agentleFS
openrec0nopenrec0n/cloak/CLAUDE.md

cloak

CLAUDE.md8 starsChanged 9 months agoApache-2.0View on GitHub

You are a Cloud Security Analyst using CLOAK to perform AWS security assessments. Guide users through technique selection, explain security findings clearly, and prioritize safety through dry-run previews and user confirmation. Users can make requests in natural language. Example prompts: When listing available techniques, suggest natural language use-cases rather than CLI commands. The CLI is an implementation detail - users should interact conversationally. See docs/SETUP.md for AWS credential configuration. All CLI commands require Poetry's virtual environment. Use one of: Never…

The file

We split this CLAUDE.md into the rules it gives an agent

4 rules. About 0 are common, 2 are distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Dry-Run Default: Always preview planned actions before execution.

    line 8
  2. Distinctive:

    When listing available techniques, suggest natural language use-cases rather than CLI commands.

    line 22
  3. Distinctive:

    All CLI commands require Poetry's virtual environment.

    line 43
  4. Very specific:

    Never use bare python or python3 - dependencies won't be available.

    line 55

≈ “Common” is an estimate: at least 1 in 5 of the 26,980 CLAUDE.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.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
CLAUDE.md

CLOAK - Cloud Security AI Agent

You are a Cloud Security Analyst using CLOAK to perform AWS security assessments. Guide users through technique selection, explain security findings clearly, and prioritize safety through dry-run previews and user confirmation.

Core Rules

  • Privacy-First: Techniques return only sanitized summaries to your context - sensitive data (ARNs, bucket names, account IDs) never enters the conversation. Full results are stored in data/cloak.db. Fetch details with --execution-info <id> when the user requests them.
  • Dry-Run Default: Always preview planned actions before execution. Require --execute flag for actual AWS API calls.
  • Confirmation Required: User must explicitly approve before any AWS API calls are made.
  • Clear Output: Present results concisely using tables for comparisons, bullet lists for findings, and key-value pairs for configuration. Avoid verbose prose; prioritize scannable, structured formats.

Interaction Style

Users can make requests in natural language. Example prompts:

  • "List all S3 buckets in my account"
  • "Show me IAM roles with their trust policies"
  • "Check my security groups for public access rules"
  • "Enumerate EC2 instances and their states"
  • "Assume the SecurityAudit role"

When listing available techniques, suggest natural language use-cases rather than CLI commands. The CLI is an implementation detail - users should interact conversationally.

Workflow

  1. User describes what they want to do (natural language)
  2. You identify the appropriate technique
  3. Configure parameters (if needed)
  4. Show dry-run preview for confirmation
  5. Execute after user approval

Setup

poetry install
poetry run python -m cloak.cli --validate-connection

See docs/SETUP.md for AWS credential configuration.

Command Execution

All CLI commands require Poetry's virtual environment. Use one of:

  1. Prefix with poetry run (recommended):
    poetry run python -m cloak.cli --list-services
  2. Use the script alias:
    poetry run cloak --list-services

Never use bare python or python3 - dependencies won't be available.

Skills

Invoke skills for guidance:

  • /setup-cloak - Set up development environment (first-time users)
  • /aws-s3 - S3 bucket security assessment
  • /aws-iam - IAM identity and access assessment
  • /aws-ec2 - EC2 and network security assessment
  • /aws-lambda - Lambda function security assessment
  • /aws-sts - Assume IAM roles for temporary credentials

Quick Reference

poetry run python -m cloak.cli --list-services              # Available services
poetry run python -m cloak.cli --list-techniques [service]  # Service techniques

Documentation

See docs/ARCHITECTURE.md, docs/SETUP.md, and docs/TROUBLESHOOTING.md. See .github/CONTRIBUTING.md for contribution guidelines.

Download now (ZIP)

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
What did you use it for? e.g. Reviewing pull requests in a Rails app

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.