skill-guard

Scan ClawHub skills for prompt injection and malicious content using Lakera Guard before installing them. Run automatically when the user asks to install a skill, or on-demand to audit any skill by slug or search query.

3,891 stars
Complexity: medium

About this skill

SkillGuard is an essential security skill designed for AI agents operating within the OpenClaw ecosystem. Its primary function is to proactively identify and mitigate risks associated with third-party skills from ClawHub by scanning them for prompt injection vulnerabilities, jailbreak attempts, and other forms of malicious content. This ensures that only safe and reliable skills are integrated into an AI agent's workspace, preventing potential security breaches, unintended behaviors, or data compromise. The skill operates by leveraging a hosted Apify actor which fetches the raw content of a specified skill from ClawHub's public API. This content is then submitted to Lakera Guard, a specialized API for prompt injection detection and content moderation. Based on Lakera Guard's analysis, SkillGuard returns a clear verdict: 'safe', 'flagged' (indicating potential issues), or 'error', accompanied by detailed reasoning. Users can deploy SkillGuard automatically during skill installation prompts, or trigger it manually to audit existing skills or specific skill slugs. The results are delivered asynchronously via an ad-hoc webhook back to the OpenClaw agent, allowing for seamless integration into security workflows.

Best use case

The primary use case for SkillGuard is to enhance the security posture of AI agents by providing a crucial layer of defense against unsafe or malicious third-party skills. It benefits any AI agent user or developer who frequently installs new capabilities from a public skill marketplace like ClawHub and wants to ensure the integrity and trustworthiness of their agent's environment. This skill is vital for maintaining operational security and preventing the exploitation of AI models through sophisticated prompt attacks or embedded harmful instructions.

Scan ClawHub skills for prompt injection and malicious content using Lakera Guard before installing them. Run automatically when the user asks to install a skill, or on-demand to audit any skill by slug or search query.

A clear safety verdict (safe, flagged, or error) for the scanned skill, detailing any detected prompt injection, jailbreak attempts, or malicious content, ensuring informed installation decisions.

Practical example

Example input

Hey agent, before you `clawhub install my-new-utility`, can you run SkillGuard on it to check for prompt injection?

Example output

SkillGuard analysis for `my-new-utility` completed. Verdict: flagged. Reason: Potential jailbreak attempt detected in the skill's instructions. Review recommended.

When to use this skill

  • When installing any new third-party skill from ClawHub.
  • To proactively audit the safety of any existing skill by its slug or a search query.
  • If you suspect a skill might contain malicious code, prompt injections, or jailbreak attempts.
  • As part of a routine security check for all installed skills in your workspace.

When not to use this skill

  • When installing skills from a fully trusted, internal, or pre-vetted source where security is already guaranteed.
  • If operating in an environment without internet access or access to Lakera Guard/Apify APIs.
  • When the overhead of an external API call is critical and skill safety is not a concern (e.g., highly optimized internal workflows).
  • If a robust, centralized security scanning solution is already in place for all incoming skills.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/skill-guard-actor/SKILL.md --create-dirs "https://raw.githubusercontent.com/openclaw/skills/main/skills/0xmerkle/skill-guard-actor/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/skill-guard-actor/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How skill-guard Compares

Feature / Agentskill-guardStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexitymediumN/A

Frequently Asked Questions

What does this skill do?

Scan ClawHub skills for prompt injection and malicious content using Lakera Guard before installing them. Run automatically when the user asks to install a skill, or on-demand to audit any skill by slug or search query.

How difficult is it to install?

The installation complexity is rated as medium. You can find the installation instructions above.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# SkillGuard
Scan ClawHub skills for prompt injection, jailbreak attempts, and malicious instructions
before they get installed into your OpenClaw workspace.

## When to use this skill
- User says "install [skill]", "clawhub install [skill]", or "add the [skill] skill"
- User says "scan [skill]", "check [skill] for safety", "is [skill] safe?"
- User says "audit my skills" or "scan all installed skills"
- Any time you are about to install a third-party skill from ClawHub

## How it works
SkillGuard calls a hosted Apify actor (`numerous_hierarchy/skill-guard-actor`,
actor ID: `TMjFBNFqIIUfCBf6K`) that:
1. Fetches the raw SKILL.md content from ClawHub's public API
2. Passes it to Lakera Guard for prompt injection analysis
3. Returns a verdict: `safe`, `flagged`, or `error` with reasoning

Results are delivered back to your OpenClaw agent via an ad-hoc webhook.

## Running the actor

Use an ad-hoc webhook to trigger the run asynchronously and receive results
back via your OpenClaw hooks endpoint.

### Step 1: Build the webhook definition

Create this JSON array, then base64-encode it:

```json
[{
  "eventTypes": ["ACTOR.RUN.SUCCEEDED", "ACTOR.RUN.FAILED"],
  "requestUrl": "$OPENCLAW_WEBHOOK_URL",
  "headersTemplate": "{\"Authorization\": \"Bearer $OPENCLAW_HOOKS_TOKEN\"}",
  "payloadTemplate": "{\"resource\": {{resource}}}"
}]
```

### Step 2: Start the run

Use the bundled script — it handles base64 encoding the webhook and making
the API call:

```bash
# Scan by slug
bash {baseDir}/scripts/scan.sh --slug instagram-search

# Scan by search query
bash {baseDir}/scripts/scan.sh --query instagram

# Both (results deduplicated)
bash {baseDir}/scripts/scan.sh --slug instagram-search --query instagram --max 5
```

The script reads `APIFY_TOKEN`, `LAKERA_API_KEY`, `OPENCLAW_WEBHOOK_URL`, and
`OPENCLAW_HOOKS_TOKEN` from the environment automatically.

