BC canvas-render-optimize
Canvas 2D大规模渲染优化方案。当Canvas需要渲染大量元素（5000+）导致掉帧、卡顿时使用。包含三层渲染管线（OffscreenCanvas静态层+脏矩形动态层+UI叠加层）、空间哈希视口裁剪、LOD细节层次、requestAnimationFrame帧调度。适用于晶圆图(WaferMap)、热力图、散点图、地图标注、甘特图等场景。实测100k元素从1fps优化到55fps。
As a process C 58/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 · 1
✓ No critical or high findings
Medium and low: 1
-
low Secrets in code
secret-high-entropy-tokenSKILL.md:27High-entropy token-like string (may be an id, hash or a credential)private ctx: Offs…t2D;
Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Implicit map keys need to be followed by map values at line 4, column 1: **使用时机**： ^^^^^^^^^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 58/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 50Failures and branches. 0 branches, has a failure section
- 100Tools and files. No external tools needed
- 100Steps. 5 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1274 tokens
- 100Running it twice. No mutating operations
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
- +1No license
- +2Single-language instructions
- +3Description length 195: enough signal without eating the budget
- +4Structure: 13 headings
- +3Step-by-step instructions: 5 items
- +4Has examples (8 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 62.
External checks
ClawHub: clean
This is a content-only Canvas performance guide with no hidden execution, credential access, persistence, or sensitive permissions.
LLM: benign (high) · VirusTotal: · 29 May 2026