backtest-expert
Expert guidance for systematic backtesting of trading strategies. Use when developing,…
Build and open FinViz screener URLs from natural language requests. Use when user wants to screen stocks, find stocks matching criteria, filter by fundamentals or technicals, or asks to open FinViz with specific conditions. Supports both Japanese and English input (e.g.,
$ npx -y skills add tradermonty/claude-trading-skills --skill finviz-screener --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/finviz-screenerContext preview
The summary Claude sees to decide when to auto-load this skill.
Build and open FinViz screener URLs from natural language requests. Use when user wants to screen stocks, find stocks matching criteria, filter by fundamentals or technicals, or asks to open FinViz with specific conditions. Supports both Japanese and English input (e.g.,
name: finviz-screener description: Build and open FinViz screener URLs from natural language requests. Use when user wants to screen stocks, find stocks matching criteria, filter by fundamentals or technicals, or asks to open FinViz with specific conditions. Supports both Japanese and English input (e.g., "高配当で成長している小型株を探したい", "Find oversold large caps with high ROE").
Translate natural-language stock screening requests into FinViz screener filter codes, build the URL, and open it in Chrome. No API key required for public screener; FINVIZ Elite is auto-detected from `$FINVIZ_API_KEY` for enhanced functionality.
**Key Features:**
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**Explicit Triggers:**
**Implicit Triggers:**
**When NOT to Use:**
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Read the filter knowledge base:
cat references/finviz_screener_filters.md
Map the user's natural-language request to FinViz filter codes. Use the Common Concept Mapping table below for quick translation, and reference the full filter list for precise code selection.
**Note:** For range criteria (e.g., "dividend 3-8%", "P/E between 10 and 20"), use the `{from}to{to}` range syntax as a single filter token (e.g., `fa_div_3to8`, `fa_pe_10to20`) instead of combining separate `_o` and `_u` filters.
**Common Concept Mapping:**
| User Concept (EN) | User Concept (JP) | Filter Codes | |---|---|---| | High dividend | 高配当 | `fa_div_o3` or `fa_div_o5` | | Small cap | 小型株 | `cap_small` | | Mid cap | 中型株 | `cap_mid` | | Large cap | 大型株 | `cap_large` | | Mega cap | 超大型株 | `cap_mega` | | Value / cheap | 割安 | `fa_pe_u20,fa_pb_u2` | | Growth stock | 成長株 | `fa_epsqoq_o25,fa_salesqoq_o15` | | Oversold | 売られすぎ | `ta_rsi_os30` | | Overbought | 買われすぎ | `ta_rsi_ob70` | | Near 52W high | 52週高値付近 | `ta_highlow52w_b0to5h` | | Near 52W low | 52週安値付近 | `ta_highlow52w_a0to5l` | | Breakout | ブレイクアウト | `ta_highlow52w_b0to5h,sh_relvol_o1.5` | | Technology | テクノロジー | `sec_technology` | | Healthcare | ヘルスケア | `sec_healthcare` | | Energy | エネルギー | `sec_energy` | | Financial | 金融 | `sec_financial` | | Semiconductors | 半導体 | `ind_semiconductors` | | Biotechnology | バイオテク | `ind_biotechnology` | | US stocks | 米国株 | `geo_usa` | | Profitable | 黒字 | `fa_pe_profitable` | | High ROE | 高ROE | `fa_roe_o15` or `fa_roe_o20` | | Low debt | 低負債 | `fa_debteq_u0.5` | | Insider buying | インサイダー買い | `sh_insidertrans_verypos` | | Short squeeze | ショートスクイーズ | `sh_short_o20,sh_relvol_o2` | | Dividend growth | 増配 | `fa_divgrowth_3yo10` | | Deep value | ディープバリュー | `fa_pb_u1,fa_pe_u10` | | Momentum | モメンタム | `ta_perf_13wup,ta_sma50_pa,ta_sma200_pa` | | Defensive | ディフェンシブ | `ta_beta_u0.5` or `sec_utilities,sec_consumerdefensive` | | Liquid / high volume | 高出来高 | `sh_avgvol_o500` or `sh_avgvol_o1000` | | Pullback from high | 高値からの押し目 | `ta_highlow52w_10to30-bhx` | | Near 52W low reversal | 安値圏リバーサル | `ta_highlow52w_10to30-alx` | | Fallen angel | 急落後反発 | `ta_highlow52w_b20to30h,ta_rsi_os40` | | AI theme | AIテーマ | `--themes "artificialintelligence"` | | Cybersecurity theme | サイバーセキュリティ | `--themes "cybersecurity"` | | AI + Cybersecurity | AI&サイバーセキュリティ | `--themes "artificialintelligence,cybersecurity"` | | AI Cloud sub-theme | AIクラウド | `--subthemes "aicloud"` | | AI Compute sub-theme | AI半導体 | `--subthemes "aicompute"` | | Yield 3-8% (trap excluded) | 配当3-8%(トラップ除外)| `fa_div_3to8` | | Mid-range P/E | 適正PER帯 | `fa_pe_10to20` | | EV undervalued | EV割安 | `fa_evebitda_u10` | | Earnings next week | 来週決算 | `earningsdate_nextweek` | | IPO recent | 直近IPO | `ipodate_thismonth` | | Target price above | 目標株価以上 | `targetprice_a20` | | Recent news | 最新ニュースあり | `news_date_today` | | High institutional | 機関保有率高 | `sh_instown_o60` | | Low float | 浮動株少 | `sh_float_u20` | | Near all-time high | 史上最高値付近 | `ta_alltime_b0to5h` | | High ATR | 高ボラティリティ | `ta_averagetruerange_o1.5` |
Before executing, present the selected filters in a table for user confirmation:
| Type | Value | Meaning | |---|---|---| | Theme | artificialintelligence | Artificial Intelligence | | Sub-theme | aicloud | AI - Cloud & Infrastructure | | Filter | cap_small | Small Cap ($300M–$2B) | | Filter | fa_div_o3 | Dividend Yield > 3% | | Filter | fa_pe_u20 | P/E < 20 | | Filter | geo_usa | USA | View: Overview (v=111) Mode: Public / Elite (auto-detected)
Ask the user to confirm or adjust before proceeding.
Run the screener script to build the URL and open Chrome:
python3 scripts/open_finviz_screener.py \ --filters "cap_small,fa_div_o3,fa_pe_u20,geo_usa" \ --view overview # Theme-only screening (no --filters required) python3 scripts/open_finviz_screener.py \ --themes "artificialintelligence,cybersecurity" \ --url-only # Theme + sub-theme + filters combined python3 scripts/open_finviz_screener.py \ --themes "artificialintelligence" \ -
Claude Trading Skills started as a personal project to use AI to improve my own trading process. Claude Trading Skills is a Claude Skills-based trading workflow toolkit for time-constrained individual investors.
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