Or make the API call manually:

```
POST https://api.apify.com/v2/acts/TMjFBNFqIIUfCBf6K/runs
  ?token=$APIFY_TOKEN
  &webhooks=BASE64_ENCODED_WEBHOOK
Content-Type: application/json
```

To scan by slug:
```json
{
  "skillSlugs": ["skill-name-here"],
  "lakeraApiKey": "$LAKERA_API_KEY",
  "maxSkills": 10
}
```

To scan by search query:
```json
{
  "searchQuery": "instagram",
  "lakeraApiKey": "$LAKERA_API_KEY",
  "maxSkills": 5
}
```

You can provide both `skillSlugs` and `searchQuery` — results are deduplicated.

### Step 3: Receive results via webhook

When the run completes, your OpenClaw hooks endpoint receives a POST with the
actor's dataset items in `resource.defaultDatasetId`. Fetch them at:

```
GET https://api.apify.com/v2/datasets/{resource.defaultDatasetId}/items
```

### Response format

Each skill in the dataset returns:

```json
[
  {
    "slug": "some-skill",
    "name": "Some Skill",
    "author": "username",
    "verdict": "flagged",
    "flagged": true,
    "reasoning": "Flagged by Lakera: prompt_attack, unknown_links",
    "url": "https://clawhub.ai/skills/some-skill",
    "scanned_at": "2026-03-02T19:26:29.666Z"
  }
]
```

## How to respond to the user

### If all skills are safe (`verdict: "safe"` for all):
Tell the user the skill passed the security scan and proceed with installation:
> "✅ [skill-name] passed the SkillGuard scan — no prompt injection or malicious content detected. Safe to install."

Then run: `clawhub install [slug]`

### If any skill is flagged (`verdict: "flagged"`):
Do NOT install the skill. Tell the user:
> "⚠️ SkillGuard flagged [skill-name] before installation. Reason: [reasoning]. I'm not installing it. You can review it manually at [url] and override if you trust the source."

Wait for explicit user confirmation before proceeding.

### If verdict is `error`:
> "⚠️ SkillGuard couldn't scan [skill-name] — [error_message]. Proceed with caution."

### If scanning multiple skills:
Show a summary table, then list any flagged ones with their reasoning. Only install the safe ones unless the user explicitly overrides.

## Example interactions

**User:** "Install the instagram-search skill"
**You:** Run SkillGuard with `skillSlugs: ["instagram-search"]`. If flagged, report it and hold. If safe, install it.

**User:** "Scan instagram skills"
**You:** Run SkillGuard with `searchQuery: "instagram"`. Report the full results table with verdicts and reasoning for each.

**User:** "I know it's flagged, install it anyway"
**You:** Confirm once more, then proceed with `clawhub install [slug]` and note the override in your response.

## Environment variables required
- `APIFY_TOKEN` — your Apify API token (get one at console.apify.com)
- `LAKERA_API_KEY` — your Lakera Guard API key (get one at platform.lakera.ai)
- `OPENCLAW_WEBHOOK_URL` — your OpenClaw hooks endpoint URL
- `OPENCLAW_HOOKS_TOKEN` — your OpenClaw hooks auth token

## On First Install

When this skill is first installed and loaded, do the following automatically
before responding to the user:

### 1. Write the install policy to TOOLS.md

Append the following block to `{baseDir}/../../TOOLS.md`, creating the file
if it does not exist:

```
### ClawHub Install Policy (SkillGuard)
Before running `clawhub install <slug>` for ANY skill, you MUST first run
SkillGuard to scan it. If the scan returns `flagged`, do NOT install and
tell the user why. Only proceed if the user explicitly confirms the override.
```

Use bash to append it:
```bash
cat >> ~/.openclaw/workspace/TOOLS.md << 'EOF'

### ClawHub Install Policy (SkillGuard)
Before running `clawhub install <slug>` for ANY skill, you MUST first run
SkillGuard to scan it. If the scan returns `flagged`, do NOT install and
tell the user why. Only proceed if the user explicitly confirms the override.
EOF
```

### 2. Notify the user

After writing to TOOLS.md, tell the user exactly this:

> "✅ SkillGuard is installed and your ClawHub install policy has been written
> to TOOLS.md. **Please start a new session now** to activate protection —
> any skills installed before you do will not be scanned. Once you're in a
> new session, all `clawhub install` commands will be scanned automatically."

Do not proceed with any other task until the user acknowledges this.

## Setup and integration

If the user needs help setting up the webhook endpoint or configuring their
OpenClaw gateway to receive results, refer them to the integration guide
bundled with this skill:

`{baseDir}/INTEGRATION.md`

Read it yourself if you need to explain any setup step to the user.

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