RRepoGEO

REPOGEO REPORT · LITE

chiphuyen/sniffly

Default branch main · commit a237d7e9 · scanned 6/26/2026, 11:18:04 AM

GitHub: 1,242 stars · 115 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
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 chiphuyen/sniffly, 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's opening sentence to explicitly state its niche

    Why:

    CURRENT
    Analyze Claude Code logs to help you use Claude Code better.
    COPY-PASTE FIX
    Sniffly is a dedicated analytics dashboard for Claude Code logs, providing usage stats, error analysis, and sharable insights to optimize your AI assistant workflows.
  • mediumtopics#2
    Add more specific topics to improve category visibility

    Why:

    CURRENT
    agent, ai, analytics, coding
    COPY-PASTE FIX
    claude-code, llm-analytics, ai-assistant, usage-monitoring, error-analysis, dashboard, generative-ai
  • lowabout#3
    Refine the 'About' description for greater precision

    Why:

    CURRENT
    Claude Code dashboard with usage stats, error analysis, and sharable feature
    COPY-PASTE FIX
    Dedicated dashboard for Claude Code logs, offering usage statistics, detailed error analysis, and sharable insights to optimize AI assistant interactions.

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 chiphuyen/sniffly
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain Plus (now LangSmith)
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain Plus (now LangSmith) · recommended 1×
  2. Datadog · recommended 1×
  3. Sentry · recommended 1×
  4. Grafana · recommended 1×
  5. Prometheus · recommended 1×
  • CATEGORY QUERY
    How can I track usage patterns and debug errors in my AI assistant workflows?
    you: not recommended
    AI recommended (in order):
    1. LangChain Plus (now LangSmith)
    2. Datadog
    3. Sentry
    4. Grafana
    5. Prometheus
    6. Loki
    7. Mixpanel
    8. OpenTelemetry

    AI recommended 8 alternatives but never named chiphuyen/sniffly. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a dashboard to visualize AI agent interactions and share analysis with colleagues.
    you: not recommended
    AI recommended (in order):
    1. Grafana (grafana/grafana)
    2. Tableau
    3. Power BI
    4. Looker Studio
    5. Kibana (elastic/kibana)
    6. Apache Superset (apache/superset)
    7. Plotly Dash (plotly/dash)

    AI recommended 7 alternatives but never named chiphuyen/sniffly. 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 chiphuyen/sniffly?
    pass
    AI did not name chiphuyen/sniffly — 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 chiphuyen/sniffly in production, what risks or prerequisites should they evaluate first?
    pass
    AI named chiphuyen/sniffly 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 chiphuyen/sniffly solve, and who is the primary audience?
    pass
    AI named chiphuyen/sniffly explicitly

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

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chiphuyen/sniffly — 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