backtest-expert
Expert guidance for systematic backtesting of trading strategies. Use when developing, testing, stress-testing, or validating…
Monitor dividend portfolios with Kanchi-style forced-review triggers (T1-T5) and convert anomalies into OK/WARN/REVIEW states without auto-selling. Use when users ask for 減配検知, 8-Kガバナンス監視, 配当安全性モニタリング, REVIEWキュー自動化, or periodic dividend risk checks.
$ npx -y skills add BaggaT236/AI-Trading-Skills --skill kanchi-dividend-review-monitor --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/kanchi-dividend-review-monitorContext preview
The summary Claude sees to decide when to auto-load this skill.
Monitor dividend portfolios with Kanchi-style forced-review triggers (T1-T5) and convert anomalies into OK/WARN/REVIEW states without auto-selling. Use when users ask for 減配検知, 8-Kガバナンス監視, 配当安全性モニタリング, REVIEWキュー自動化, or periodic dividend risk checks.
name: kanchi-dividend-review-monitor description: Monitor dividend portfolios with Kanchi-style forced-review triggers (T1-T5) and convert anomalies into OK/WARN/REVIEW states without auto-selling. Use when users ask for 減配検知, 8-Kガバナンス監視, 配当安全性モニタリング, REVIEWキュー自動化, or periodic dividend risk checks.
Detect abnormal dividend-risk signals and route them into a human review queue. Treat automation as anomaly detection, not automated trade execution.
Use this skill when the user needs:
Provide normalized input JSON that follows:
If upstream data is unavailable, provide at least:
Never auto-sell based only on machine triggers. Always create `WARN` or `REVIEW` evidence for human confirmation first.
Use `references/trigger-matrix.md` for trigger thresholds and actions.
When T6 is driven only by `freeze_flag` / latest regular dividend equal to prior regular dividend, treat it as a `WARN` for cadence confirmation, not as proof of dividend deterioration. Many quarterly dividend payers repeat the same dividend for several quarters between annual raise cycles. In reports, phrase this as “confirm next dividend-growth cadence / pause optional adds until checked” and avoid implying a cut or broken thesis unless T1/T2/T3/T4/T5 evidence also supports escalation.
Collect per ticker fields in one JSON document:
Use `references/input-schema.md` for field definitions and sample payload.
Run:
python3 skills/kanchi-dividend-review-monitor/scripts/build_review_queue.py \ --input /path/to/monitor_input.json \ --output-dir reports/
The script maps each ticker to `OK/WARN/REVIEW` based on T1-T5. Output files are saved to the specified directory with dated filenames (e.g., `review_queue_20260227.json` and `.md`).
If multiple triggers fire:
For each `REVIEW` ticker, include:
Use `references/review-ticket-template.md` output format.
When implementing live SEC fetchers:
Always return: 1. Queue JSON with summary counts and ticker-level findings. 2. Markdown dashboard for quick triage. 3. List of immediate `REVIEW` tickets.
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