Repository
fla-org/flash-linear-attention agent skills
- skills
- 9
- GitHub stars
- 5.8k
GitHub description: “🚀 Efficient implementations for emerging model architectures”
- Stars
- 5,831 (743 forks)
- Licence
- MIT
- Last push
- Oct 2026
- Created
- Dec 2023
- large-language-models
- machine-learning-systems
- natural-language-processing
- sequence-modeling
Install all skills
npx skills add fla-org/flash-linear-attentionAdd --skill <name> for a single skill and -a <agent> to choose the agent (see the agent guides).
Skills in fla-org/flash-linear-attention, ranked
Ranked by score. Sort bymost stars,trending,newest,recently updated
| # | Skill | Repository | Stars | Used in | Tokens | Auto-check | Licence | Updated |
|---|---|---|---|---|---|---|---|---|
| 1 | Guidelines for Ascend NPU kernel / Triton-Ascend backend performance work in the FLA repo. | fla-org/ | 5.8k | — | ~6.3k | Automated safety check: Pass | MIT | today |
| 2 | Disciplined, reproducible loop for making an FLA kernel faster (Triton, Gluon, TileLang, CuTe) without ever breaking or gaming correctness. | fla-org/ | 5.8k | — | ~3.1k | Automated safety check: Pass | MIT | today |
| 3 | Workflow for porting an existing Triton kernel in fla/ops/ to Gluon (triton.experimental.gluon) to gain explicit control over tensor layouts, shared memory, async data movement (cp.async / TMA), MMA… | fla-org/ | 5.8k | — | ~4.2k | Automated safety check: Pass | MIT | today |
| 4 | Guidelines for kernel correctness testing and coverage in fla/ops/ and related modules, including common Triton grid/addressing pitfalls. | fla-org/ | 5.8k | — | ~1.5k | Automated safety check: Pass | MIT | today |
| 5 | Contract-first design and coverage discipline for FLA kernel and numerical changes. | fla-org/ | 5.8k | — | ~3.6k | Automated safety check: Pass | MIT | today |
| 6 | Workflow for FLA backend dispatch decorators and backend implementations. | fla-org/ | 5.8k | — | ~1.1k | Automated safety check: Pass | MIT | today |
| 7 | 7.Fla Kda FLA KDA kernel workflow and public technical notes. An agent skill from fla-org/flash-linear-attention. | fla-org/ | 5.8k | — | ~1.4k | Automated safety check: Pass | MIT | today |
| 8 | Guidelines for NVIDIA GPU kernel / Triton / Gluon / TileLang / CUDA backend performance work in the FLA repo. | fla-org/ | 5.8k | — | ~1.2k | Automated safety check: Pass | MIT | today |
| 9 | Prepare or update an FLA pull request with one concrete purpose, a concise description, verified tests and benchmarks, and justified size exceptions. | fla-org/ | 5.8k | — | ~1.2k | Automated safety check: Pass | MIT | today |
Questions, answered from the data.
What is the best skill in fla-org/flash-linear-attention?
Fla Ascend Performance from fla-org/flash-linear-attention ranks first of the 9 skills in fla-org/flash-linear-attention listed here, with the highest score: its repository has 5.8k GitHub stars, its SKILL.md loads about 6.3k tokens and it passes the automated safety check with no findings. Next come Fla Optimization Loop and Fla Triton To Gluon.
Are the skills in fla-org/flash-linear-attention official?
None yet. All 9 skills in fla-org/flash-linear-attention listed here come from community repositories; a skill counts as official when the product's own GitHub organization publishes it.
How do I install all skills from fla-org/flash-linear-attention?
Run npx skills add fla-org/flash-linear-attention in your project: the open-source skills CLI installs the repository's skills into your coding agent's skills folder. To install a single skill, open its page here for the exact command.
How are these skills ranked?
By Skill Navigator score, which combines the GitHub stars of the skill's repository (shared across that repo's skills and discounted for large collections), how many other GitHub owners carry a copy of the skill, and automated SKILL.md quality checks, minus penalties for safety-check warnings and for each further skill from the same repository. Skills that fail the safety check are not listed.