Research

social-graph-ranker is the weighted graph-ranking layer for warm intro discovery, bridge scoring, and network gap analysis across X and LinkedIn. Use the social-graph-ranker skill when you need a reusable ranking engine for Lead Research, not a full outbound or network-maintenance workflow.

search-first is a research-before-coding workflow for finding existing tools, libraries, and patterns before you write custom code. Use the search-first skill to evaluate options, compare tradeoffs, and choose adopt, extend, or build custom with less guesswork.

research-ops is an evidence-first workflow for current-state research in ECC. Use it to find fresh facts, compare options, enrich people or companies, and produce recommendations grounded in public evidence plus any local context. It works as a routing layer for web research, citations, and repeatable decision support.

The market-research skill helps you produce source-backed, decision-grade research on markets, competitors, funds, and technology trends. Use it for market sizing, Competitive Analysis, investor due diligence, and thesis testing. It emphasizes recent evidence, clear takeaways, and separate fact, inference, and recommendation.

exa-search is an Exa MCP skill for current web-backed research, code examples, company intel, people lookup, and fast source discovery. Use it when freshness and evidence matter, and when you need a practical exa-search guide for live search, tool-based answers, and web research workflows.

The deep-research skill turns broad questions into sourced web research with firecrawl and exa MCP tools. Use it to compare sources, synthesize findings, and produce cited reports for competitive analysis, technology evaluation, due diligence, and other decisions that need evidence.

Open Notebook is a self-hosted, open-source research workspace for document analysis, notes, chat with sources, search, and podcast-style summaries. Use the open-notebook skill to organize notebooks, ingest PDFs, web pages, audio, video, and Office files, and support private, API-first workflows for Data Analysis.

hypogenic is a skill for generating and testing hypotheses on tabular or text-derived datasets with LLM support. It helps with hypogenic for Data Analysis by turning empirical questions into structured, testable workflows for classification interpretation, content analysis, and deception detection. Use it when you need evidence-backed hypotheses, not just brainstorming.

dhdna-profiler extracts cognitive patterns and thinking fingerprints from text or speech. Use it to profile how someone reasons, decides, values, and communicates, compare thinking styles, or answer “what’s my thinking style?” It is especially useful for structured analysis, repeated comparisons, and deeper insight into the mind behind a passage.

notion-research-documentation helps search Notion, fetch relevant pages, and turn them into cited briefs, comparisons, summaries, or reports. Use this notion-research-documentation skill for knowledge base writing, internal documentation, competitor tracking, and decision memos when your sources live in Notion.

market-sizing helps estimate TAM, SAM, and SOM with top-down and bottom-up methods. Use it for Market Research workflows, market entry decisions, investor decks, and launch planning when you need a defensible logic trail, assumptions to validate, and a practical first-pass market estimate.

swot-analysis skill for structured SWOT assessments with actionable recommendations. Use it for strategic assessment, competitive analysis, and product or business positioning when you need a clear internal-vs-external view.

summarize-interview turns a customer interview transcript into a structured discovery summary with JTBD, current solution, satisfaction signals, key insights, and action items. Use it for interview recordings, transcript cleanup, and concise summaries for product teams, researchers, founders, or Data Analysis workflows.

prioritize-features skill for Product Management helps rank a feature backlog into a defensible top 5 using impact, effort, risk, and strategic fit. Use it when you need to compare feature ideas, make scope decisions, and explain why one item should come first.

interview-script helps you create structured customer interview guides with warm-up, core exploration, and wrap-up sections. It follows The Mom Test and JTBD-style probing to keep questions neutral, avoid pitching, and focus on past behavior for discovery, product, and UX research interviews.

identify-assumptions-existing helps you stress-test a feature idea in an existing product by surfacing risky assumptions across Value, Usability, Viability, and Feasibility. It uses PM, designer, and engineer perspectives plus a devil’s advocate lens for Strategic Planning and pre-build risk review.

user-segmentation helps turn feedback, interviews, tickets, surveys, and usage logs into distinct behavior-based user segments. Built for Data Analysis, it identifies at least 3 actionable groups using jobs-to-be-done, motivations, and unmet needs rather than demographics alone.

The sentiment-analysis skill turns user feedback into segment-level insights, sentiment scores, JTBD, and product impact. Use it for sentiment-analysis for Data Analysis on reviews, surveys, support notes, or social listening when you need a practical sentiment-analysis guide, not a generic polarity check.

The customer-journey-map skill helps you create an end-to-end customer journey map with stages, touchpoints, emotions, pain points, and opportunities. It fits UX Research, onboarding improvement, and experience analysis when you need a structured journey story from messy inputs.

competitor-analysis helps you map a market, identify 5 direct competitors, and compare positioning, pricing, features, strengths, weaknesses, and differentiation opportunities. Use it for competitive research, a competitive brief, launch prep, or competitor-analysis for Competitive Analysis when you need decision-ready insights.

competitive-battlecard helps you create a sales-ready battlecard for one named competitor, covering positioning, feature comparison, objection handling, and win/loss framing. Use it for competitive analysis, sales enablement, and internal prep when you need a practical answer to “why us instead of competitor X?”

huggingface-papers helps you read Hugging Face paper pages in markdown and extract structured metadata from the papers API, including authors, linked models, datasets, Spaces, GitHub repos, and project pages. Use it for Hugging Face paper URLs, arXiv URLs or IDs, and Academic Research workflows that need paper-page evidence.

huggingface-paper-publisher helps publish and manage research papers on the Hugging Face Hub. Use it to index arXiv papers, link papers to models or datasets, verify authorship, and create markdown research articles with templates for technical writing.

hv-analysis is a horizontal-vertical research skill for turning a product, company, concept, technology, or person into a structured analysis report. Use the hv-analysis skill for deep research, competitive comparison, and report-ready output, especially when you need hv-analysis for Data Analysis or a polished PDF workflow.