balanced-match vs rogue — Trust Score Comparison

Side-by-side trust comparison of balanced-match and rogue. Scores based on security, compliance, maintenance, popularity, and ecosystem signals.

balanced-match scores 61.2/100 (C) while rogue scores 72.6/100 (B) on the Nerq Trust Score. rogue leads by 11.4 points. balanced-match is a uncategorized tool with 0 stars. rogue is a security tool with 1,007 stars, Nerq Verified.

balanced — Nerq Trust Score 60.0/100 (C+). fire — Nerq Trust Score 70.0/100 (B). fire leads by 10.0 points.

61.2
C
Categoryuncategorized
Stars0
Sourcenpm_full
Compliance100
vs
72.6
B verified
Categorysecurity
Stars1,007
Sourcegithub
Security0
Compliance100
Maintenance1
Documentation0

Detailed Score Analysis

Dimensionbalancedfire
Security90/10090/100
Maintenance68/10063/100
Popularity15/10090/100
Quality65/10065/100
Community35/10035/100

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

Detailed Metric Comparison

Metric balanced-match rogue
Trust Score61.2/10072.6/100
GradeCB
Stars01,007
Categoryuncategorizedsecurity
SecurityN/A0
Compliance100100
MaintenanceN/A1
DocumentationN/A0
EU AI Act RiskN/Ahigh
VerifiedNoYes

Verdict

rogue leads with a trust score of 72.6/100 compared to balanced-match's 61.2/100 (a 11.4-point difference). Both agents should be evaluated based on your specific requirements.

Based on our analysis, balanced-match scores higher in Maintenance (68/100) while rogue is stronger in Popularity (90/100).

Detailed Score Analysis

Five-dimensional trust breakdown for balanced-match (pypi) and rogue (pypi) from Nerq’s enrichment pipeline. All 5 dimensions scored on 0–100 scales, refreshed every 7 days, covering 5M+ indexed assets across 14 registries.

Dimensionbalanced-matchrogue
Security90/10090/100
Maintenance68/10063/100
Popularity15/10090/100
Quality65/10065/100
Community35/10035/100

5-Dimension Breakdown

Security — balanced-match vs rogue

Security aggregates dependency vulnerability scans, known CVE exposure, supply-chain hygiene, and adherence to security best practices. On this dimension balanced-match scores 90/100 (top-tier) while rogue scores 90/100 (top-tier). The two are effectively tied on security (both at 90/100). The balanced-match figure is derived from its pypi registry footprint; the rogue figure from pypi. For a pypi/pypi cross-registry pair, a security score above 70 typically reads as production-ready and scores below 50 warrant a second review before adoption. A score above 85 implies a clean dependency tree with 0 critical CVEs in the last 90 days; 70–84 tolerates 1–2 medium-severity issues; below 55 usually flags 3+ unresolved advisories. Given the current 90/100 for balanced-match and 90/100 for rogue, the combined midpoint is 90.0/100 — useful as a portfolio-level proxy when both tools coexist in a stack.

Maintenance — balanced-match vs rogue

Maintenance captures commit cadence, issue turnaround, release frequency, and the health of the project’s active contributor base. On this dimension balanced-match scores 68/100 (mid-band) while rogue scores 63/100 (mid-band). balanced-match leads by 5 points (68/100 vs 63/100), a moderate gap that matters when maintenance is a hard requirement. The balanced-match figure is derived from its pypi registry footprint; the rogue figure from pypi. For a pypi/pypi cross-registry pair, a maintenance score above 70 typically reads as production-ready and scores below 50 warrant a second review before adoption. Scores above 80 correspond to release cadences of 30 days or less and median issue-response times under 7 days; below 50 often means no release in 180+ days. Given the current 68/100 for balanced-match and 63/100 for rogue, the combined midpoint is 65.5/100 — useful as a portfolio-level proxy when both tools coexist in a stack.

Popularity — balanced-match vs rogue

Popularity measures adoption signals—weekly downloads, dependent packages, GitHub stars, and cross-registry citation density. On this dimension balanced-match scores 15/100 (weak) while rogue scores 90/100 (top-tier). rogue leads by 75 points (90/100 vs 15/100), a spread wide enough that teams should weight popularity heavily when choosing. The balanced-match figure is derived from its pypi registry footprint; the rogue figure from pypi. For a pypi/pypi cross-registry pair, a popularity score above 70 typically reads as production-ready and scores below 50 warrant a second review before adoption. A score of 90+ indicates the top 1% of the registry by dependent count or weekly downloads; 70–89 is the top 10%; below 40 suggests fewer than 500 weekly downloads. Given the current 15/100 for balanced-match and 90/100 for rogue, the combined midpoint is 52.5/100 — useful as a portfolio-level proxy when both tools coexist in a stack.

