139 lines
3.8 KiB
Markdown
139 lines
3.8 KiB
Markdown
---
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name: daily-stock-analysis
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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.
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---
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# Daily Stock Analysis
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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.
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## Hard Rules
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1. Read and write files only under `working_directory`.
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2. Save new reports only to:
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- `<working_directory>/daily-stock-analysis/reports/`
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3. Use filename:
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- `YYYY-MM-DD-<TICKER>-analysis.md`
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4. If same ticker/day file exists, ask user:
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- `overwrite` or `new_version` (`-v2`, `-v3`, ...)
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- For unattended runs, default to `new_version`
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5. Always review history before new prediction.
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6. Limit history read count to control token usage:
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- Script mode: max 5 files (default)
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- Compatibility mode: max 3 files
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## Required Scripts (Use First)
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1. Plan output path + collect history:
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```bash
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python3 {baseDir}/scripts/report_manager.py plan \
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--workdir <working_directory> \
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--ticker <TICKER> \
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--run-date <YYYY-MM-DD> \
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--versioning auto \
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--history-limit 5
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```
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2. Compute rolling accuracy from existing reports:
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```bash
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python3 {baseDir}/scripts/calc_accuracy.py \
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--workdir <working_directory> \
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--ticker <TICKER> \
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--windows 1,3,7,30 \
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--history-limit 60
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```
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3. Optional: migrate legacy files after explicit user confirmation:
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```bash
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python3 {baseDir}/scripts/report_manager.py migrate \
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--workdir <working_directory> \
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--file <ABS_PATH_1> --file <ABS_PATH_2>
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```
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## Compatibility Mode (No Python / Small Model)
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If Python scripts are unavailable or model capability is limited, switch to minimal mode:
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1. Read at most 3 recent reports for the same ticker.
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2. Use only a minimal source set:
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- one official disclosure source
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- one reliable market data source (Yahoo Finance acceptable)
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3. Output concise result only:
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- recommendation
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- `pred_close_t1`
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- prior review (`prev_pred_close_t1`, `prev_actual_close_t1`, `AE`, `APE`) if available
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- one `improvement_action`
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4. Save report with same filename rules in canonical reports directory.
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See `references/minimal_mode.md`.
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## Minimal Run Protocol
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1. Resolve ticker/exchange/market (ask if ambiguous).
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2. Run `report_manager.py plan`.
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3. Read `history_files` returned by script.
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4. If `legacy_files` exist, list all absolute paths and ask whether to migrate.
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5. Gather data using `references/sources.md` + `references/search_queries.md`.
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6. Run `calc_accuracy.py` for consistent metrics.
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7. Render report using `references/report_template.md`.
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8. Save to `selected_output_file` returned by `report_manager.py`.
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## Required Output Fields
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Must include:
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- `recommendation`
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- `pred_close_t1`
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- `prev_pred_close_t1`
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- `prev_actual_close_t1`
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- `AE`, `APE`
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- rolling strict/loose accuracy fields
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- `improvement_actions`
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## Self-Improvement (Required)
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Each run must include 1-3 concrete `improvement_actions` from recent misses and use them in the next run.
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Do not skip this step.
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## Scheduling Recommendation
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Recommend users set this as a weekday recurring task (for example 10:00 local time) to keep prediction-review windows continuous.
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## References
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Default:
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- `references/workflow.md`
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- `references/report_template.md`
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- `references/metrics.md`
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- `references/search_queries.md`
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- `references/sources.md`
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- `references/minimal_mode.md`
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- `references/security.md`
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Deep-dive only (`full_report` mode):
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- `references/fundamental-analysis.md`
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- `references/technical-analysis.md`
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- `references/financial-metrics.md`
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## Compliance
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Always append:
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"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."
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