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fla-optimization-loop

Disciplined, reproducible loop for making an FLA kernel faster (Triton, Gluon, TileLang, CuTe) without ever breaking or gaming correctness. Synthesizes the task-contract / three-phase / iteration-protocol / silent-bug-catalog discipline of agent kernel-optimization frameworks (KDA, the MLSys FlashInfer contest workflow, AKO4ALL/AKO4X), and anchors all of it on FLA's frozen pytest (forward AND backward, under NaN poisoning) as the immutable correctness gate. Use when iterating on `fla/ops/**` performance over multiple rounds.

73

Quality

90%

Does it follow best practices?

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SecuritybySnyk

Passed

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SKILL.md
Quality
Evals
Security

Quality

Content

92%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

An excellently structured process skill: concrete commands, explicit validation checkpoints, clear phase sequencing, and well-organized references to bundle files and sibling skills. The only minor weakness is a few source-attribution asides that add tokens without aiding execution.

Suggestions

Trim the 'Borrowed from KDA/AKO4ALL/AKO4X' attribution parentheticals, or consolidate them into a single one-line provenance note, to tighten conciseness.

Consider inlining a one-line example of a completed OPT_LOG.md row in the iteration-protocol section so the loop is fully self-contained before deferring to the template.

DimensionReasoningScore

Conciseness

Dense and substantive with no padding of basic concepts, but attribution parentheticals ('Borrowed from KDA', 'Borrowed from AKO4ALL', 'Borrowed from AKO4X's TRAPS.md') are minor over-explanation that could be trimmed without losing actionable value.

4 / 5

Actionability

Provides copy-paste-ready commands ('python -m benchmarks.ops.verify --op <op> [--base main]', '--gate-k <subset>'), a concrete banned-vs-allowed table, and explicit decision rules covering the common iteration loop.

5 / 5

Workflow Clarity

A clearly sequenced three-phase process with an explicit per-iteration validation checkpoint (gate must stay green every iteration), feedback loops (stall handling, re-assessment), and a no-go bar checklist for termination.

5 / 5

Progressive Disclosure

Well-structured overview that points to one-level-deep, clearly signaled references — 'references/opt-log-template.md', 'references/TRAPS.md', and the sibling fla-* skills — with bundle files present and correctly referenced.

5 / 5

Total

19

/

20

Passed

Description

87%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong, specific description that clearly states what the skill does and when to use it, in third person, with concrete domain anchors. It is slightly meta in framing and could surface a few more natural synonyms, but it is highly distinguishable and complete.

DimensionReasoningScore

Specificity

Names the domain and several concrete actions — 'making an FLA kernel faster (Triton, Gluon, TileLang, CuTe)', 'anchors all of it on FLA's frozen pytest', 'iterating on fla/ops/** performance' — but the 'Synthesizes the ... discipline' framing is somewhat meta, leaving minor coverage gaps versus a fully enumerated action list.

4 / 5

Completeness

Explicitly answers both what ('Disciplined, reproducible loop for making an FLA kernel faster ... without ever breaking or gaming correctness') and when ('Use when iterating on fla/ops/** performance over multiple rounds.') with concrete trigger phrases.

5 / 5

Trigger Term Quality

Includes natural phrases a user would say ('making an FLA kernel faster', 'iterating on fla/ops/** performance over multiple rounds') with good keyword coverage, though synonyms like 'optimize', 'speed up', or 'benchmark' are not surfaced.

4 / 5

Distinctiveness Conflict Risk

Occupies a clear niche (FLA kernels in specific backends, gated on FLA's pytest) with distinct triggers and minimal overlap risk against other skills.

5 / 5

Total

18

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
fla-org/flash-linear-attention
Reviewed

Table of Contents

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