| name | research |
| description | 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. |
| invocable | auto |
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, Go)?
- 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).
- FUSE implementation patterns (if Go layer is 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:
## 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>
