From 5f8623f129d8b9fa6334978732523f890059415a Mon Sep 17 00:00:00 2001 From: Matt Van Horn Date: Sat, 24 Jan 2026 13:23:31 -0800 Subject: [PATCH] feat: Smart query detection for better research results MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit 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 --- SKILL.md | 85 ++++++++++++++++++++++++++++++++++++++++++++++++++++---- 1 file changed, 80 insertions(+), 5 deletions(-) diff --git a/SKILL.md b/SKILL.md index e1c6ded..759535c 100644 --- a/SKILL.md +++ b/SKILL.md @@ -8,9 +8,15 @@ disable-model-invocation: true allowed-tools: Bash, Read, Write, AskUserQuestion, WebSearch --- -# last30days: Become Expert → Write Prompts +# last30days: Research Any Topic from the Last 30 Days -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. +Research ANY topic across Reddit, X, and the web. Surface what people are actually discussing, recommending, and debating right now. + +Use cases: +- **Recommendations**: "best Claude Code skills" → get a LIST of specific skills people mention +- **News**: "what's happening with OpenAI" → get current events and updates +- **How-to**: "Midjourney prompts" → learn techniques, then get copy-paste prompts +- **General**: any topic → understand what the community is saying ## CRITICAL: Parse User Intent @@ -18,19 +24,27 @@ 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: + - **RECOMMENDATIONS** - "best X", "top X", "what X should I use", "recommended X" → User wants a LIST of specific things + - **NEWS** - "what's happening with X", "X news", "latest on X" → User wants current events/updates + - **HOW-TO** - "how to X", "X tutorial", "learn X" → User wants educational content + - **GENERAL** - anything else → User wants broad understanding of the topic Common patterns: - `[topic] for [tool]` → "web mockups for Nano Banana Pro" → TOOL IS SPECIFIED - `[topic] prompts for [tool]` → "UI design prompts for Midjourney" → TOOL IS SPECIFIED - Just `[topic]` → "iOS design mockups" → TOOL NOT SPECIFIED, that's OK +- "best [topic]" or "top [topic]" → QUERY_TYPE = RECOMMENDATIONS +- "what are the best [topic]" → QUERY_TYPE = RECOMMENDATIONS **IMPORTANT: Do NOT ask about target tool before research.** - If tool is specified in the query, use it - If tool is NOT specified, run research first, then ask AFTER showing results -**Store the TOPIC** - you'll extract or ask about TARGET_TOOL later: +**Store these variables:** - `TOPIC = [extracted topic]` - `TARGET_TOOL = [extracted tool, or "unknown" if not specified]` +- `QUERY_TYPE = [RECOMMENDATIONS | NEWS | HOW-TO | GENERAL]` --- @@ -92,8 +106,31 @@ The script displays progress: ``` **Step 2: While script runs, do WebSearch** -- Search for: `{TOPIC} 2026` (or current year) - find 8-15 pages -- Search for: `{TOPIC} best practices tutorial guide` - find 5-10 more + +Choose search queries based on QUERY_TYPE: + +**If RECOMMENDATIONS** ("best X", "top X", "what X should I use"): +- Search for: `best {TOPIC} recommendations` +- Search for: `{TOPIC} list examples` +- Search for: `most popular {TOPIC}` +- Goal: Find SPECIFIC NAMES of things, not generic advice + +**If NEWS** ("what's happening with X", "X news"): +- Search for: `{TOPIC} news 2026` +- Search for: `{TOPIC} announcement update` +- Goal: Find current events and recent developments + +**If HOW-TO** ("how to X", "tutorial"): +- Search for: `{TOPIC} tutorial guide 2026` +- Search for: `{TOPIC} best practices` +- Goal: Find educational content + +**If GENERAL** (default): +- Search for: `{TOPIC} 2026` +- Search for: `{TOPIC} discussion` +- Goal: Find what people are actually saying + +For ALL query types: - EXCLUDE reddit.com, x.com, twitter.com (covered by script) - INCLUDE: blogs, tutorials, docs, news, GitHub repos - **DO NOT output "Sources:" list** - this is noise, we'll show stats at the end @@ -140,6 +177,24 @@ Read the research output carefully. Pay attention to: **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. +### If QUERY_TYPE = RECOMMENDATIONS + +**CRITICAL: Extract SPECIFIC NAMES, not generic patterns.** + +When user asks "best X" or "top X", they want a LIST of specific things: +- Scan research for specific product names, tool names, project names, skill names, etc. +- Count how many times each is mentioned +- Note which sources recommend each (Reddit thread, X post, blog) +- List them by popularity/mention count + +**BAD synthesis for "best Claude Code skills":** +> "Skills are powerful. Keep them under 500 lines. Use progressive disclosure." + +**GOOD synthesis for "best Claude Code skills":** +> "Most mentioned skills: /commit (5 mentions), remotion skill (4x), git-worktree (3x), /pr (3x). The Remotion announcement got 16K likes on X." + +### For all QUERY_TYPEs + Identify from the ACTUAL RESEARCH OUTPUT: - **PROMPT FORMAT** - Does research recommend JSON, structured params, natural language, keywords? THIS IS CRITICAL. - The top 3-5 patterns/techniques that appeared across multiple sources @@ -169,12 +224,32 @@ Analyzed {total_sources} sources from the last 30 days What I learned: [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.] +``` +**Then, based on QUERY_TYPE:** + +**If RECOMMENDATIONS** - Show specific things mentioned: +``` +🏆 Most mentioned: +1. [Specific name] - mentioned {n}x (r/sub, @handle, blog.com) +2. [Specific name] - mentioned {n}x (sources) +3. [Specific name] - mentioned {n}x (sources) +4. [Specific name] - mentioned {n}x (sources) +5. [Specific name] - mentioned {n}x (sources) + +Notable mentions: [other specific things with 1-2 mentions] +``` + +**If NEWS/HOW-TO/GENERAL** - Show patterns: +``` KEY PATTERNS I'll use: 1. [Pattern from research] 2. [Pattern from research] 3. [Pattern from research] +``` +**Then always end with:** +``` --- Share your vision for what you want to create and I'll write a thoughtful prompt you can copy-paste directly into {TARGET_TOOL}. ```