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@@ -30,6 +30,9 @@ Transform vague topics raised by users into high-quality, deliverable research r
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- **Internet-first investigation** — do not rely on training data for factual claims; search the web extensively for every sub-question, rephrase queries when results are thin, and keep searching until you have converging evidence from multiple independent sources
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- **Multi-perspective analysis** — examine every problem from at least 3 different viewpoints (e.g., end-user, implementer, business decision-maker, contrarian, domain expert, field practitioner); each perspective should generate its own search queries
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- **Question multiplication** — for each sub-question, generate multiple reformulated search queries (synonyms, related terms, negations, "what can go wrong" variants, practitioner-focused variants) to maximize coverage and uncover blind spots
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- **Component option breadth** — for every component area, build a broad option landscape before selecting. Search direct candidates, adjacent-domain alternatives, commercial/open-source variants, classical/simple baselines, current SOTA, and "do not use" failure cases. A component may not be narrowed to one candidate until alternatives have been searched and rejected with evidence.
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- **Component research depth** — for every serious component candidate, go beyond discovery pages. Read official docs, repository/license files, issue discussions, benchmarks, deployment guides, version/platform requirements, security notes, maintenance signals, and real-world failure reports. Extract evidence for inputs/outputs, lifecycle assumptions, runtime/storage/latency fit, integration boundaries, licensing, operational risks, and unsupported scenarios before assigning any selection status.
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- **Exact-fit component selection** — never select a component, tool, library, service, architecture pattern, or algorithm merely because it solves a similar class of problem. It must be proven compatible with the project's explicit operating context, constraints, required inputs/outputs, non-functional requirements, lifecycle assumptions, and acceptance criteria. If fit is unproven or mismatched, mark it `Rejected`, `Experimental only`, or escalate for user decision before it can shape the solution.
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## Context Resolution
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