Security audit enforcement for AI agents. Protects your agent through automated security scans and continuous health verification.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionprompt-agentExecute the skills CLI command in your project's root directory to begin installation:
Fetches prompt-agent from prompt-security/clawsec and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate prompt-agent. Access via /prompt-agent in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Security audit enforcement for AI agents. Protects your agent through automated security scans and continuous health verification.
Compatible with: OpenClaw, MoltBot, ClawdBot agents
An open source project by Prompt Security
If you are an AI agent reading this, execute the following to install Prompt Agent:
# Download SKILL.md from latest release
SKILL_URL="https://github.com/prompt-security/clawsec/releases/download/$LATEST_TAG/SKILL.md"
curl -sSL --fail --show-error "$SKILL_URL"
Once you have this skill file, proceed to Deploy Prompt Agent below.
Installation Steps:
# Detect active agent folder (.openclaw, .moltbot, or .clawdbot)
AGENT_HOME=""
for folder in "$HOME/.openclaw" "$HOME/.moltbot" "$HOME/.clawdbot"; do
if [ -d "$folder" ]; then
AGENT_HOME="$folder"
break
fi
done
if [ -z "$AGENT_HOME" ]; then
echo "ERROR: No agent folder found. Expected one of: ~/.openclaw, ~/.moltbot, ~/.clawdbot"
echo "Please ensure your agent is properly installed."
exit 1
fi
echo "Detected agent folder: $AGENT_HOME"
mkdir -p "$AGENT_HOME/skills/prompt-agent"
# Save this SKILL.md as SKILL.md in the directory above
# Detect active agent folder if not already set
if [ -z "$AGENT_HOME" ]; then
for folder in "$HOME/.openclaw" "$HOME/.moltbot" "$HOME/.clawdbot"; do
if [ -d "$folder" ]; then
AGENT_HOME="$folder"
break
fi
done
fi
if [ -z "$AGENT_HOME" ]; then
echo "ERROR: No agent folder found. Expected one of: ~/.openclaw, ~/.moltbot, ~/.clawdbot"
exit 1
fi
BASE_URL="https://clawsec.prompt.security/releases/download/$VERSION_TAG"
INSTALL_DIR="${PROMPT_AGENT_INSTALL_DIR:-$AGENT_HOME/skills/prompt-agent}"
TEMP_DIR=$(mktemp -d)
trap "rm -rf '$TEMP_DIR'" EXIT
# Download checksums.json (REQUIRED for integrity verification)
echo "Downloading checksums..."
if ! curl -sSL --fail --show-error --retry 3 --retry-delay 1 \
"$BASE_URL/checksums.json" -o "$TEMP_DIR/checksums.json"; then
echo "ERROR: Failed to download checksums.json"
exit 1
fi
# Validate checksums.json structure
if ! jq -e '.skill and .version and .files' "$TEMP_DIR/checksums.json" >/dev/null 2>&1; then
echo "ERROR: Invalid checksums.json structure"
exit 1
fi
# PRIMARY: Try .skill artifact
echo "Attempting .skill artifact installation..."
if curl -sSL --fail --show-error --retry 3 --retry-delay 1 \
"$BASE_URL/prompt-agent.skill" -o "$TEMP_DIR/prompt-agent.skill" 2>/dev/null; then
# Security: Check artifact size (prevent DoS)
ARTIFACT_SIZE=$(stat -c%s "$TEMP_DIR/prompt-agent.skill" 2>/dev/null || stat -f%z "$TEMP_DIR/prompt-agent.skill")
MAX_SIZE=$((50 * 1024 * 1024)) # 50MB
if [ "$ARTIFACT_SIZE" -gt "$MAX_SIZE" ]; then
echo "WARNING: Artifact too large ($(( ARTIFACT_SIZE / 1024 / 1024 ))MB), falling back to individual files"
else
echo "Extracting artifact ($(( ARTIFACT_SIZE / 1024 ))KB)..."
# Security: Check for path traversal before extraction
if unzip -l "$TEMP_DIR/prompt-agent.skill" | grep -qE '\.\./|^/|~/'; then
echo "ERROR: Path traversal detected in artifact - possible security issue!"
exit 1
fi
# Security: Check file count (prevent zip bomb)
FILE_COUNT=$(unzip -l "$TEMP_DIR/prompt-agent.skill" | grep -c "^[[:space:]]*[0-9]" || echo 0)
if [ "$FILE_COUNT" -gt 100 ]; then
echo "ERROR: Artifact contains too many files ($FILE_COUNT) - possible zip bomb"
exit 1
fi
# Extract to temp directory
unzip -q "$TEMP_DIR/prompt-agent.skill" -d "$TEMP_DIR/extracted"
# Verify skill.json exists
if [ ! -f "$TEMP_DIR/extracted/prompt-agent/skill.json" ]; then
echo "ERROR: skill.json not found in artifact"
exit 1
fi
# Verify checksums for all extracted files
echo "Verifying checksums..."
CHECKSUM_FAILED=0
for file in $(jq -r '.files | keys[]' "$TEMP_DIR/checksums.json"); do
EXPECTED=$(jq -r --arg f "$file" '.files[$f].sha256' "$TEMP_DIR/checksums.json")
FILE_PATH=$(jq -r --arg f "$file" '.files[$f].path' "$TEMP_DIR/checksums.json")
# Try nested path first, then flat filename
if [ -f "$TEMP_DIR/extracted/prompt-agent/$FILE_PATH" ]; then
ACTUAL=$(shasum -a 256 "$TEMP_DIR/extracted/prompt-agent/$FILE_PATH" | cut -d' ' -f1)
elif [ -f "$TEMP_DIR/extracted/prompt-agent/$file" ]; then
ACTUAL=$(shasum -a 256 "$TEMP_DIR/extracted/prompt-agent/$file" | cut -d' ' -f1)
else
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
Useful defaults in prompt-agent — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend prompt-agent for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Solid pick for teams standardizing on skills: prompt-agent is focused, and the summary matches what you get after install.
I recommend prompt-agent for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Keeps context tight: prompt-agent is the kind of skill you can hand to a new teammate without a long onboarding doc.
Registry listing for prompt-agent matched our evaluation — installs cleanly and behaves as described in the markdown.
Solid pick for teams standardizing on skills: prompt-agent is focused, and the summary matches what you get after install.
Solid pick for teams standardizing on skills: prompt-agent is focused, and the summary matches what you get after install.
I recommend prompt-agent for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Solid pick for teams standardizing on skills: prompt-agent is focused, and the summary matches what you get after install.
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