Matt Van Horn
2ff9b6f6c1
- _compute_text_similarity() now checks outcome names with bidirectional substring matching (0.85) and token overlap (0.7), not just event titles - Collect outcomes from ALL active markets per event, filter to >1% price - Reorder outcome_prices to surface topic-matching outcome before top-3 truncation - Add SKILL.md "Prediction Markets" synthesis section with structural/long-term market preference, domain examples, citation format, and narrative weaving - Add Polymarket to citation priority list between HN and Web - Update stats box template to show up to 5 market odds - Fix render.py "vol24h" label to "volume" - Add NCAA seed fixture event for outcome-only matching tests - 82 polymarket tests pass (14 new) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
5.1 KiB
One-Shot Research Mode
Research ANY topic across Reddit, X, YouTube, Polymarket, and the web. Surface what people are actually discussing, recommending, betting on, 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, Polymarket, 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 could have an X account)
If TOPIC looks like it could have its own X account - people, creators, brands, products, tools, companies (e.g., "Dor Brothers", "Nano Banana Pro", "Seedance"), do ONE quick WebSearch:
WebSearch("{TOPIC} X twitter handle site:x.com")
Extract their X handle from results (look for x.com/{handle} URLs or "@handle" mentions). Verify it's the real account, not a parody/fan page - check for verified status, official website links, consistent naming. If found, pass as --x-handle={handle} (no @). Skip if TOPIC is a generic concept (not an entity), already has @, uses --quick, or no official account exists.
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
- Prediction markets are high-signal when relevant - real money on outcomes cuts through opinion. Prefer structural/long-term markets (championship > regular season, regime change > near-term deadline). When the topic is an outcome in a multi-outcome market, call out that specific outcome's odds and movement. Weave odds into narrative: "Polymarket has X at Y% (up/down Z%)"
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
|- Polymarket: {N} markets | {summary of up to 5 most relevant market odds}
|- Web: {N} pages (supplementary)
|- Top voices: @{handle1}, @{handle2} | r/{sub1}, r/{sub2}
---
CRITICAL: Omit any source line that returned 0 results. Do NOT show "0 threads", "0 stories", "0 markets", or "(no results this cycle)". If a source found nothing, DELETE that line entirely.
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.).