[Spike] Benchmark dataset growth and fixture-loading strategies

[knytcomics-ui]

Category

Spike

Question

How should fixture loading and lookup behave as the corpus grows from 12 entries to hundreds or thousands?

Context

The open roadmap proposes substantial dataset growth, and the adapter already has specialized incremental parsing benchmarks, but no shared testkit scale targets exist.

Why This Matters

Growth can affect extension startup, browser bundle size, memory, release size, and research throughput.

Areas to Investigate

Raw JSON, generated modules, indexed lookups, compressed archives, lazy loading, split packs, browser and Node consumers.

Evaluation Criteria

Startup latency, lookup latency, memory, bundle size, release complexity, portability, and developer experience.

Expected Deliverables

Reproducible harness, measurements at multiple corpus sizes, comparison matrix, recommendation, and thresholds.

Acceptance Criteria

• Current loading is measured as a baseline.
• At least three corpus sizes are evaluated.
• Two loading strategies are compared.
• Startup, lookup, memory, and artifact size are reported.
• The recommendation states when the current approach becomes insufficient.

Follow-Up Opportunities

May lead to split packs, indexes, or adapter loading changes.

Cross-Repository Impact

Testkit, adapter, and extension.

Complexity

Spike

Impact

High — informs scalable dataset growth.

Suggested Labels

spike, area: tooling, area: cross-repo

[Ogstevyn]

Hey! This looks like a great fit for my experience. I'm a full-stack blockchain developer and I'd be happy to take this on, contribute a clean implementation, and make sure the existing functionality remains intact.

[grantfox-oss]

🦊 GrantFox — @Ogstevyn has been assigned to this issue as part of the Third Campaign campaign!

Next steps:

1. Open a Pull Request referencing this issue (e.g., Closes #76)
2. Your PR will be reviewed by the Gryd-lock maintainers

Good luck! Track your progress on GrantFox.