Home/Compare/every_eval_ever vs auto-evaluator

Comparison

every_eval_ever vs auto-evaluator

Verdict

Pick every_eval_ever when every_eval_ever is primarily Python; auto-evaluator is TypeScript; pick auto-evaluator when auto-evaluator is primarily TypeScript; every_eval_ever is Python.

Markdown twin · every_eval_ever alternatives · auto-evaluator alternatives

GraphCanon updated Sep 9, 2026

16views this month

every_eval_ever logo

every_eval_ever

evaleval/every_eval_ever

111pushed Sep 7, 2026
vs
auto-evaluator logo

auto-evaluator

langchain-ai/auto-evaluator

783pushed Jun 26, 2025

Trust & integrity

Signalevery_eval_everauto-evaluator
Maintenance
Very active (1d since push)
As of Sep 9, 2026 · github_public_v1
Archived (438d since push)
As of Sep 8, 2026 · github_public_v1
Provenance
Not a fork · Organization account
As of Sep 9, 2026 · github_public_v1
Not a fork · Organization account
As of Sep 8, 2026 · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of Jul 15, 2026 · osv@v1
No lockfile (source not queried)
As of Jul 11, 2026 · osv@v1
deps.dev advisories
Not queried
deps.dev@v1
Not queried
deps.dev@v1
OpenSSF Scorecard
Not queried
openssf-scorecard@v1
Not queried
openssf-scorecard@v1

Tagline

every_eval_ever
Shared schema and crowdsourced eval database
auto-evaluator
auto-evaluator

Stars

every_eval_ever
111
auto-evaluator
783

Forks

every_eval_ever
49
auto-evaluator
99

Open issues

every_eval_ever
27
auto-evaluator
21

Language

every_eval_ever
Python
auto-evaluator
TypeScript

Adopt for

every_eval_ever
Every Eval Ever is dedicated to providing a standardized metadata framework and a crowdsourced evaluation database for AI results.
auto-evaluator
-

Persona

every_eval_ever
-
auto-evaluator
-

Runtime

every_eval_ever
-
auto-evaluator
-

License

every_eval_ever
MIT
auto-evaluator
Other

Last pushed

every_eval_ever
Sep 7, 2026
auto-evaluator
Jun 26, 2025

Categories

every_eval_ever
Evaluation & Observability
auto-evaluator
Evaluation & Observability

Trust and health

Maintenance

every_eval_ever
Very active (96%)
auto-evaluator
Archived (8%)

Days since push

every_eval_ever
1d
auto-evaluator
438d

Archived on GitHub

every_eval_ever
No
auto-evaluator
Yes

Open issues (now)

every_eval_ever
27
auto-evaluator
21

Stars delta

every_eval_ever
+9 (30d)
auto-evaluator
0 (30d)

Open issues delta

every_eval_ever
+3 (30d)
auto-evaluator
0 (30d)

Full report

every_eval_ever
Trust report
auto-evaluator
Trust report

Choose every_eval_ever if…

  • every_eval_ever is primarily Python; auto-evaluator is TypeScript.
  • License: every_eval_ever is MIT, auto-evaluator is Other.
  • Pricing: Every Eval Ever is open-source under the MIT license, allowing free use and modification. No direct costs are associated with using the schema or contributing to the database..
  • Requirements: Min 2 GB RAM; To utilize all features, you need to install specific converter dependencies via pip..
  • Tags unique to every_eval_ever: agent-evaluation, ai-evaluation, evaluations, infra.
  • Use Every Eval Ever if you need to compare evaluation results from different frameworks in a consistent manner, ensuring results can be easily reproduced or reused as they conform to a defined schema.

When NOT to use every_eval_ever

  • Avoid Every Eval Ever if you require real-time updates on evaluation results, as the database relies on contributions from a community to maintain and update its dataset.
  • If your project needs to integrate evaluation outcomes without an explicit need for extensive metadata validation or standardization, this tool might be less suitable.

Choose auto-evaluator if…

  • auto-evaluator is primarily TypeScript; every_eval_ever is Python.
  • License: auto-evaluator is Other, every_eval_ever is MIT.
  • Tags unique to auto-evaluator: auto-evaluation, railway, typescript, vercel.
  • Use auto-evaluator when you are working with TypeScript and need an integrated solution for evaluating AI models

When NOT to use auto-evaluator

  • Avoid using auto-evaluator if you require a multi-language support environment, as it focuses solely on TypeScript
  • Do not use this tool if your project's hosting requirements do not align with using Vercel or Railway

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: every_eval_ever 111 · auto-evaluator 783 (synced Sep 9, 2026).

Common questions

What is the difference between every_eval_ever and auto-evaluator?
every_eval_ever: Shared schema and crowdsourced eval database. auto-evaluator: auto-evaluator. See the comparison table for live GitHub stats and shared categories.
When should I choose every_eval_ever over auto-evaluator?
Choose every_eval_ever over auto-evaluator when every_eval_ever is primarily Python; auto-evaluator is TypeScript; License: every_eval_ever is MIT, auto-evaluator is Other; Pricing: Every Eval Ever is open-source under the MIT license, allowing free use and modification. No direct costs are associated with using the schema or contributing to the database.; Requirements: Min 2 GB RAM; To utilize all features, you need to install specific converter dependencies via pip.; Tags unique to every_eval_ever: agent-evaluation, ai-evaluation, evaluations, infra; Use Every Eval Ever if you need to compare evaluation results from different frameworks in a consistent manner, ensuring results can be easily reproduced or reused as they conform to a defined schema.
When should I choose auto-evaluator over every_eval_ever?
Choose auto-evaluator over every_eval_ever when auto-evaluator is primarily TypeScript; every_eval_ever is Python; License: auto-evaluator is Other, every_eval_ever is MIT; Tags unique to auto-evaluator: auto-evaluation, railway, typescript, vercel; Use auto-evaluator when you are working with TypeScript and need an integrated solution for evaluating AI models.
When should I avoid every_eval_ever?
Avoid Every Eval Ever if you require real-time updates on evaluation results, as the database relies on contributions from a community to maintain and update its dataset. If your project needs to integrate evaluation outcomes without an explicit need for extensive metadata validation or standardization, this tool might be less suitable.
When should I avoid auto-evaluator?
Avoid using auto-evaluator if you require a multi-language support environment, as it focuses solely on TypeScript Do not use this tool if your project's hosting requirements do not align with using Vercel or Railway
Is every_eval_ever or auto-evaluator more popular on GitHub?
auto-evaluator has more GitHub stars (783 vs 111). Stars measure visibility, not whether either tool fits your constraints.
Are every_eval_ever and auto-evaluator open source?
Yes - both are open-source projects on GitHub (every_eval_ever: MIT, auto-evaluator: Other).
Where can I find alternatives to every_eval_ever or auto-evaluator?
GraphCanon lists graph-backed alternatives at every_eval_ever alternatives and auto-evaluator alternatives (every_eval_ever markdown twin, auto-evaluator markdown twin), ranked by typed relationship edges rather than popularity votes.
Is there a machine-readable version of this comparison?
Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
Which is better maintained, every_eval_ever or auto-evaluator?
every_eval_ever: Very active. auto-evaluator: Archived. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
Where are the full trust reports for every_eval_ever and auto-evaluator?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: every_eval_ever trust report; auto-evaluator trust report.

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