Matt Van Horn
4f584a4e96
When a topic is a person/brand (e.g. "Dor Brothers", "Jason Calacanis"), the agent now resolves their X handle via WebSearch before running the script, then passes --x-handle to search their posts unfiltered (no topic keywords required). This finds posts the entity made without mentioning their own name. - SKILL.md + OpenClaw variant: Step 0.5 handle resolution instructions - last30days.py: --x-handle CLI arg, passed through to _run_supplemental() - bird_x.search_handles(): topic is now Optional[str] for unfiltered mode - schema.py: resolved_x_handle field on Report - render.py: show resolved handle in stats output Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
4.2 KiB
One-Shot Research Mode
Research ANY topic across Reddit, X, YouTube, and the web. Surface what people are actually discussing, recommending, and debating right now.
Parse User Intent
Before doing anything, parse the user's input for:
- TOPIC: What they want to learn about
- TARGET TOOL (if specified): Where they'll use the prompts
- QUERY TYPE:
- PROMPTING — "X prompts", "prompting for X" → copy-paste prompts
- RECOMMENDATIONS — "best X", "top X" → list of specific things
- NEWS — "what's happening with X" → current events
- GENERAL — anything else → broad understanding
Do NOT ask about target tool before research. Run research first, ask after.
Display your parsing before calling tools:
I'll research {TOPIC} across Reddit, X, YouTube, and the web.
Parsed intent:
- TOPIC = {TOPIC}
- TARGET_TOOL = {TARGET_TOOL or "unknown"}
- QUERY_TYPE = {QUERY_TYPE}
Research typically takes 2-8 minutes. Starting now.
Step 0.5: Resolve X Handle (if topic is a person/brand)
If TOPIC looks like a person, creator, brand, or specific account (1-3 words, proper noun), do ONE quick WebSearch:
WebSearch("{TOPIC} X twitter handle")
Extract their X handle from results (look for x.com/{handle} URLs or "@handle" mentions). If found, pass it to the script as --x-handle={handle} (no @). Skip if TOPIC is generic, already has @, or uses --quick.
Research Execution
Step 1: Run the research script (FOREGROUND)
python3 "${SKILL_ROOT}/scripts/last30days.py" "$ARGUMENTS" --emit=compact --store 2>&1 # Add --x-handle=HANDLE if resolved
Use a timeout of 300000 (5 minutes). The --store flag persists findings for watchlist/briefing integration.
The script auto-detects: API keys, Bird CLI, yt-dlp, web search backends.
Read the ENTIRE output. It contains Reddit, X, YouTube, AND web sections.
Step 2: WebSearch (supplement)
After the script finishes, use your WebSearch tool for additional coverage.
Choose queries based on QUERY_TYPE:
- RECOMMENDATIONS:
best {TOPIC} recommendations,{TOPIC} list examples - NEWS:
{TOPIC} news 2026,{TOPIC} announcement update - PROMPTING:
{TOPIC} prompts examples 2026,{TOPIC} techniques tips - GENERAL:
{TOPIC} 2026,{TOPIC} discussion
Rules:
- USE THE USER'S EXACT TERMINOLOGY
- EXCLUDE reddit.com, x.com, twitter.com (covered by script)
- Do NOT output "Sources:" list
Synthesis
Judge Agent rules:
- Weight Reddit/X HIGHER (engagement signals)
- Weight YouTube HIGH (views + transcript content)
- Weight web LOWER (no engagement data)
- Identify cross-source patterns (strongest signals)
- Extract top 3-5 actionable insights
Ground synthesis in ACTUAL research, not pre-existing knowledge.
Citation Rules
- Cite sparingly: 1-2 sources per topic
- Priority: @handles > r/subreddits > YouTube channels > web sources
- Use publication names, never raw URLs
- Lead with people, not publications
Display Results
1. "What I learned" (format depends on QUERY_TYPE)
If RECOMMENDATIONS — show specific items with sources:
Most mentioned:
[Name] - {n}x mentions
Use Case: [what it does]
Sources: @handle1, r/sub, blog.com
If PROMPTING/NEWS/GENERAL — show synthesis:
What I learned:
**{Topic 1}** — [1-2 sentences, per @handle or r/sub]
KEY PATTERNS:
1. [Pattern] — per @handle
2. [Pattern] — per r/sub
2. Stats box (calculate from actual output):
---
All agents reported back!
|- Reddit: {N} threads | {N} upvotes | {N} comments
|- X: {N} posts | {N} likes | {N} reposts
|- YouTube: {N} videos | {N} views | {N} with transcripts
|- Web: {N} pages (supplementary)
|- Top voices: @{handle1}, @{handle2} | r/{sub1}, r/{sub2}
---
3. Invitation with 2-3 specific follow-up suggestions based on research.
Follow-Up
After research, you are an EXPERT on this topic.
- QUESTION → Answer from research (no new searches)
- GO DEEPER → Elaborate from findings
- CREATE/PROMPT → Write ONE prompt using research insights
- Different topic → Run new research
When writing prompts, match the FORMAT the research recommends (JSON, structured, etc.).