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Skill for accessing, downloading, and parsing financial filings from the SEC EDGAR database. Helps users retrieve 10-K, 10-Q, 8-K, and other forms using the SEC's JSON API.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
Structured hypothesis formulation from observations. Use when you have experimental observations or data and need to formulate testable hypotheses with predictions, propose mechanisms, and design experiments to test them. Follows scientific method framework. For open-ended ideation use scientific-brainstorming; for automated LLM-driven hypothesis testing on datasets use hypogenic.
Transforms raw user requests into structured, outcome-focused prompts for Claude Cowork. Use when the user wants to optimize or rewrite a prompt for Cowork, needs help structuring a multi-step task for autonomous execution, or says things like "optimize this Cowork prompt", "rewrite for Cowork", or "make this a Cowork prompt". Outputs a single code block with the rewritten prompt following the GOAL/CONTEXT LOADING/IDENTITY/SUCCESS CRITERIA/INPUTS/CONSTRAINTS/CHECKPOINT RULE structure.
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Creative research ideation and exploration. Use for open-ended brainstorming sessions, exploring interdisciplinary connections, challenging assumptions, or identifying research gaps. Best for early-stage research planning when you do not have specific observations yet. For formulating testable hypotheses from data use hypothesis-generation.
Comprehensive citation management for academic research. Search Google Scholar and PubMed for papers, extract accurate metadata, validate citations, and generate properly formatted BibTeX entries. This skill should be used when you need to find papers, verify citation information, convert DOIs to BibTeX, or ensure reference accuracy in scientific writing.
Match a pasted list of academic references against the Crossref REST API and produce a four-column markdown table (original, matched, confidence, flags) with canonical APA citations and DOIs. Use whenever the user pastes a bibliography or reference list and wants to verify, clean up, canonicalize, or find DOIs for those references — triggers include "verify bibliography", "match these references", "find DOIs for this reference list", "canonicalize my citations", "clean up the reference list against Crossref", "check these citations", or any pasted block of academic references accompanied by a request to normalize them.
| name | sec-edgar-parser |
| description | Skill for accessing, downloading, and parsing financial filings from the SEC EDGAR database. Helps users retrieve 10-K, 10-Q, 8-K, and other forms using the SEC's JSON API. |
This skill enables the agent to interact with the SEC's EDGAR system to retrieve corporate filings and extract financial data.
company_tickers.json).10-K for annual reports, 10-Q for quarterly, 8-K for current events).https://data.sec.gov/submissions/CIK{cik_padded}.jsonhttps://www.sec.gov/Archives/edgar/data/{cik}/{accession_number}/{primary_document}BeautifulSoup to strip HTML tags and extract sections (e.g., "Item 1A. Risk Factors", "Item 7. MD&A").pd.read_html() to convert HTML tables into Pandas DataFrames.Sample Company Name AdminContact@sample.com. Requests without this will be blocked.scripts/sec_utils.pyA utility script to:
from scripts.sec_utils import get_cik, get_filings
cik = get_cik("AAPL")
filings = get_filings(cik, form_type="10-K")
print(filings.head())
from scripts.sec_utils import download_filing
# Use the URL from the filings dataframe
text = download_filing(filings.iloc[0]['url'])