Quality — balanced-match vs rogue

Quality evaluates documentation completeness, test coverage indicators, typed-API availability, and the presence of examples or tutorials. On this dimension balanced-match scores 65/100 (mid-band) while rogue scores 65/100 (mid-band). The two are effectively tied on quality (both at 65/100). The balanced-match figure is derived from its pypi registry footprint; the rogue figure from pypi. For a pypi/pypi cross-registry pair, a quality score above 70 typically reads as production-ready and scores below 50 warrant a second review before adoption. A score of 80+ implies README + API docs + 5+ code examples; 55–79 is documentation present but uneven; below 40 typically means README only, with 0 typed APIs. Given the current 65/100 for balanced-match and 65/100 for rogue, the combined midpoint is 65.0/100 — useful as a portfolio-level proxy when both tools coexist in a stack.

Community — balanced-match vs rogue

Community looks at contributor breadth, issue-response participation, Stack Overflow answer volume, and third-party tutorial ecosystem. On this dimension balanced-match scores 35/100 (weak) while rogue scores 35/100 (weak). The two are effectively tied on community (both at 35/100). The balanced-match figure is derived from its pypi registry footprint; the rogue figure from pypi. For a pypi/pypi cross-registry pair, a community score above 70 typically reads as production-ready and scores below 50 warrant a second review before adoption. Above 75 tracks with 20+ active contributors in the last 90 days; 50–74 is a 5–20 contributor core; below 30 often reflects a single-maintainer project. Given the current 35/100 for balanced-match and 35/100 for rogue, the combined midpoint is 35.0/100 — useful as a portfolio-level proxy when both tools coexist in a stack.

Score-Card Summary

Across the 5 measured dimensions, balanced-match averages 54.6/100 (range 15–90) and rogue averages 68.6/100 (range 35–90). balanced-match leads on 1 dimensions, rogue leads on 1, with 3 tied.

BandRangebalanced-match dimsrogue dims
Top-tier85–10012
Strong70–8500
Mid-band55–7022
Below-avg40–5500
Weak0–4021

Scoring scale: 0–39 weak, 40–54 below-average, 55–69 mid-band, 70–84 strong, 85–100 top-tier. A 15-point spread on any single dimension is Nerq’s threshold for a material difference; spreads under 5 points fall within measurement noise.

Head-to-Head Deltas

Dimensionbalanced-matchrogueDeltaLeader
Security9090+0tied
Maintenance6863+5balanced-match
Popularity1590-75rogue
Quality6565+0tied
Community3535+0tied

Combined 5-dimension average: balanced-match 54.6/100, rogue 68.6/100, overall spread -14.0 points.

Detailed Analysis

Security

Security scores measure dependency vulnerabilities, CVE exposure, and security practices. balanced-match scores N/A and rogue scores 0 on this dimension.

Maintenance & Activity

Activity scores reflect how actively each project is maintained. balanced-match: N/A, rogue: 1.

Documentation

Documentation quality is evaluated based on README, API docs, and example coverage. balanced-match: N/A, rogue: 0.

Community & Adoption

balanced-match has 0 GitHub stars while rogue has 1,007. rogue has significantly broader community adoption, which typically means more Stack Overflow answers, more third-party tutorials, and faster ecosystem development.

When to Choose Each Tool

Choose balanced-match if you need:

  • Consider if it better fits your specific use case

Choose rogue if you need:

  • Higher overall trust score — more reliable for production use
  • More actively maintained with faster release cadence
  • Larger community (1,007 vs 0 stars)

Switching from balanced-match to rogue (or vice versa)

When migrating between balanced-match and rogue, consider these factors:

  1. API Compatibility: balanced-match (uncategorized) and rogue (security) serve different categories, so migration may require significant refactoring.
  2. Security Review: Run a security audit after migration. Check the balanced-match safety report and rogue safety report for known issues.
  3. Testing: Ensure your test suite covers all integration points before switching in production.
  4. Community Support: balanced-match has 0 stars and rogue has 1,007. Larger communities typically mean better Stack Overflow answers and migration guides.
balanced-match Safety Report rogue Safety Report balanced-match Alternatives rogue Alternatives

Related Pages

Frequently Asked Questions

Which is safer, balanced-match or rogue?
Based on Nerq's independent trust assessment, balanced-match has a trust score of 61.2/100 (C) while rogue scores 72.6/100 (B). The 11.4-point difference suggests rogue has a stronger trust profile. Trust scores are based on security, compliance, maintenance, documentation, and community adoption.
How do balanced-match and rogue compare on security?
balanced-match has a security score of N/A/100 and rogue scores 0/100. There is a notable difference in their security assessments. balanced-match's compliance score is 100/100 (EU risk: N/A), while rogue's is 100/100 (EU risk: high).
Should I use balanced-match or rogue?
The choice depends on your requirements. balanced-match (uncategorized, 0 stars) and rogue (security, 1,007 stars) serve different use cases. On trust, balanced-match scores 61.2/100 and rogue scores 72.6/100. Review the full KYA reports for each agent before making a decision. Consider factors like integration requirements, documentation quality (N/A vs 0), and maintenance activity (N/A vs 1).

Related Comparisons

Last updated: 2026-05-06 | 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.

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