinforcement learning for optimal access control.
Install on your platform
Showing Claude Code. One command installs this skill into any of the agents below.
- 1
Run this in your project
terminal$ npx skills add troykelly/codex-skills --skill postgres-rls -a claude-code Uses the open-source
skillsCLI and needs Node.js. Add-gto install it for your user instead of this project.
What we know about this skill
Publisher
troykelly
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Install target
Live repository
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Automated safety checks
This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.
Declares what it does: passed
SKILL.md parses and declares a name and a description.
SKILL.md exists, its frontmatter parses, and it declares a name and a description.
No undeclared network calls: passed
Makes no network calls.
Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.
No obfuscated payloads: passed
No encoded or obfuscated payloads.
No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.
No credential access: passed
Reads no keys, tokens, keychains or credential files.
Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.
No pipe-to-shell installers: passed
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No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.
Pinned to a commit: passed
Scanned troykelly/codex-skills at d8fb3968e4.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.
- Commit
- d8fb3968e4
- Manifest
- skills/postgres-rls/SKILL.md
- Scanned
- 1 file, 358 lines
About this skill
What it does
This skill allows AI agents to interact with and manage PostgreSQL databases using Row Level Security (RLS). It enables fine-grained access control, ensuring that users can only see and modify data they are authorized to. The agent can create, update, and delete RLS policies directly within the database.
When to use it
- Data Masking: Implement dynamic masking of sensitive data based on user roles or attributes.
- Multi-Tenant Applications: Control access to data in a multi-tenant environment where different tenants should not see each other's records.
- Compliance Requirements: Enforce specific data access rules required by regulatory compliance mandates (e.g., GDPR, HIPAA).
- Secure Reporting: Generate reports that only include data the user is permitted to view.
Key capabilities
- Create RLS policies
- Update existing RLS policies
- Delete RLS policies
- Manage database permissions related to RLS
Example prompts
- "Create an RLS policy on the 'orders' table that only allows users in the 'sales' role to view orders assigned to their team."
- "Modify the existing RLS policy for the 'products' table to restrict access based on a user’s region attribute."
- “Delete the RLS policy applied to the ‘employees’ table.”
Tips & gotchas
- Requires a PostgreSQL database instance with appropriate permissions.
- RLS policies can be complex; careful planning and testing are essential to avoid unintended consequences.