RRepoGEO

REPOGEO REPORT · LITE

HugoRCD/evlog

Default branch main · commit 6d4d87c1 · scanned 5/23/2026, 5:31:35 AM

GitHub: 1,348 stars · 41 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
40 /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
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 HugoRCD/evlog, 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 H1 and opening paragraph to clarify language and type

    Why:

    CURRENT
    # evlog

**Digging through logs is not observability. It's hope.**
    COPY-PASTE FIX
    # evlog: TypeScript-first Observability Library for Modern Web Applications

**Digging through logs is not observability. It's hope.**

evlog is a TypeScript-first library designed for modern web applications, providing a powerful approach to application observability. Instead of scattered log lines, evlog focuses on capturing one comprehensive 'wide event' per operation, ensuring all context is available when you need it most. It delivers structured errors that explain *why* something went wrong and what to do next, across every runtime.
  • highabout#2
    Refine repository description to emphasize 'library' and 'enabling observability'

    Why:

    CURRENT
    Digging through logs is not observability. It's hope. — wide events, structured errors, TypeScript-first, every runtime.
    COPY-PASTE FIX
    evlog is a TypeScript-first library for modern web applications, enabling true observability with wide events and structured errors across every runtime. Stop hoping, start seeing.
  • mediumreadme#3
    Add a direct comparison section in README against common logging libraries

    Why:

    COPY-PASTE FIX
    Add a new section heading and introductory sentence to the README, for example:

```
## evlog vs. Traditional Logging (Pino, Winston, Bunyan)

Unlike traditional logging libraries that often produce scattered, line-by-line outputs, evlog's core differentiator is its 'one wide event per operation' philosophy, ensuring comprehensive context and structured errors for true observability.
```

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 HugoRCD/evlog
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Datadog
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Datadog · recommended 1×
  2. Splunk · recommended 1×
  3. ELK Stack · recommended 1×
  4. Elasticsearch · recommended 1×
  5. Logstash · recommended 1×
  • CATEGORY QUERY
    How to get better observability from application logs instead of scattered console outputs?
    you: not recommended
    AI recommended (in order):
    1. Datadog
    2. Splunk
    3. ELK Stack
    4. Elasticsearch
    5. Logstash
    6. Kibana
    7. Filebeat
    8. Metricbeat
    9. Elastic Stack
    10. Grafana Loki
    11. New Relic Logs
    12. Sumo Logic
    13. Logz.io

    AI recommended 13 alternatives but never named HugoRCD/evlog. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    TypeScript-first logging solution for modern web applications with structured errors and context?
    you: not recommended
    AI recommended (in order):
    1. Pino (pinojs/pino)
    2. Winston (winstonjs/winston)
    3. Bunyan (trentm/node-bunyan)
    4. LogRocket
    5. Sentry (getsentry/sentry)
    6. Signadot
    7. OpenTelemetry (open-telemetry/opentelemetry-js)

    AI recommended 7 alternatives but never named HugoRCD/evlog. 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 HugoRCD/evlog?
    pass
    AI named HugoRCD/evlog explicitly

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

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

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

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MARKDOWN (README)
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HugoRCD/evlog — 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
HugoRCD/evlog — RepoGEO report