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research

Before designing a feature, research how comparable libraries solve the problem, check best practices, known pitfalls, and upstream changes. Use when starting a new feature, investigating an unfamiliar area, or the user asks to research something.

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NVIDIA/multi-storage-client
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2026년 9월 9일 18:30
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research
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Before designing a feature, research how comparable libraries solve the problem, check best practices, known pitfalls, and upstream changes. Use when starting a new feature, investigating an unfamiliar area, or the user asks to research something.
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# Research Research the problem space before designing or implementing a feature to avoid reinventing the wheel and catch issues early. ## When to Use - Starting a new feature or significant enhancement. - Working with unfamiliar APIs, cloud SDKs, or library internals. - User explicitly asks to research or investigate an approach. ## Workflow ### 1. Clarify scope Confirm with the user: - What problem are we solving? - Which language layers are involved (Python, Rust)? - Any known constraints or preferences? ### 2. Research comparable solutions Search for: - How other multi-cloud storage libraries solve the same problem. - Best practices for the relevant cloud SDKs (AWS S3, GCS, Azure, OCI). - Known pitfalls or breaking changes in upstream dependencies. - PyO3/maturin patterns (if Rust bindings are involved). ### 3. Check upstream Look for: - Recent releases of relevant dependencies. - Open issues or PRs related to the feature area. - Deprecation notices. ### 4. Produce a summary Output using this format: ```markdown ## Research Summary: <topic> ### Approaches Found - <approach 1>: <trade-offs> - <approach 2>: <trade-offs> ### Recommendation - <recommended approach with rationale> ### Risks / Blockers - <anything that could derail implementation> ### References - <links to docs, issues, examples> ```
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