Deeper Seeker
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About this skill
What It Solves
When knowledge workers enter unfamiliar domains, the main problem is usually not a lack of sources, but too many noisy sources mixed together: search results, summaries, and opinion pieces can easily blend consensus, debate, noise, and half-mature knowledge. Ordinary search can answer “what exists” and “who said what,” but it is less useful for answering “what matters,” “where the real disagreement is,” and “what should be done next.”
deeper-seeker is not a source aggregator. Its goal is to convert information into reusable judgment. It is useful for rapidly entering a new domain, preparing for meetings or interviews, analyzing an industry, doing investment research, or building an actionable cognitive framework from large amounts of material.
How It Works
The skill is built around Synthesis, and it follows a research chain by default:
- Define the question: clarify the actual problem before summarizing sources.
- Build context: explain why the issue matters and what the mainstream understanding is.
- Organize facts: filter high-signal material and separate primary evidence from secondhand interpretation.
- Separate consensus from debate: identify what is settled and where schools, industries, or stakeholders still disagree.
- Extract underlying logic: look for key mechanisms, hidden assumptions, and overlooked variables.
- Form judgment: answer “so what?” directly instead of producing an unopinionated document dump.
- Recommend actions: suggest metrics to track, directions to study, and decision signals to watch.
It also provides three modes: Mode 1 for quickly building a sound baseline understanding, Mode 2 for internal industry views and a structured view matrix, and Mode 3 for discovering new relationships between sources, proposing new frameworks, or generating original insights. It prioritizes academic papers, industry reports, primary data, filings, and high-quality deep reporting, while treating self-published secondhand takes and emotionally charged opinions with caution.
Boundaries and Caveats
It is not a replacement for simple fact lookup, real-time news monitoring, raw database retrieval, or compliance advice. Output quality depends on the input material, the research goal, and the user’s existing context. Mode 3 allows “micro-original” insights, but they must remain grounded in evidence, logically closed, and explainable, rather than packaging speculation as conclusion.
Use Cases
- Before a meeting, quickly enter an unfamiliar industry and organize mainstream understanding, key debates, and follow-up questions.
- Before investment research, split filings, reports, and expert views into consensus, debates, and blind spots, then list metrics to track.
- For interview prep, build an elevator pitch, key mechanisms, common misconceptions, and non-consensus judgments on a new technology.
- When drafting strategy work, find hidden causal chains across sources and propose a reusable framework with next actions.
Best For
- Strategy analysts preparing industry meetings who need a judgment-backed discussion outline.
- Investment analysts who need to separate consensus, debates, and underpriced variables from primary sources.
- Product managers entering a new domain who need core concepts, misconceptions, and action signals.
- Researchers writing in-depth reports who need to extract underlying logic and reusable frameworks.
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