smart-search

Intelligent search strategy skill. Activates whenever the user needs to search, research, find facts, compare options, get recommendations, or analyze current events. Prevents over-reliance on the model's stale training data by enforcing source-diversity, recency checks, and anti-SEO filtering. Trigger keywords: search, find, recommend, latest, current, analyze, compare, what's the best, research, is it true, look up.

Smart Search Strategy Skill

Core Philosophy

The goal of search is not just to find an answer — it's to find the most credible, closest-to-truth information available. For topics involving national interests, capital incentives, or political agendas, actively surface the underlying logic beneath the surface narrative.


Step 1 — Pre-Search Checklist (Run Before Every Search)

1.1 Recency Assessment

Information TypeShelf LifeStrategy
Political events, market prices, product launches< 1 monthMust search in real time — training data is stale
Policy direction, company strategy, tech trends< 6 monthsSearch and verify; check publication dates
Historical events, foundational principles, institutional structuresYearsTraining knowledge acceptable; selective verification

1.2 Topic Classification → Jump to Corresponding Source Matrix (Section 2)

  • Geopolitics / economics / international affairs → 2.1
  • Tech tools / software / open-source → 2.2
  • Investment / finance / markets → 2.3
  • Lifestyle / consumer / health / local → 2.4
  • Frontier tech / AI / academic → 2.5

Step 2 — Source Matrix by Domain

2.1 🌍 Geopolitics / Macroeconomics / International Trade

Primary Sources (highest credibility)

  • Government websites, central bank announcements, international org original texts (UN / WTO / IMF / BIS / OECD)
  • Corporate filings, regulatory disclosures (SEC, stock exchange announcements)

Expert Analysis Layer

  • Western think tanks: RAND / CSIS / Brookings / PIIE / CFR / Chatham House
  • Asia-Pacific perspective: ISEAS Singapore, Tokyo Foundation, East Asia Forum
  • Independent economists: Follow their X/Twitter accounts; always note their background and potential conflicts of interest

Real-Time Verification

  • Prediction markets: Polymarket / Kalshi / Metaculus (use as crowd confidence signal, not authority)
  • Reuters / FT / Bloomberg: News layer — reliable for facts, less so for interpretation

Counter-Narrative Check (Critical Step)

  • For any topic involving state or capital interests, always ask: Who is saying this? Who benefits? Who is being silenced?
  • For any major geopolitical event, find at least one non-Western source for comparison (e.g., Al Jazeera, Caixin, South China Morning Post, The Hindu)
  • Distinguish clearly: official position vs. academic research vs. market expectations vs. public sentiment

2.2 💻 Tech Tools / Software Recommendations / Open-Source Ecosystem

Core Principle: Avoid SEO Content Farms

Priority Sources

  • GitHub: Star count + recent commit activity + issue quality (active issues = real users)
  • Reddit: Domain-specific subreddits (r/MacApps / r/selfhosted / r/homelab / r/linux / r/programming) — read actual user threads, not pinned promotions
  • Hacker News: Search site:news.ycombinator.com [product name] for candid community reactions
  • alternativeto.net: Side-by-side comparison of similar tools

Developer Blogs (personal blogs > media review sites)

  • Search: [tool name] review site:dev.to or [tool name] honest experience

Reverse Validation (Always Do This)

  • Also search: [product] problems / [product] alternatives / [product] reddit
  • Any article titled "Best X in [Year]" with no concrete test data → downrank immediately

Open-Source Discovery Logic

  • Free/open-source tools are rarely SEO-optimized; they spread by word of mouth
  • Add open source / free / GitHub keywords to surface tools that don't buy ads

2.3 💰 Investment / Finance / Markets

Primary Data (the only reliable foundation)

  • US: SEC filings (EDGAR), Fed statements, BLS/BEA data
  • EU: ECB, Eurostat, ESMA disclosures
  • China: CSRC regulatory filings, PBOC, NBS official data
  • Global: Bloomberg / Reuters data citations, IMF World Economic Outlook

Analysis Layer (note conflicts of interest)

  • Sell-side research has client-retention incentives — maintain healthy skepticism
  • Independent analysts: useful signal, but always note their disclosed positions

Must Flag

  • Content containing "price target," "strong buy," or "guaranteed returns" — trace back to the original research document
  • Social media market sentiment ≠ fundamentals — treat separately
  • Capital narrative recognition: which type of capital benefits from this policy/event? Who is promoting this framing?

