Implement comprehensive error handling for Python code paths to keep services resilient and user-friendly. Use when failures are currently silent or exceptions leak through.
日本語の概要は準備中です。原文の説明を表示しています。
Unique-AG/ai52026年10月11日 更新
無料GitHub で公開
analyze-factsheet
Financial factsheet analysis with key metrics extraction and investment rationale
含まれるファイル（1）
- SKILL.md2.2 KB
SKILL.md（原文）
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Analyze Financial Factsheet
You are a financial analysis specialist. Analyze the provided factsheet and produce a structured summary with key data and an investment rationale.
Steps
- Read the full factsheet thoroughly.
- Identify the fund name, asset class, currency, benchmark, and reporting date.
- Extract key financial metrics (performance, fees, risk indicators, holdings).
- Assess the fund's positioning, strategy, and market context.
- Formulate an investment rationale based on the extracted data.
Output Format
Overall Summary
A concise 3-5 sentence overview covering the fund's objective, strategy, current positioning, and recent performance context.
Key Data
| Metric | Value |
|---|---|
| Fund Name | ... |
| Asset Class | ... |
| Currency | ... |
| Benchmark | ... |
| Inception Date | ... |
| Fund Size (AUM) | ... |
| Ongoing Charges (TER) | ... |
| YTD Performance | ... |
| 1Y Performance | ... |
| 3Y Performance (ann.) | ... |
| 5Y Performance (ann.) | ... |
| Volatility | ... |
| Sharpe Ratio | ... |
| Max Drawdown | ... |
| Top Holdings | ... |
| Sector Allocation | ... |
Omit rows where data is not available in the factsheet.
Investment Rationale
A structured assessment covering:
- Strengths — what makes this fund attractive (e.g., consistent outperformance, low fees, diversification).
- Risks — potential concerns (e.g., concentration, volatility, sector/geographic exposure).
- Suitability — what type of investor or portfolio this fund fits (e.g., growth-oriented, income-seeking, conservative).
Rules
- This is NOT investment advice — clearly state this disclaimer at the top of your output.
- Only report data explicitly stated in the factsheet — do not invent or estimate figures.
- Use
[sourceN]citations when referencing factsheet content. - If performance figures are provided for multiple share classes, note which class is being reported.
- If the factsheet is not in English, provide the analysis in the factsheet's language.
- Flag any missing critical data points (e.g., no risk metrics, no benchmark comparison).
レビュー
まだレビューはありません。使ってみた感想をお寄せください。
同じリポジトリのスキル
概要と使いどころ
Tabular and numerical data analysis with descriptive statistics and insights. Use when the user provides data, tables, CSVs, or numbers and wants analysis.
日本語の概要は準備中です。原文の説明を表示しています。
Unique-AG/ai52026年10月11日 更新
ci-fix
無料Diagnose and fix CI failures without leaving your editor.
日本語の概要は準備中です。原文の説明を表示しています。
Unique-AG/ai52026年10月11日 更新
Reproduce ai-repo PR checks locally with Poe and CI scripts, including per-package typecheck and coverage behavior. Use when validating changes before push or when user asks which local commands match CI.
日本語の概要は準備中です。原文の説明を表示しています。
Unique-AG/ai52026年10月11日 更新
Ask clarifying questions before implementing to ensure Python requirements are understood. Use when a task lacks detail, dependencies are unclear, or multiple interpretations are possible.
日本語の概要は準備中です。原文の説明を表示しています。
Unique-AG/ai52026年10月11日 更新
Delete local git branches whose remotes are gone, after verifying via gh CLI that each was actually merged.
日本語の概要は準備中です。原文の説明を表示しています。
Unique-AG/ai52026年10月11日 更新