AC llm-usage-aggregator
LLM使用流水数据汇总工具。将LLM调用日志CSV文件按Provider、Model、用户维度进行汇总统计，输出多Sheet Excel报表，并基于pricing_config.json计算成本。适用场景：(1) 用户提供LLM流水CSV文件需要汇总分析；(2) 需要区分内部/外部用户使用情况；(3) 需要统计prompt_tokens、completion_tokens、generated_image_count、duration_seconds等指标；(4) 需要计算各维度成本费用。
LLM使用流水数据汇总工具。将LLM调用日志CSV文件按Provider、Model、用户维度进行汇总统计，输出多Sheet Excel报表，并基于pricingconfig.json计算成本。适用场景：(1) 用户提供LLM流水CSV文件需要汇总分析；(2) 需要区分内部/外部用户使用情况；(3)…
As a process C 53/100 · 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.
- 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: 4. 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")
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. 23 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 735 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 246: enough signal without eating the budget
- +4Structure: 13 headings
- +3Step-by-step instructions: 23 items
- +4Has examples (1 code blocks)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.