BD arthas-dashboard
Arthas 监控可视化面板。直观展示 JVM 线程、内存、GC、方法调用等核心指标，并自动检测异常、分级诊断、提供可操作的解决方案。当用户说 "dashboard"、"arthas"、"jvm 监控"、"线程分析"、"内存分析"、"方法耗时"、"CPU 高"、"死锁"、"GC 分析"、"火焰图"、"profiler"、"方法调用链"、"watch 方法"、"trace 方法" 或任何 Arthas 诊断相关需求时使用。
Arthas 监控可视化面板。直观展示 JVM 线程、内存、GC、方法调用等核心指标，并自动检测异常、分级诊断、提供可操作的解决方案。当用户说 "dashboard"、"arthas"、"jvm 监控"、"线程分析"、"内存分析"、"方法耗时"、"CPU 高"、"死锁"、"GC…
As a process D 49/100 · Unfinished process — 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.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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
description-no-whendescription does not say WHEN to use the skill (no "use when") - warning
body-longSKILL.md body ≈ 6605 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 49/100
- 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
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 4 mutating operations with no state check
- 70Execution cost. Instruction body is 6605 tokens
- 100Tools and files. No external tools needed
- 100Steps. 45 steps
- 100Consistency. Name and required fields are in place
- low 15 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -255 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +5Description quotes 6 example trigger phrases
- +3Description length 212: enough signal without eating the budget
- +4Structure: 42 headings
- +3Step-by-step instructions: 45 items
- +4Has examples (20 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.