Every scene is a path you can run: which skills to use, how to install, how to prompt, and what traps to avoid.
Deep Research compresses hours-to-days analysis into tens of minutes: you give the question, the agent searches in steps, cross-checks, and returns a sourced structured report. Community method stresses: break the question fine first, cross-verify from multiple sources, every claim traceable — fast
The value of research is the source, not the length of the conclusion. The discipline: every key number carries a source link; conclusions AI can't source are guesses — keep them out of formal material.
k-dense-ai/claude-scientific-skills/skills/market-research-reports
Build evidence-traceable market research reports and assumption-driven market sizing or forecast scenarios. Use for market definition, industry and customer evidence, competitive landscapes, TAM/SAM/SOM reconciliation, forecast sensitivity, and auditable report scaffolds.
alirezarezvani/claude-skills/research-ops/skills/market-research
Use when doing upstream market-research methodology — sizing a market as TAM/SAM/SOM computed BOTH top-down and bottoms-up (never a single unsourced number), planning a survey sample size with finite-population correction and per-segment minimums, or scoring candidate market segments against Kotler's measurable/substantial/accessible/differentiable/actionable criteria. Outputs always show the method and the assumptions. For market-research analysts and product-marketing at the sizing/survey/segmentation moment. Distinct from marketing-skill (campaign analytics, attribution, demand-gen) — this is the evidence-building methodology, not live-campaign optimization.
Weizhena/Deep-Research-skills/skills/research-codex-en/research-deep
Read research outline, launch independent agent for each item for deep research. Disable task output.