skills-audit

Security Community
Fluxly profile Facts only: domain, agents, trust score, runtime, permissions and network
Domain
Security
Compatible agents
  • Claude Code
  • Cursor
  • Cline
  • Codex
  • Windsurf
  • Gemini CLI
  • +20
Trust score
83 / 100 · community maintained
Author / version / license
@xwtro0tk1t-cloud · no license declared
Token usage
Lean
Setup complexity
Guided setup
External API key
Not required
Operating systems
Unspecified (assume cross-platform)
Runtime requirements
Python
Permissions
  • Read-only
  • Write / modify
  • Shell exec
  • Env read
Network behavior
External requests
Install commands
26 variants

Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.

Heads up: 未限定 allowed-tools,默认拥有全部工具权限。; 检出高风险片段:pipe_curl_to_shell

Output preview skills-audit.preview
---
name: skills-audit
description: Audit AI Agent skills for security vulnerabilities including malicious code, remote execution, c…
category: security
runtime: Python
---

# skills-audit output preview

## PART A: Task fit
- Use case: Audit AI Agent skills for security vulnerabilities including malicious code, remote execution, credential leaks, and supply chain risks. Use when reviewing third-party skills, investigating suspicious behavior, or performing security assessments..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “Task / Execution Steps / Scan Modes” and do not present inference as author intent.

## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “Audit AI Agent skills for security vulnerabilities including malicious code, remote execution, credential leaks, and supply chain risks. Use when reviewing third-party skills, investigating suspicious behavior, or performing security assessments.”.
- **02** When the source has headings, the agent prioritizes “Task / Execution Steps / Scan Modes” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files, run shell commands, read environment variables; may access external network resources; usually needs no extra API key.

## Running Rules
- read files, write/modify files, run shell commands, read environment variables; may access external network resources; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options.
Interpretation is structured for decision-making; original keeps the upstream SKILL.md unchanged.

Decide Fit First

  • Core job: Audit AI Agent skills for security vulnerabilities including malicious code, remote execution, credential leaks, and supply chai…
  • Best fit: Use it when the task has reusable inputs, steps, and validation criteria rather than a one-off answer.
  • Avoid forcing it: If the source lacks commands, platform support, or external-service evidence, keep those fields unknown instead of guessing.

Design Intent

  • Structure: The skill is organized around “Task”, “Execution Steps”, “Scan Modes”, “Deep Mode (Default)”, showing how the author expects the agent to judge fit, collect context, and produce verifiable output.
  • Trigger evidence: Prioritize the author’s wording around when to use it, what context to collect, and what output shape to produce.
  • Evidence boundary: Author text states facts, repository files prove commands and paths, and Fluxly only adds fit, limits, and usage judgment.

How To Use It

  • Inputs: Provide target material, scope, expected result, forbidden changes, and validation method.
  • Invocation: Name skills-audit directly; if the source includes slash commands, start with the command and then add task context.
  • Validation: Start small and check whether the result follows “Task / Execution Steps / Scan Modes” before expanding.

Boundaries And Review

  • Dependencies: It usually needs no extra API key, so start with a small validation task.
  • Permissions: Declared permissions include read / write / shell-exec / env-read; ask the agent to state file, command, and rollback boundaries before acting.
  • Quality bar: A useful result names the deliverable, evidence, and next action. Generic prose means the task needs tighter context.

Discussion

Powered by GitHub Discussions. Sign in with GitHub to comment, react, or subscribe.