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CC makepad-2.0-performance

CRITICAL: Use for Makepad 2.0 performance optimization and debugging. Triggers on: makepad performance, makepad debug, makepad profiling, makepad gc, new_batch, texture_caching, render optimization, draw batching, mod.gc, garbage collection, memory, debug logging, troubleshoot, ViewOptimize, PortalList, CachedView, render tree, invisible text, text disappears, UI freezes, scroll stuttering, 性能, 调试, 优化, 垃圾回收, 渲染, 批处理, 日志

ZhangHanDong/makepad-skills Agent Skills author: ZhangHanDong 2 files body ≈ 5 160 tokens Open the sourcegithub.com↗ analyzed 8 h ago

CRITICAL: Use for Makepad 2.0 performance optimization and debugging. Triggers on: makepad performance, makepad debug, makepad profiling, makepad gc…

As a process C 60/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

GeneratorSoftware developmenttype and topics are labelled automatically from the skill text
Runs in: 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) OpenClaw Goose OpenCode
JSON
Technical rating
C
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
65
Run on models
none yet
Process rating
C
60/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning body-long SKILL.md body ≈ 5160 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 60/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 30Running it twice. 4 mutating operations with no state check
  • 70Execution cost. Instruction body is 5160 tokens
  • 100Tools and files. No external tools needed
  • 100Steps. 67 steps
  • 100When it triggers. States when to use and when not to
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • low 12 top-level sections: this looks like several domains in one skill

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

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -41 reference files, but SKILL.md never points to them: the model will not open them
  • +1No license
  • +2Single-language instructions
  • +3Description length 423: enough signal without eating the budget
  • +4Structure: 52 headings
  • +3Step-by-step instructions: 67 items
  • +4Has examples (27 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.