ffuf-web-fuzzing
Expert guidance for ffuf web fuzzing during authorized penetration testing. Covers directory discovery, subdomain enumeration,…
Researches a topic from the last 30 days on Reddit, X, and the web. Surfaces real community discussions with engagement metrics and synthesizes findings into actionable insights. Use when the user wants to know what people are saying about a topic right now.
$ npx -y skills add trailofbits/skills-curated --skill last30days --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/last30daysContext preview
The summary Claude sees to decide when to auto-load this skill.
Researches a topic from the last 30 days on Reddit, X, and the web. Surfaces real community discussions with engagement metrics and synthesizes findings into actionable insights. Use when the user wants to know what people are saying about a topic right now.
name: last30days description: "Researches a topic from the last 30 days on Reddit, X, and the web. Surfaces real community discussions with engagement metrics and synthesizes findings into actionable insights. Use when the user wants to know what people are saying about a topic right now." argument-hint: 'nano banana pro prompts, NVIDIA news, best AI video tools' allowed-tools: - Bash - Read - Write - AskUserQuestion - WebSearch - mcp__exa__web_search_exa
Research ANY topic across Reddit, X, and the web. Surface what people are actually discussing, recommending, and debating right now.
Before doing anything, parse the user's input for:
1. **TOPIC**: What they want to learn about (e.g., "web app mockups", "Claude Code skills", "image generation") 2. **TARGET TOOL** (if specified): Where they'll use the prompts (e.g., "Nano Banana Pro", "ChatGPT", "Midjourney") 3. **QUERY TYPE**: What kind of research they want:
Common patterns:
**IMPORTANT: Do NOT ask about target tool before research.**
**Store these variables:**
**DISPLAY your parsing to the user.** Before running any tools, output:
I'll research {TOPIC} across Reddit, X, and the web to find what's been discussed in the last 30 days.
Parsed intent:
- TOPIC = {TOPIC}
- TARGET_TOOL = {TARGET_TOOL or "unknown"}
- QUERY_TYPE = {QUERY_TYPE}
Starting now.If TARGET_TOOL is known, mention it in the intro: "...to find {QUERY_TYPE}-style content for use in {TARGET_TOOL}."
This text MUST appear before you call any tools. It confirms to the user that you understood their request.
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**Step 1: Run the research script**
python3 "{baseDir}/scripts/last30days.py" "$ARGUMENTS" --emit=compact 2>&1The script will automatically:
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The script auto-detects sources (API keys, etc). While waiting for it, do WebSearch.
For **ALL modes**, do WebSearch to supplement (or provide all data in web-only mode).
Choose search queries based on QUERY_TYPE:
**If RECOMMENDATIONS** ("best X", "top X", "what X should I use"):
**If NEWS** ("what's happening with X", "X news"):
**If PROMPTING** ("X prompts", "prompting for X"):
**If GENERAL** (default):
For ALL query types:
**Options** (passed through from user's command):
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**After all searches complete, internally synthesize (don't display stats yet):**
The Judge Agent must: 1. Weight Reddit/X sources HIGHER (they have engagement signals: upvotes, likes) 2. Weight WebSearch sources LOWER (no engagement data) 3. Identify patterns that appear across ALL three sources (strongest signals) 4. Note any contradictions between sources 5. Extract the top 3-5 actionable insights
**Do NOT display stats here - they come at the end, right before the invitation.**
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**CRITICAL: Ground your synthesis in the ACTUAL research content, not your pre-existing knowledge.**
Rea
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