research

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>