RRepoGEO

REPOGEO REPORT · LITE

getagentseal/codeburn

Default branch main · commit 8208cf8f · scanned 5/9/2026, 6:16:22 AM

GitHub: 5,892 stars · 457 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 getagentseal/codeburn, 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 core value proposition to the very top of README

    Why:

    CURRENT
    The README currently starts with centered paragraphs and empty links before the main descriptive text.
    COPY-PASTE FIX
    Add this sentence as the absolute first line of the README, before any formatting or badges: 'CodeBurn: Interactive TUI dashboard for AI coding token usage, cost, and performance observability across 18 AI coding tools (Claude Code, Codex, Cursor, etc.).'
  • highabout#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    Set the 'Homepage' field in the repository settings to: https://www.npmjs.com/package/codeburn
  • mediumabout#3
    Refine the 'About' description for clarity and keyword density

    Why:

    CURRENT
    See where your AI coding tokens go. Interactive TUI dashboard for Claude Code, Codex, and Cursor cost observability.
    COPY-PASTE FIX
    Interactive TUI dashboard for AI coding token usage and cost observability. Track spending across Claude Code, Codex, Cursor, and 15+ other AI coding assistants.

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 getagentseal/codeburn
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Helicone
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Helicone · recommended 2×
  2. OpenAI API Usage Dashboard · recommended 1×
  3. Azure AI Studio / Azure OpenAI Service Monitoring · recommended 1×
  4. LangChain Callbacks / Tracing · recommended 1×
  5. LangSmith · recommended 1×
  • CATEGORY QUERY
    How can I monitor token usage and cost for my AI coding assistant usage?
    you: not recommended
    AI recommended (in order):
    1. OpenAI API Usage Dashboard
    2. Azure AI Studio / Azure OpenAI Service Monitoring
    3. LangChain Callbacks / Tracing
    4. LangSmith
    5. Helicone
    6. LiteLLM (BerriAI/litellm)
    7. Custom API Wrappers with Logging

    AI recommended 7 alternatives but never named getagentseal/codeburn. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a local tool to observe AI coding costs broken down by project and model.
    you: not recommended
    AI recommended (in order):
    1. Langfuse
    2. OpenTelemetry
    3. Grafana
    4. Prometheus
    5. Datadog
    6. Helicone
    7. Weights & Biases
    8. Snowflake
    9. Google BigQuery
    10. Tableau
    11. Microsoft Power BI
    12. Metabase

    AI recommended 12 alternatives but never named getagentseal/codeburn. 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 getagentseal/codeburn?
    pass
    AI did not name getagentseal/codeburn — 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 getagentseal/codeburn in production, what risks or prerequisites should they evaluate first?
    pass
    AI named getagentseal/codeburn 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 getagentseal/codeburn solve, and who is the primary audience?
    pass
    AI named getagentseal/codeburn 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 getagentseal/codeburn. 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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getagentseal/codeburn — 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