Overview
- Skill Key
- hexavi8/daily-stock-analysis
- Author
- hexavi8
- Source Repo
- openclaw/skills
- Version
- -
- Source Path
- skills/hexavi8/daily-stock-analysis
- Latest Commit SHA
- f23c2e314f14f016bda3dce8ab7bd382760382e7
Deterministic daily stock analysis skill for global equities. Use when users need daily analysis, next-trading-day close prediction, prior forecast review, rolling accuracy, and reliable markdown report output.
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Status
ACTIVE
Visibility
PUBLIC
直接复制以下提示词,发送给你的 AI 助手即可完成安装。
请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 daily-stock-analysis 技能。 若已安装,则直接安装 daily-stock-analysis 技能。
# Daily Stock Analysis
Perform market-aware, evidence-based daily stock analysis with prediction, next-run review, rolling accuracy tracking, and a structured self-evolution mechanism that updates future assumptions from observed forecast errors.
## Hard Rules
1. Read and write files only under `working_directory`.
2. Save new reports only to:
- `<working_directory>/daily-stock-analysis/reports/`
3. Use filename:
- `YYYY-MM-DD-<TICKER>-analysis.md`
4. If same ticker/day file exists, ask user:
- `overwrite` or `new_version` (`-v2`, `-v3`, ...)
- For unattended runs, default to `new_version`
5. Always review history before new prediction.
6. Limit history read count to control token usage:
- Script mode: max 5 files (default)
- Compatibility mode: max 3 files
## Required Scripts (Use First)
1. Plan output path + collect history:
```bash
python3 {baseDir}/scripts/report_manager.py plan \
--workdir <working_directory> \
--ticker <TICKER> \
--run-date <YYYY-MM-DD> \
--versioning auto \
--history-limit 5
```
2. Compute rolling accuracy from existing reports:
```bash
python3 {baseDir}/scripts/calc_accuracy.py \
--workdir <working_directory> \
--ticker <TICKER> \
--windows 1,3,7,30 \
--history-limit 60
```
3. Optional: migrate legacy files after explicit user confirmation:
```bash
python3 {baseDir}/scripts/report_manager.py migrate \
--workdir <working_directory> \
--file <ABS_PATH_1> --file <ABS_PATH_2>
```
## Compatibility Mode (No Python / Small Model)
If Python scripts are unavailable or model capability is limited, switch to minimal mode:
1. Read at most 3 recent reports for the same ticker.
2. Use only a minimal source set:
- one official disclosure source
- one reliable market data source (Yahoo Finance acceptable)
3. Output concise result only:
- recommendation
- `pred_close_t1`
- prior review (`prev_pred_close_t1`, `prev_actual_close_t1`, `AE`, `APE`) if available
- one `improvement_action`
4. Save report with same file...
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