feat: Smart query detection for better research results
Added QUERY_TYPE detection:
- RECOMMENDATIONS ("best X") → searches for lists, extracts specific names
- NEWS → searches for current events
- HOW-TO → searches for tutorials
- GENERAL → broad topic research
For RECOMMENDATIONS queries, synthesis now extracts specific entity names
with mention counts instead of generic patterns.
Example: "best Claude Code skills" now returns:
"Most mentioned: /commit (5x), remotion (4x), git-worktree (3x)"
Instead of:
"Skills are good. Keep them under 500 lines."
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
Matt Van Horn
@@ -8,9 +8,15 @@ disable-model-invocation: true
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allowed-tools: Bash, Read, Write, AskUserQuestion, WebSearch
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---
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# last30days: Become Expert → Write Prompts
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# last30days: Research Any Topic from the Last 30 Days
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Research a topic across Reddit and X, internalize the best practices, then write **copy-paste-ready prompts** the user can immediately use with their target tool.
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Research ANY topic across Reddit, X, and the web. Surface what people are actually discussing, recommending, and debating right now.
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Use cases:
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- **Recommendations**: "best Claude Code skills" → get a LIST of specific skills people mention
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- **News**: "what's happening with OpenAI" → get current events and updates
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- **How-to**: "Midjourney prompts" → learn techniques, then get copy-paste prompts
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- **General**: any topic → understand what the community is saying
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## CRITICAL: Parse User Intent
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@@ -18,19 +24,27 @@ Before doing anything, parse the user's input for:
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1. **TOPIC**: What they want to learn about (e.g., "web app mockups", "Claude Code skills", "image generation")
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2. **TARGET TOOL** (if specified): Where they'll use the prompts (e.g., "Nano Banana Pro", "ChatGPT", "Midjourney")
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3. **QUERY TYPE**: What kind of research they want:
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- **RECOMMENDATIONS** - "best X", "top X", "what X should I use", "recommended X" → User wants a LIST of specific things
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- **NEWS** - "what's happening with X", "X news", "latest on X" → User wants current events/updates
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- **HOW-TO** - "how to X", "X tutorial", "learn X" → User wants educational content
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- **GENERAL** - anything else → User wants broad understanding of the topic
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Common patterns:
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- `[topic] for [tool]` → "web mockups for Nano Banana Pro" → TOOL IS SPECIFIED
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- `[topic] prompts for [tool]` → "UI design prompts for Midjourney" → TOOL IS SPECIFIED
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- Just `[topic]` → "iOS design mockups" → TOOL NOT SPECIFIED, that's OK
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- "best [topic]" or "top [topic]" → QUERY_TYPE = RECOMMENDATIONS
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- "what are the best [topic]" → QUERY_TYPE = RECOMMENDATIONS
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**IMPORTANT: Do NOT ask about target tool before research.**
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- If tool is specified in the query, use it
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- If tool is NOT specified, run research first, then ask AFTER showing results
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**Store the TOPIC** - you'll extract or ask about TARGET_TOOL later:
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**Store these variables:**
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- `TOPIC = [extracted topic]`
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- `TARGET_TOOL = [extracted tool, or "unknown" if not specified]`
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- `QUERY_TYPE = [RECOMMENDATIONS | NEWS | HOW-TO | GENERAL]`
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---
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@@ -92,8 +106,31 @@ The script displays progress:
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```
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**Step 2: While script runs, do WebSearch**
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- Search for: `{TOPIC} 2026` (or current year) - find 8-15 pages
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- Search for: `{TOPIC} best practices tutorial guide` - find 5-10 more
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Choose search queries based on QUERY_TYPE:
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**If RECOMMENDATIONS** ("best X", "top X", "what X should I use"):
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- Search for: `best {TOPIC} recommendations`
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- Search for: `{TOPIC} list examples`
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- Search for: `most popular {TOPIC}`
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- Goal: Find SPECIFIC NAMES of things, not generic advice
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**If NEWS** ("what's happening with X", "X news"):
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- Search for: `{TOPIC} news 2026`
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- Search for: `{TOPIC} announcement update`
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- Goal: Find current events and recent developments
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**If HOW-TO** ("how to X", "tutorial"):
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- Search for: `{TOPIC} tutorial guide 2026`
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- Search for: `{TOPIC} best practices`
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- Goal: Find educational content
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**If GENERAL** (default):
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- Search for: `{TOPIC} 2026`
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- Search for: `{TOPIC} discussion`
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- Goal: Find what people are actually saying
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For ALL query types:
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- EXCLUDE reddit.com, x.com, twitter.com (covered by script)
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- INCLUDE: blogs, tutorials, docs, news, GitHub repos
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- **DO NOT output "Sources:" list** - this is noise, we'll show stats at the end
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@@ -140,6 +177,24 @@ Read the research output carefully. Pay attention to:
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**ANTI-PATTERN TO AVOID**: If user asks about "clawdbot skills" and research returns ClawdBot content (self-hosted AI agent), do NOT synthesize this as "Claude Code skills" just because both involve "skills". Read what the research actually says.
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### If QUERY_TYPE = RECOMMENDATIONS
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**CRITICAL: Extract SPECIFIC NAMES, not generic patterns.**
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When user asks "best X" or "top X", they want a LIST of specific things:
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- Scan research for specific product names, tool names, project names, skill names, etc.
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- Count how many times each is mentioned
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- Note which sources recommend each (Reddit thread, X post, blog)
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- List them by popularity/mention count
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**BAD synthesis for "best Claude Code skills":**
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> "Skills are powerful. Keep them under 500 lines. Use progressive disclosure."
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**GOOD synthesis for "best Claude Code skills":**
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> "Most mentioned skills: /commit (5 mentions), remotion skill (4x), git-worktree (3x), /pr (3x). The Remotion announcement got 16K likes on X."
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### For all QUERY_TYPEs
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Identify from the ACTUAL RESEARCH OUTPUT:
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- **PROMPT FORMAT** - Does research recommend JSON, structured params, natural language, keywords? THIS IS CRITICAL.
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- The top 3-5 patterns/techniques that appeared across multiple sources
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@@ -169,12 +224,32 @@ Analyzed {total_sources} sources from the last 30 days
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What I learned:
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[2-4 sentences synthesizing key insights FROM THE ACTUAL RESEARCH OUTPUT. Quote or paraphrase what the sources said. The synthesis should be traceable back to the research results above.]
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```
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**Then, based on QUERY_TYPE:**
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**If RECOMMENDATIONS** - Show specific things mentioned:
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```
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🏆 Most mentioned:
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1. [Specific name] - mentioned {n}x (r/sub, @handle, blog.com)
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2. [Specific name] - mentioned {n}x (sources)
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3. [Specific name] - mentioned {n}x (sources)
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4. [Specific name] - mentioned {n}x (sources)
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5. [Specific name] - mentioned {n}x (sources)
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Notable mentions: [other specific things with 1-2 mentions]
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```
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**If NEWS/HOW-TO/GENERAL** - Show patterns:
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```
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KEY PATTERNS I'll use:
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1. [Pattern from research]
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2. [Pattern from research]
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3. [Pattern from research]
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```
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**Then always end with:**
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```
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---
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Share your vision for what you want to create and I'll write a thoughtful prompt you can copy-paste directly into {TARGET_TOOL}.
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```
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