RRepoGEO

REPOGEO REPORT · LITE

Einsia/OpenChronicle

Default branch main · commit bad3a1e8 · scanned 6/26/2026, 9:52:55 PM

GitHub: 2,778 stars · 213 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)

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

AI VISIBILITY SCORE
30 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
3 / 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 Einsia/OpenChronicle, 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
  • highabout#1
    Add a concise project description

    Why:

    COPY-PASTE FIX
    Open-source, local-first memory for any tool-capable LLM agent, built from real screen and app context.
  • hightopics#2
    Add relevant topics for AI agent memory

    Why:

    COPY-PASTE FIX
    llm-agents, ai-agents, memory, local-first, contextual-memory, macOS, open-source, chronicle
  • highreadme#3
    Add a prominent H2 clarifying the project's core purpose

    Why:

    COPY-PASTE FIX
    ## OpenChronicle: Local-First Memory for LLM Agents

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 Einsia/OpenChronicle
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
SQLite
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. SQLite · recommended 1×
  2. sqlalchemy/sqlalchemy · recommended 1×
  3. coleifer/peewee · recommended 1×
  4. sqlite3 · recommended 1×
  5. duckdb/duckdb · recommended 1×
  • CATEGORY QUERY
    How can I provide my LLM agent with persistent, inspectable, local-first memory?
    you: not recommended
    AI recommended (in order):
    1. SQLite
    2. SQLAlchemy Core (sqlalchemy/sqlalchemy)
    3. Peewee (coleifer/peewee)
    4. sqlite3
    5. DuckDB (duckdb/duckdb)
    6. ChromaDB (chroma-core/chroma)
    7. LanceDB (lancedb/lancedb)
    8. LMDB
    9. RocksDB (facebook/rocksdb)
    10. shelve
    11. JSON
    12. YAML
    13. Pickle
    14. LangChain (langchain-ai/langchain)
    15. ConversationBufferMemory
    16. VectorStoreRetrieverMemory

    AI recommended 16 alternatives but never named Einsia/OpenChronicle. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help AI agents build memory from real-time screen and application context?
    you: not recommended
    AI recommended (in order):
    1. OpenCV
    2. Tesseract OCR
    3. PyAutoGUI
    4. Selenium
    5. Faiss
    6. Pinecone
    7. Weaviate
    8. LangChain
    9. LlamaIndex
    10. Neo4j

    AI recommended 10 alternatives but never named Einsia/OpenChronicle. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 Einsia/OpenChronicle?
    pass
    AI named Einsia/OpenChronicle explicitly

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

  • If a team adopts Einsia/OpenChronicle in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Einsia/OpenChronicle 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 Einsia/OpenChronicle solve, and who is the primary audience?
    pass
    AI named Einsia/OpenChronicle explicitly

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

Embed your GEO score

Drop this badge into the README of Einsia/OpenChronicle. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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Einsia/OpenChronicle — 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