SKILLEMALL.ai

BC pans-roi-analyzer

AI算力销售 ROI 分析器。对比当前方案与新方案的成本和性能,计算 ROI、 TCO(总拥有成本)和投资回收期。输入 GPU 配置和业务指标, 生成投资回报分析报告,支持成本优化建议和竞品对比。 触发词:ROI分析, 成本对比, TCO计算, 投资回报, 成本优化, ROI calculator, TCO comparison, 性价比分析

ClawHub Agent Skills author: dashiming v1.0.0 MIT-0 3 files body ≈ 63 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
80/100
safety, quality, tests
Safety 60%
100
Quality 40%
50
Run on models
none yet
Process rating
C
53/100
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. 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 · 0

✓ No critical or high findings

Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 53/100

  • 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
  • 100Tools and files. No external tools needed
  • 100Steps. 5 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 63 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
  • +4No input/output examples
  • -15SKILL.md body under 300 characters: nearly empty
  • -31 of 1 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 172: enough signal without eating the budget
  • +4Structure: 5 headings
  • +3Step-by-step instructions: 5 items

Quality base 70; lint remarks subtract, signals add up to 100. Result: 50.

External checks

ClawHub: clean
This skill is a local AI compute ROI/TCO calculator; its main caveat is that its trigger words are broad and could activate in ordinary finance discussions.
LLM: benign (high) · VirusTotal: · 29 May 2026