RRepoGEO

REPOGEO REPORT · LITE

dgunning/edgartools

Default branch main · commit 6b785787 · scanned 6/24/2026, 2:36:54 AM

GitHub: 2,387 stars · 412 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
33 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 warn · 0 fail
Objective metadata checks
AI knows your name
2 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface dgunning/edgartools, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition README opening to emphasize structured data analysis and standardization

    Why:

    CURRENT
    EdgarTools is a Python library for accessing SEC EDGAR filings as structured data. Parse financial statements, insider trades, fund holdings, proxy statements, and 20+ other filing types with a consistent Python API — in a few lines of code. Free and open source.
    COPY-PASTE FIX
    EdgarTools is a Python library that transforms raw SEC EDGAR filings into structured, standardized data for financial analysis. It provides a clean, well-typed API to parse financial statements, insider trades, fund holdings, and 20+ other filing types, making complex XBRL data instantly usable for investment research and quantitative finance.
  • mediumcomparison#2
    Add a 'Comparison' section to the README

    Why:

    COPY-PASTE FIX
    ## Comparison to Alternatives

EdgarTools stands apart from generic XML parsers (like `lxml`), raw SEC API wrappers, or data rendering tools by focusing on transforming complex, unstructured EDGAR data into standardized, ready-to-use Python objects for financial analysis. Unlike services that provide pre-processed data, EdgarTools gives you direct, programmatic control over the raw filings, ensuring transparency and flexibility for deep investment research and quantitative modeling.
  • lowtopics#3
    Expand topics to include analytical and standardization terms

    Why:

    CURRENT
    10-k, 10-q, 13-f, 8-k, balance-sheet, bdc, cashflow-statement, company, cusip, edgar, filings, financials, form-4, income-statement, insider-trading, sec, tickers, xbrl
    COPY-PASTE FIX
    10-k, 10-q, 13-f, 8-k, balance-sheet, bdc, cashflow-statement, company, cusip, edgar, filings, financials, form-4, income-statement, insider-trading, sec, tickers, xbrl, financial-analysis, data-standardization, investment-research, quantitative-finance

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface dgunning/edgartools
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
lxml
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. lxml · recommended 2×
  2. SEC EDGAR Renderer · recommended 1×
  3. sec-api.io Python SDK · recommended 1×
  4. XBRL-US · recommended 1×
  5. OpenBB Terminal · recommended 1×
  • CATEGORY QUERY
    Python library to parse and standardize public company financial statements and regulatory forms?
    you: not recommended
    AI recommended (in order):
    1. SEC EDGAR Renderer
    2. sec-api.io Python SDK
    3. XBRL-US
    4. OpenBB Terminal
    5. Beautiful Soup
    6. lxml
    7. Pandas

    AI recommended 7 alternatives but never named dgunning/edgartools. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to programmatically access and analyze corporate financial disclosures for investment research?
    you: not recommended
    AI recommended (in order):
    1. XBRLExplorer
    2. Financial Modeling Prep (FMP) API
    3. BamSEC API
    4. SEC EDGAR API
    5. Quandl (now Nasdaq Data Link)
    6. Alpha Vantage API
    7. FactSet
    8. Bloomberg Terminal APIs
    9. sec-api
    10. xbrl-fundamentals
    11. BeautifulSoup
    12. lxml

    AI recommended 12 alternatives but never named dgunning/edgartools. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of dgunning/edgartools?
    pass
    AI did not name dgunning/edgartools — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts dgunning/edgartools in production, what risks or prerequisites should they evaluate first?
    pass
    AI named dgunning/edgartools explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo dgunning/edgartools solve, and who is the primary audience?
    pass
    AI named dgunning/edgartools explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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dgunning/edgartools — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite