AF a-stock-trading-assistant
A股股票智能交易助手，专服务中国大陆股票市场。当用户询问A股股票行情、个股分析、大盘情绪、热点板块、交易策略、价格预警、涨跌幅、成交量、技术面或基本面分析时触发。只处理沪深A股（代码以6/00/30/68开头），自动忽略港股和美股。所有数据实时从东方财富、新浪财经、同花顺、雪球抓取。Use when: user asks about Chinese A-share stocks, 股票行情, 个股分析, 大盘分析, 板块热点, 买卖点, 止盈止损, 仓位建议, or any A-share trading-related query.
As a process F 35/100 · Will not run — References files that are not bundled: references/watchlist.md
The same skill appears in 4 more places: ClawHub, ClawHub, ClawHub, ClawHub
How to improve
- The text references files that are not there: add them or drop the references.
- 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
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: A股股票智能交易助手，专服务中国大陆股票市场。当用户询问A股股票行情、个股分析、大盘情绪、热点板块、交易策略、价格预警、涨跌幅、成交… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
missing-refreference to a missing file: references/watchlist.md
Process rating: all ten parameters 35/100
- 0Tools and files. 1 referenced file(s) missing: references/watchlist.md
- 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
- 100Steps. 25 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 451 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 270: enough signal without eating the budget
- +4Structure: 13 headings
- +3Step-by-step instructions: 25 items
- +4Has examples (2 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.