backoff-func vs pygments-agentspeak — Trust Score Comparison

Name: backoff-func vs pygments-agentspeak Trust Comparison
Creator: Nerq

Side-by-side trust comparison of backoff-func and pygments-agentspeak. Scores based on security, compliance, maintenance, popularity, and ecosystem signals.

backoff-func scores 57.8/100 (D) while pygments-agentspeak scores 54.0/100 (D) on the Nerq Trust Score. backoff-func leads by 3.8 points. backoff-func is a uncategorized agent with 0 stars. pygments-agentspeak is a uncategorized agent with 0 stars.

backoff — Nerq Trust Score 77.5/100 (B+). pygments — Nerq Trust Score 80.8/100 (A-). pygments leads by 3.3 points.

backoff-func

57.8

Categoryuncategorized

Stars0

Sourcenpm_full

Compliance100

pygments-agentspeak

54.0

Categoryuncategorized

Stars0

Sourcepypi_full

Compliance100

Detailed Score Analysis

Dimension	backoff	pygments
Security	90/100	90/100
Maintenance	87/100	100/100
Popularity	100/100	100/100
Quality	65/100	65/100
Community	35/100	35/100

Five-dimension Nerq trust breakdown (registries: pypi / pypi). Scored equally weighted across security, maintenance, popularity, quality, community.

Detailed Metric Comparison

Metric	backoff-func	pygments-agentspeak
Trust Score	57.8/100	54.0/100
Grade	D	D
Stars	0	0
Category	uncategorized	uncategorized
Security	N/A	N/A
Compliance	100	100
Maintenance	N/A	N/A
Documentation	N/A	N/A
EU AI Act Risk	N/A	N/A
Verified	No	No

Verdict

backoff-func leads with a trust score of 57.8/100 compared to pygments-agentspeak's 54.0/100 (a 3.8-point difference). Both agents should be evaluated based on your specific requirements.

Detailed Analysis

Community & Adoption

backoff-func has 0 GitHub stars while pygments-agentspeak has 0. Both tools have comparable community sizes, suggesting similar levels of ecosystem support and third-party resources.

When to Choose Each Tool

Choose backoff-func if you need:

Higher overall trust score — more reliable for production use

Choose pygments-agentspeak if you need:

Consider if it better fits your specific use case

Switching from backoff-func to pygments-agentspeak (or vice versa)

When migrating between backoff-func and pygments-agentspeak, consider these factors:

API Compatibility: backoff-func (uncategorized) and pygments-agentspeak (uncategorized) share similar interfaces since they are in the same category.
Security Review: Run a security audit after migration. Check the backoff-func safety report and pygments-agentspeak safety report for known issues.
Testing: Ensure your test suite covers all integration points before switching in production.
Community Support: backoff-func has 0 stars and pygments-agentspeak has 0. Larger communities typically mean better Stack Overflow answers and migration guides.

backoff-func Safety Report pygments-agentspeak Safety Report backoff-func Alternatives pygments-agentspeak Alternatives

Frequently Asked Questions

Which is safer, backoff-func or pygments-agentspeak?

Based on Nerq's independent trust assessment, backoff-func has a trust score of 57.8/100 (D) while pygments-agentspeak scores 54.0/100 (D). The 3.8-point difference suggests backoff-func has a stronger trust profile. Trust scores are based on security, compliance, maintenance, documentation, and community adoption.

How do backoff-func and pygments-agentspeak compare on security?

backoff-func has a security score of N/A/100 and pygments-agentspeak scores N/A/100. There is a notable difference in their security assessments. backoff-func's compliance score is 100/100 (EU risk: N/A), while pygments-agentspeak's is 100/100 (EU risk: N/A).

Should I use backoff-func or pygments-agentspeak?

The choice depends on your requirements. backoff-func (uncategorized, 0 stars) and pygments-agentspeak (uncategorized, 0 stars) serve similar use cases. On trust, backoff-func scores 57.8/100 and pygments-agentspeak scores 54.0/100. Review the full KYA reports for each agent before making a decision. Consider factors like integration requirements, documentation quality (N/A vs N/A), and maintenance activity (N/A vs N/A).

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Last updated: 2026-06-02 | Data refreshed weekly
Disclaimer: Nerq trust scores are automated assessments based on publicly available signals. They are not endorsements or guarantees. Always conduct your own due diligence.