2.4 🏠 Lifestyle / Consumer / Health / Local

Prioritize Authentic User Feedback

  • Reddit (relevant subreddits for any topic)
  • Product-specific forums and communities
  • Review aggregators with verified purchase filters (not paid placement)
  • Local community boards and city-specific subreddits for local questions

Recency Check

  • Consumer products: verify model year/version (2023 recommendations may be superseded)
  • Policy-related topics (visa, tax, benefits): always check for the latest version

Localization Strategy

  • For region-specific questions, search in the local language first — don't just translate English answers
  • Add location + time qualifiers to avoid generic responses

2.5 🔬 Frontier Tech / AI / Academic

Primary Sources

  • arXiv preprints (note: not peer-reviewed — assess accordingly)
  • Official GitHub repos (README + Release Notes are often more accurate than media coverage)
  • Research lab blogs: DeepMind / OpenAI / Anthropic / Google Research / Meta AI

First-Hand Signal Layer (researchers > media)

  • Researcher X/Twitter accounts for immediate interpretation (before media rewrites)
  • Tech media (The Verge / Ars Technica / MIT Tech Review) as supplement, not authority

Version Awareness

  • Always confirm: paper/model/tool version number and publication date
  • In AI, content from 6 months ago may already be obsolete

Step 3 — Search Execution Standards

3.1 Query Construction

❌ Avoid: best / top / amazing / recommended / ultimate (SEO trap words)
✅ Use:   specific function + context + time qualifier

# Source-scoped queries
site:reddit.com [question]
site:github.com [tool name]

# Time-scoped queries
[topic] after:2024
[topic] 2025

# Reverse search (always run at least one)
[product/policy/event] problems
[product/policy/event] criticism
[product/policy/event] alternatives
[product/policy/event] debunked

3.2 Multi-Round Search Rhythm

  1. Round 1 — Wide: Broad query to map the topic landscape; identify key names, institutions, terminology
  2. Round 2 — Deep: Drill into specific entities surfaced in Round 1; find original/primary sources
  3. Round 3 — Adversarial (when contradictions exist): Specifically search for opposing views, criticism, alternative interpretations

3.3 Underlying Logic Excavation (Required for Interest-Conflict Topics)

For political, economic, and policy questions, actively surface:

① Who is making this claim? (Government / media / capital / academic / grassroots)
② Who benefits from this narrative? Whose interests are protected or harmed?
③ What information is being deliberately omitted or downplayed?
④ Are there historical parallels? What were the outcomes?
⑤ Surface cause vs. deep driver (economic structure / power logic / historical grievances)

Step 4 — Result Processing Standards

4.1 Confidence Labeling

  • High: Multiple independent sources agree; primary data supports the claim
  • Medium: Single reliable source, or multiple sources with divergence
  • Low: Inference / indirect information / single secondary source

4.2 Handling Contradictory Information

  • Do not force a single conclusion — explicitly surface the disagreement:

    "Source A states… Source B states… The key point of divergence is…"

  • Label the nature and likely bias of each source

4.3 Information Gap Declaration

  • Explicitly tell the user which questions the current search cannot confirm
  • Distinguish between "no public information available" and "information exists but contradicts itself"

Step 5 — Pre-Output Bias Check

[ ] Did I only cite sources from one language/cultural sphere?
    (Geopolitical topics require at least one non-dominant-perspective source)
[ ] Are there commercially-incentivized sources mixed in without flagging?
[ ] Is the time reference explicit? ("Latest" = how recent exactly?)
[ ] Am I overconfident in the conclusion? Is confidence level labeled?
[ ] Did I probe the underlying interest logic?
    (Required for political / economic / capital topics)
[ ] Did I miss niche but high-quality sources?
    (Open-source tools / independent researchers often don't rank well in SEO)

Quick Reference: Source Index

CategorySources
Geopolitical think tanksRAND / CSIS / CFR / Brookings / Chatham House / ISEAS
Prediction marketsPolymarket / Kalshi / Metaculus
Open-source communitiesGitHub / Hacker News / alternativeto.net
Tech communitiesr/MacApps / r/selfhosted / r/homelab / r/programming
International financeFT / Bloomberg / Reuters / WSJ / The Economist
AI frontierarXiv / HuggingFace / DeepMind blog / OpenAI blog
PreprintsarXiv / SSRN / bioRxiv
Local/consumerReddit (domain subreddits) / community forums