AC ta-philosophy
当用户质疑"技术分析到底有没有用"、分不清技术分析 vs 基础分析、或想确定"什么时候该用图表法、 什么时候图表法会失效"时激活。也用于给新手建立技术分析的世界观与前提假设。 不适用于：具体买卖信号（转 trend-tools / 形态类 skill）、纯基本面研究。 关键 trigger 词：技术分析有效性、技术分析和基本面区别、图表预测原理、随机行走、历史会重演。 Activate when the user questions "does technical analysis even work", cannot distinguish TA from fundamental analysis, or wants to determine "when to use charting and when charting fails". Also for building a beginner's worldview and assumptions of TA. Not applicable: specific buy/sell signals (-> trend-tools / pattern skills), pure fundamental research. Key trigger words: TA validity, TA vs fundamental difference, chart prediction principle, random walk, history repeats.
当用户质疑"技术分析到底有没有用"、分不清技术分析 vs 基础分析、或想确定"什么时候该用图表法、 什么时候图表法会失效"时激活。也用于给新手建立技术分析的世界观与前提假设。 不适用于：具体买卖信号（转 trend-tools / 形态类 skill）、纯基本面研究。 关键 trigger…
As a process C 59/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches
How to improve
- 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
- note
frontmatter-keyunknown frontmatter key "source_book" - note
frontmatter-keyunknown frontmatter key "source_chapter" - note
frontmatter-keyunknown frontmatter key "related_skills"
Process rating: all ten parameters 59/100
- 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
- 70When it triggers. States when to use, but not when not to
- 100Tools and files. No external tools needed
- 100Steps. 42 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 594 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
- +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
- +1No license
- +2Single-language instructions
- +5Description quotes 3 example trigger phrases
- +3Description length 663: enough signal without eating the budget
- +4Structure: 18 headings
- +3Step-by-step instructions: 42 items
Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.