用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/daloopa/daloopa-plugin-claude --skill initiate命令会保持在同一行。复制前请横向滚动并检查完整内容。
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基于 SOC 职业分类
| name | initiate |
| description | Initiate coverage — generate both research note (.docx) and Excel model (.xlsx) |
| argument-hint | TICKER |
Initiate coverage on the company specified by the user: $ARGUMENTS
Before starting, read data-access.md for data access methods and design-system.md for formatting conventions. Follow the data access detection logic and design system throughout this skill.
This is the capstone skill that produces both a research note and an Excel model from a single comprehensive data gathering pass.
Rather than running /research-note and /build-model independently (which would duplicate data gathering), this skill gathers a superset of data once, then renders both outputs.
Look up the company by ticker using discover_companies. Capture:
company_idlatest_calendar_quarter — anchor for all period calculations (see data-access.md Section 1.5)latest_fiscal_quarterdata-access.md Section 4.5Get market data (see data-access.md Section 2):
Follow the /build-model skill's Phase 2 data pull (the most comprehensive). Calculate 8-16 quarters backward from latest_calendar_quarter. Pull:
Identify 5-8 comparable companies. Get peer trading multiples (see data-access.md Section 2). If consensus forward estimates are available (data-access.md Section 3), include NTM estimates. Pull peer fundamentals from Daloopa where available (revenue growth, margins).
Build forward estimates yourself — perform the calculations directly, no external tooling:
Search SEC filings comprehensively:
Build falsifiable bull/bear beliefs (follows /research-note methodology):
Write the executive summary, variant perception, and key findings.
Present all trend and sensitivity data as well-formatted tables (no chart images are generated):
Research Note: Compile all gathered data, charts, and narrative sections into a single styled HTML research note using the HTML Report Template from design-system.md (full CSS inlined, zero dependencies). Never output raw markdown — the design system explicitly forbids it. Present it directly in the response.
Excel Model:
Generate a React artifact that builds the model in-browser using the SheetJS (xlsx) library and triggers a download of {TICKER}_model.xlsx. Structure the workbook with one sheet per tab, preserving the same tab structure as the original model:
Assemble all gathered data (company info, market data, periods, historical statements, segments, KPIs, guidance, projections, projection assumptions, DCF outputs, comps) into a single in-memory data object inside the artifact, then use it to populate each sheet via SheetJS (XLSX.utils.aoa_to_sheet / json_to_sheet, XLSX.utils.book_append_sheet, XLSX.writeFile).
!!! MANDATORY EXCEL DATAPOINT HYPERLINK FORMAT !!!
123.4 to cell B5 and set its l property (SheetJS cell hyperlink, e.g. ws['B5'].l = { Target: "https://daloopa.com/src/71667434" }) so it renders as $123.4 millionMark projected/editable cells (e.g. the Projections tab assumptions) with distinct fill styling so the user can identify and adjust inputs after download.
If SheetJS generation fails for any reason, report the error clearly so the user can retry.
Present both deliverables directly in the response:
{TICKER}_model.xlsxThen provide:
All financial figures must use Daloopa citation format: $X.XX million