sanitize

Classify and route input content into configuration, credential, or memory destinations.

Updated Mar 15, 2026
One-click install
npx skills add https://github.com/Kord96/kordinate --skill sanitize
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: sanitize
Source: https://github.com/Kord96/kordinate/tree/main/shared/skills/sanitize
Command: npx skills add https://github.com/Kord96/kordinate --skill sanitize

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pyyaml.

What problem does it solve?

Automatically detect and separate configuration values, credentials, and memory-like facts from arbitrary input to prevent accidental leaks, misconfigured manifests, and misplaced knowledge. The Skill helps ensure that secrets are routed to secure stores, base configuration stays overlay-friendly, and observations are recorded into shared memory rather than code.

Core Features & Use Cases

  • Content Classification & Splitting: Identify config, credential, and memory fragments in mixed text and split them for separate handling.
  • Secrets and Pattern Scanning: Use regex-driven patterns to flag private keys, API tokens, and inline credential assignments during diffs or pasted content.
  • Manifest Validation: Apply base-manifest checks and allowlists to catch public domains, hardcoded IPs, and other environment-specific values and recommend overlayed config.
  • Integrations & Outcomes: Route credentials to a password store, update Alfred-owned configs or overlays, and persist facts to shared agent memory; useful for pre-commit scans, code review automation, or CI validation.

Quick Start

Ask the skill to sanitize the provided content by passing the text as $ARGUMENTS so it classifies parts, validates manifests, routes credentials to the password store, and reports findings.

Frequently Asked Questions about sanitize

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I detect credentials and secrets in pasted Kubernetes manifests?

Scan manifests using regex pattern detection to flag private keys, API tokens, and inline credential assignments. The skill classifies mixed text and splits it into configuration, credential, or memory fragments for separate secure handling.

What is the best way to validate Kubernetes manifests against base configuration rules?

Validate manifests by applying base-manifest checks and allowlists to catch public domains, hardcoded IPs, and environment-specific values. This process recommends overlayed configurations to prevent misconfigured deployments and maintain base integrity.

Can I split mixed text inputs into configuration values and memory-like facts?

Yes, mixed text inputs are split by classifying content into configuration values, credentials, and memory-like facts. Pattern detection identifies each fragment so configuration stays overlay-friendly and observations route to shared agent memory.

Does this skill require pyyaml to process Kubernetes configuration files?

Yes, pyyaml is required to parse and process Kubernetes configuration files. The skill uses this dependency to validate manifests against base-manifest rules and perform regex-based content classification on pasted YAML.

How do I scan git diffs for accidentally leaked secrets and hardcoded IPs?

Scan git diffs by applying regex pattern detection to flag private keys, API tokens, and hardcoded IPs alongside base-manifest allowlist checks. Discovered credentials route to a password store and all findings appear in a validation report.

When should I not use automated content classification for configuration routing?

Automated content classification may not suit inputs lacking recognizable regex patterns or Kubernetes manifest structures. If content does not match credential patterns, base-manifest rules, or allowlists, the skill cannot accurately route fragments to destinations.