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AF tilegym-improve-cutile-kernel-perf

Iteratively optimize cuTile kernel performance through systematic profiling, bottleneck analysis, IR comparison, and targeted tuning. Covers tile sizes, occupancy, autotune configs, TMA, latency hints, persistent scheduling, num_ctas, flush_to_zero, and IR-level debugging. Use when asked to "optimize cutile kernel", "improve kernel perf", "tune cutile performance", "make kernel faster", or iteratively benchmark and refine a cuTile GPU kernel in the TileGym project.

ClawHub Agent Skills author: NVIDIA 1 file body ≈ 1 734 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

Iteratively optimize cuTile kernel performance through systematic profiling, bottleneck analysis, IR comparison, and targeted tuning.

As a process F 42/100 · Will not run — References files that are not bundled: references/optimization-playbook.md, references/perf-knobs-catalog.md, references/cutile-api-reference.md

AnalyzerSoftware developmenttype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
78
Run on models
none yet
Process rating
F
42/100
Will not run
References files that are not bundled: references/optimization-playbook.md, references/perf-knobs-catalog.md, references/cutile-api-reference.md
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 0

✓ No critical or high findings

Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: references/optimization-playbook.md
  • warning missing-ref reference to a missing file: references/perf-knobs-catalog.md
  • warning missing-ref reference to a missing file: references/cutile-api-reference.md
  • warning missing-ref reference to a missing file: references/performance-model.md
  • warning missing-ref reference to a missing file: references/ir-dump-guide.md
  • warning missing-ref reference to a missing file: references/cutile-patterns-reference.md

Process rating: all ten parameters 42/100

Will not run. References files that are not bundled: references/optimization-playbook.md, references/perf-knobs-catalog.md, references/cutile-api-reference.md
  • 0Tools and files. 6 referenced file(s) missing: references/optimization-playbook.md, references/perf-knobs-catalog.md, references/cutile-api-reference.md
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 7 mutating operations with no state check
  • 85Steps. 44 steps, 1 vague phrases
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1734 tokens
  • 100Progress reporting. Reports progress
  • low The response is described with custom markup (4 tags): a typed call is more reliable

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +5Description quotes 4 example trigger phrases
  • +3Description length 469: enough signal without eating the budget
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 44 items
  • +4Has examples (4 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.