BF stock-prediction-daily
A股个股日线涨跌预测系统。七大能力：训练模型（XGBoost二分类+交叉验证+输出模型文件和报告）、优化模型（扩展特征+特征筛选）、模型预测（腾讯日线）、模型评估（日线T+1验证）、输出网页（Flask五页面仪表盘）、板块分析（直接调用stock-sector-research技能）、个股分析（直接调用stock-watchlist-briefing技能）。Use when: 股票预测, stock prediction, 训练模型, train model, 模型优化, optimize model, 模型预测, predict stock, 模型评估, evaluate model, 预测网页, prediction dashboard, 板块分析, sector research, 个股分析, watchlist briefing, XGBoost, A股, 沪深300, daily prediction, 日线预测
As a process F 33/100 · Will not run — References files that are not bundled: scripts/reports/, scripts/data/{code}_daily.csv, scripts/models/xgb_stock_model.pkl
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: 17. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
missing-refreference to a missing file: scripts/reports/ - warning
missing-refreference to a missing file: scripts/data/{code}_daily.csv - warning
missing-refreference to a missing file: scripts/models/xgb_stock_model.pkl - warning
missing-refreference to a missing file: scripts/models/scaler.pkl - warning
missing-refreference to a missing file: scripts/models/feature_names.json - warning
missing-refreference to a missing file: scripts/results/model_report.json - warning
missing-refreference to a missing file: scripts/data/ - warning
missing-refreference to a missing file: scripts/results/predictions.csv - warning
missing-refreference to a missing file: scripts/results/prediction_history/predictions_YYYYMMDD_HHMMSS.csv - warning
missing-refreference to a missing file: scripts/reports/sector_analysis/ - warning
missing-refreference to a missing file: scripts/reports/stock_analysis/
Process rating: all ten parameters 33/100
- 0Tools and files. 11 referenced file(s) missing: scripts/reports/, scripts/data/{code}_daily.csv, scripts/models/xgb_stock_model.pkl
- 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. 1 mutating operations with no state check
- 100Steps. 122 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1871 tokens
- low 13 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
- +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
- -42 reference files, but SKILL.md never points to them: the model will not open them
- +1No license
- +2Single-language instructions
- +3Description length 417: enough signal without eating the budget
- +4Structure: 40 headings
- +3Step-by-step instructions: 122 items
- +4Has examples (6 code blocks)
- +3All 7 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.