소스 정보
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- daloopa/daloopa-plugin-claude
- 최근 소스 활동
- 2026년 7월 22일 17:00
- 감지된 SKILL.md 언어
- 영어
- 스타
- 8
- 포크
- 1
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소스 파일 검토
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
메뉴
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/daloopa/daloopa-plugin-claude --skill initiate명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
SOC 직업 분류 기준
SKILL.md 표시 중
| 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