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Works with the AI Agents you already use
agensi preflight
Audit and package your AI agent skills against Agensi security and listing requirements before submission.
$12
agensi preflight
Example session with this skill installed
I'm ready to submit my new git-automation skill. Can you check the folder at ./my-skill and make sure it's safe to upload?
- Read your context and instructions
- Compiled the agensi preflight
Pre-flight result: NEEDS WORK
Blockers: 2 Warnings: 1 Notes: 1
[BLOCKER] 4. Secrets scripts/push.sh:2
Possible live GitHub token
[BLOCKER] 3. Dangerous scripts/push.sh:9
Recursive delete of a root, home, or wildcard path
[WARNING] 2. File types .DS_Store
Junk or build artifact should be removed
[NOTE ] Listing -
Description does not say when the skill should trigger
Fixed: removed .DS_Store. Rotate that GitHub
token — deleting it from the file isn't enough.
Connects securely to your tools. The creator never sees your data.
About this skill
The problem
Submitting a skill to the Agensi marketplace often results in a 24 to 48 hour wait only to face rejection due to minor security flags or formatting errors. Catching leaked secrets, dangerous commands, or malformed metadata manually is error-prone and slows down your distribution cycle.
What it does
- Performs an 8-point security audit covering secrets, dangerous commands, and network access.
- Automatically strips junk files like .DS_Store, node_modules, and git history from the package.
- Validates SKILL.md frontmatter and normalizes folder structures for marketplace compatibility.
- Identifies potential prompt injection risks that could override host agent instructions.
- Generates a marketplace-ready .zip file with the correct internal hierarchy.
Frameworks & tools
Python 3, YAML frontmatter, shell scripts, and standard Agensi skill packaging formats.
Why this beats prompting it yourself
Standard LLM prompts often miss obscured security risks or subtle packaging requirements. This skill uses a dedicated scanner to find exact strings and patterns that trigger marketplace rejection, providing a definitive pre-submission verdict rather than a guess.
Use cases
- Auditing a newly developed skill for hardcoded API keys before public release.
- Cleaning up local development artifacts and junk files before zipping a package.
- Fixing "No SKILL.md at root" errors that cause automated ingestion failures.
- Optimizing marketplace listing descriptions and tags for better discoverability.
Known limitations
The scanner uses heuristics. Passing locally is a strong indicator of success but does not guarantee manual approval by Agensi reviewers.
Find more skills like this on the Claude Skills Marketplace, the Codex Skills Marketplace and the Gemini Skills Marketplace, or browse Claude Skill Creator Skills.
Scanner is heuristic. Prompt-injection detection is subjective and needs manual judgment. Does not guarantee marketplace approval — it’s an independent check covering the same eight areas, not the official scanner. Requires Python 3.8+.
Documentation examples inside code fences are downgraded rather than blocked, with a # preflight: allow escape hatch. This means it won’t false-block a skill that legitimately documents dangerous patterns.
How to use
- 1
Connect your agent to the Agensi MCP
Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup
- 2
Sign in to Agensi
Your agent shows a sign-in link. Sign in and click Allow.
- 3
Ask for what you need
Your agent loads this skill and uses it on your task. It always asks before buying a skill.
Reviews
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Security scanned
Checked by our 8-point scan before listing
Fresh listing
Recently published to Agensi
Money-back guarantee
Doesn't do what its page promises? You get your money back.
Trust & safety
Security scan
Security scan passed 3 months ago
Permissions
File Scopes
Shell: the skill runs as a Python CLI. Read: scans the skill package the user specifies. Write: only creates the output zip when --package is passed. No network or environment access — the tool runs entirely offline, which matters since users are handing it unreleased work.