FLA MR Readiness Skill
SkillProductivityGuides your agent through preparing a pull request for the FLA repo, checking contribution rules, tests, and benchmarks.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the FLA MR Readiness Skill skill
About this capability
Checklist and workflow for preparing an MR/PR in the FLA repo. Covers CONTRIBUTING.md compliance, test plan, benchmark evidence, and PR body structure.
What this skill tells your AI
The instructions your AI receives, as published by fla-org/flash-linear-attention in .agents/skills/fla-mr-readiness/SKILL.md and read by ahel’s review.
Use this skill before opening a pull request to make sure the change is well-scoped, well-tested, and well-documented.
Pre-flight checklist
-
Read
CONTRIBUTING.md- Confirm code style, docstring format, commit message conventions.
- Make sure your branch is up to date with
main(or the target branch).
-
Confirm change scope
- List the files you modified.
- If the change spans multiple layers (kernel + model + benchmark script), note the dependency chain in the PR description.
-
Check for duplicate work
- Search open issues and PRs:
gh pr list --repo fla-org/flash-linear-attention --state open --search "<keywords>" - If a related PR exists, comment on it rather than opening a competing one.
- Search open issues and PRs:
-
Run dependent tests
- Find tests affected by your change:
python scripts/find_dependent_tests.py <changed_file_or_dir> - Run those tests locally and ensure they pass.
- If a test is flaky, retry once; if it still fails, explain why in the PR.
- Find tests affected by your change:
-
Performance evidence (if touching kernel code)
- See
fla-nvidia-performanceskill for the full evidence requirements. - At minimum: before/after benchmark on the same hardware, dense + varlen workloads if applicable, and a summary of any NCU profiling you did.
- See
-
Write PR summary
- Use the CI-enforced structure below. The source of truth is
.github/pull_request_template.md; thecheck-pr-titleworkflow rejects bodies that drop the checklist, so never trim it to save space.
- Use the CI-enforced structure below. The source of truth is
-
Code style review
- Follow
CONTRIBUTING.mdfor Python style, docstrings, comments, and commit prefixes. - In tests and public code, use device/platform wrappers from
fla.utils(device,device_platform,IS_NVIDIA,IS_NVIDIA_HOPPER,IS_NVIDIA_BLACKWELL,IS_AMD,IS_INTEL) instead of new directtorch.cudaplatform checks. Add a smallfla.utilshelper first when the existing wrappers are not enough. - Keep NVIDIA-only profiling commands in performance docs or scripts, not in generic correctness tests.
- Follow
PR body structure
Follow .github/pull_request_template.md exactly, checklist included:
## Summary
One-paragraph description of what changed and why.
## Test plan
- Unit tests added/modified: `<list>`
- Dependent tests run: `<list>`
- Varlen / CP / model tests: `<yes/no + details>`
## Benchmark / NCU (kernel changes only)
- Hardware: `<e.g., H100>`
- Workload: `<batch, seq_len, dtype>`
- Before: `<throughput or latency>`
- After: `<throughput or latency>`
- Conclusion: `<improvement / neutral / trade-off>`
(state "neutral" when the change is not performance-related)
## Breaking changes
- None / list any API or behavior changes.
## Checklist
- [x] I have read [CONTRIBUTING.md](../CONTRIBUTING.md) and follow its conventions (code style, docstrings, commit prefixes).
- [x] I have read [AGENTS.md](../AGENTS.md) and, where my change matches its scope, the relevant skill under [.agents/skills](../.agents/skills).
- [x] Dependent tests pass locally or in CI, and new behavior is covered by tests where applicable (tick as N/A for changes with no testable code, e.g. docs-only).
- [x] Kernel changes include same-hardware before/after benchmark numbers, dense + varlen where applicable (tick as N/A when no kernel code changed).
- [ ] This PR is minor/cosmetic-only (typo, formatting, style-only tweaks) — tick only if it is, and justify below.
### If you ticked the "minor" box above
<justification — required when the "minor" box is ticked; otherwise delete this section>
What check-pr-title (.github/workflows/check-pr-title.yml) enforces:
- The first four checklist boxes must always be ticked; each item carries its own N/A reading, so a tick means "considered — done or not applicable" (e.g. benchmark numbers on a docs-only PR).
- The "minor" box is the inverse: leave it unticked for normal PRs. Tick it only when the PR genuinely is a typo/formatting/style-only tweak — then a justification of at least a sentence (≥ 20 non-whitespace characters, HTML comments stripped) under
### If you tickedis required. - Editing the body re-triggers the check. To edit a PR title/body on this repo, use the REST API, not
gh pr edit(see AGENTS.md "Opening PRs").
Important reminders
-
Do not put raw performance numbers without context. Always include:
- workload shape (batch, seq_len, heads, dims, dtype)
- hardware model
- benchmark command used
- before vs after
- your conclusion
-
Do not commit
.ncu-repfiles or raw profile dumps. Summarize results in the PR body and keep artifacts local. -
No busywork PRs: bundle trivial cleanups into a substantive change; do not open a PR for a single typo unless it is part of a larger fix.
Signals
- GitHub stars
- 6k
- Forks
- 702
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
fla-mr-readiness- Source
- github.com/fla-org/flash-linear-attention