openclaw-home-pc/workspace/skills/daily-stock-analysis/SKILL.md
2026-03-21 15:31:06 +08:00

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---
name: daily-stock-analysis
description: 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.
---
# 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 filename rules in canonical reports directory.
See `references/minimal_mode.md`.
## Minimal Run Protocol
1. Resolve ticker/exchange/market (ask if ambiguous).
2. Run `report_manager.py plan`.
3. Read `history_files` returned by script.
4. If `legacy_files` exist, list all absolute paths and ask whether to migrate.
5. Gather data using `references/sources.md` + `references/search_queries.md`.
6. Run `calc_accuracy.py` for consistent metrics.
7. Render report using `references/report_template.md`.
8. Save to `selected_output_file` returned by `report_manager.py`.
## Required Output Fields
Must include:
- `recommendation`
- `pred_close_t1`
- `prev_pred_close_t1`
- `prev_actual_close_t1`
- `AE`, `APE`
- rolling strict/loose accuracy fields
- `improvement_actions`
## Self-Improvement (Required)
Each run must include 1-3 concrete `improvement_actions` from recent misses and use them in the next run.
Do not skip this step.
## Scheduling Recommendation
Recommend users set this as a weekday recurring task (for example 10:00 local time) to keep prediction-review windows continuous.
## References
Default:
- `references/workflow.md`
- `references/report_template.md`
- `references/metrics.md`
- `references/search_queries.md`
- `references/sources.md`
- `references/minimal_mode.md`
- `references/security.md`
Deep-dive only (`full_report` mode):
- `references/fundamental-analysis.md`
- `references/technical-analysis.md`
- `references/financial-metrics.md`
## Compliance
Always append:
"This content is for research and informational purposes only and does not constitute investment advice or a return guarantee. Markets are risky; invest with caution."