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PythonReactSEOPDF
OpenClaw

daily-stock-analysis

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.

hexavi80 installations selon la source☆ 0 Étoiles du dépôt

Installation

Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.

SkillHub CLI

skillhub install hexavi8/daily-stock-analysis

Examinez la source et la compatibilité, puis suivez les étapes d’installation.

Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.

Voir la source ↗Guides

Instructions

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/
  1. Use filename:
  • YYYY-MM-DD-<TICKER>-analysis.md
  1. If same ticker/day file exists, ask user:
  • overwrite or new_version (-v2, -v3, ...)
  • For unattended runs, default to new_version
  1. Always review history before new prediction.
  2. 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:
python3 {baseDir}/scripts/report_manager.py plan \
  --workdir <working_directory> \
  --ticker <TICKER> \
  --run-date <YYYY-MM-DD> \
  --versioning auto \
  --history-limit 5
  1. Compute rolling accuracy from existing reports:
python3 {baseDir}/scripts/calc_accuracy.py \
  --workdir <working_directory> \
  --ticker <TICKER> \
  --windows 1,3,7,30 \
  --history-limit 60
  1. Optional: migrate legacy files after explicit user confirmation:
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)
  1. 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
  1. Save report with same file...

Informations sur la source

Source
github
Repository
openclaw/skills
Path
skills/hexavi8/daily-stock-analysis
Version
—
Commit
f23c2e314f14f016bda3dce8ab7bd382760382e7
Source de classification
rules
Statut
active
Visibilité
public

Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.

Contenu extrait

SKILL.md
# 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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