RRepoGEO

REPOGEO REPORT · LITE

davidfowl/tally

Default branch main · commit 2dc309c6 · scanned 5/28/2026, 5:41:49 PM

GitHub: 1,135 stars · 93 forks

AI VISIBILITY SCORE
28 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 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 davidfowl/tally, 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 the README H1 and opening sentence to specify 'bank transactions'

    Why:

    CURRENT
    # Tally

**A local rule engine for transaction classification.** Pair it with an AI assistant to eliminate the manual work.
    COPY-PASTE FIX
    # Tally: A Local Rule Engine for Bank Transaction Classification

Pair it with an AI assistant to eliminate the manual work of categorizing your financial transactions.
  • hightopics#2
    Add specific topics to improve categorization

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    finance, banking, transaction-classification, ai-agent, local-rules, spending-reports, budgeting, personal-finance
  • mediumreadme#3
    Add a 'How Tally Differs' section to clarify its unique position

    Why:

    COPY-PASTE FIX
    ## How Tally Differs

Tally is designed for power users and developers who want a flexible, local engine for financial transaction classification. Unlike generic machine learning libraries, Tally is purpose-built for financial data. It also differs from all-in-one personal finance applications by providing a customizable, AI-agent-driven workflow rather than a closed-source, end-user experience.

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 davidfowl/tally
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
scikit-learn
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. scikit-learn · recommended 1×
  2. Pandas · recommended 1×
  3. Rasa · recommended 1×
  4. spaCy · recommended 1×
  5. Apache OpenNLP · recommended 1×
  • CATEGORY QUERY
    How can I automatically categorize bank transactions using a local rule engine and AI?
    you: not recommended
    AI recommended (in order):
    1. scikit-learn
    2. Pandas
    3. Rasa
    4. spaCy
    5. Apache OpenNLP

    AI recommended 5 alternatives but never named davidfowl/tally. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help classify financial transactions and generate spending reports with AI agents?
    you: not recommended
    AI recommended (in order):
    1. Copilot Money
    2. Mint
    3. Quicken Simplifi
    4. YNAB (You Need A Budget)
    5. Fyle
    6. Tiller Money

    AI recommended 6 alternatives but never named davidfowl/tally. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    warn

    Suggestion:

  • 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 davidfowl/tally?
    pass
    AI did not name davidfowl/tally — 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 davidfowl/tally in production, what risks or prerequisites should they evaluate first?
    pass
    AI named davidfowl/tally 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 davidfowl/tally solve, and who is the primary audience?
    pass
    AI named davidfowl/tally explicitly

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

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davidfowl/tally — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite