소스 정보
- 저장소
- stanfish06/skillquarium
- 최근 소스 활동
- 2026년 8월 10일 05:02
- 감지된 SKILL.md 언어
- 영어
- 스타
- 7
- 포크
- 4
설치 방법
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
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/stanfish06/skillquarium --skill industry명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
build a repo-local skill and install a matching iterated coding-agent GitHub Actions workflow, prompt, memory file, and reference templates
interview the user to design an agentic control loop (sensor, controller, actuator under disturbances) tailored to their codebase, then build it as locally-runnable components plus a scheduled coding-agent workflow
narrow React component prop types to match live code paths
SOC 직업 분류 기준
SKILL.md 표시 중
| name | industry |
| description | Cross-company industry comparison across multiple tickers |
Perform an industry comparison across the companies named in the user's request. If no ticker or company is provided, ask for one before proceeding.
The user will provide multiple tickers separated by spaces (e.g., "AAPL MSFT GOOG AMZN").
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.
Follow these steps:
Look up all provided tickers using discover_companies. For each company, capture:
company_idlatest_calendar_quarter — use the earliest latest_calendar_quarter across all companies as the anchor for period calculations (see ../data-access.md Section 1.5)latest_fiscal_quarter../data-access.md Section 4.5Calculate 8 quarters backward from the anchor latest_calendar_quarter. For each company, find and pull these metrics:
Income Statement:
Cash Flow:
For any derived/computed metric, mark it with "(calc.)" so the reader knows it's not directly sourced.
First, think about what KPIs matter for the specific industry being compared. Use the full sector taxonomy to guide discovery:
For each company, discover and pull the most relevant KPIs. Note which KPIs are common across the group (apples-to-apples comparison) and which are unique to specific companies. For mixed-sector comparisons, focus on the KPIs that apply to the largest revenue segments of each company.
For each company, search the most recent 2 quarters of filings across multiple queries. If any search returns empty, try alternative keywords before giving up.
If a company returns sparse results across all searches, try broader single-keyword searches (e.g., just "competitive" or just "growth") and search additional periods.
For each company, extract:
Use these findings to enrich the rankings analysis — numbers tell you who's winning, filings tell you why.
Save to reports/{INDUSTRY_LABEL}_industry_comp.html (where INDUSTRY_LABEL is derived from the tickers, e.g., "AAPL_MSFT_GOOG_AMZN") using the HTML report template from ../design-system.md. Write the full analysis as styled HTML with the design system CSS inlined. This is the final deliverable — no intermediate markdown step needed.
The report should include:
All financial figures must use Daloopa citation format: <a href="https://daloopa.com/src/{fundamental_id}">$X.XX million</a>
Tell the user where the HTML report was saved.
Give a clear competitive verdict: Who is winning and who is losing? Which company has the strongest competitive position and why? Which company looks most vulnerable? Are any of the companies structurally mispriced relative to peers (too cheap or too expensive given the fundamentals)? Don't hedge — rank them honestly.