undercoveragent vs aiohttp-wsgi — Trust Score Comparison
Side-by-side trust comparison of undercoveragent and aiohttp-wsgi. Scores based on security, compliance, maintenance, popularity, and ecosystem signals.
coverage — Nerq Trust Score 80.8/100 (A-). aiohttp — Nerq Trust Score 80.8/100 (A-). Nearly identical overall trust.
Detailed Score Analysis
| Dimension | coverage | aiohttp |
|---|---|---|
| Security | 90/100 | 90/100 |
| Maintenance | 100/100 | 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 | undercoveragent | aiohttp-wsgi |
|---|---|---|
| Trust Score | 67.4/100 | 62.7/100 |
| Grade | C | C |
| Stars | 0 | 234 |
| Category | marketing | uncategorized |
| Security | 0 | 0 |
| Compliance | 100 | 100 |
| Maintenance | 1 | 0 |
| Documentation | 1 | 0 |
| EU AI Act Risk | minimal | N/A |
| Verified | No | No |
Verdict
undercoveragent leads with a trust score of 67.4/100 compared to aiohttp-wsgi's 62.7/100 (a 4.7-point difference). undercoveragent scores higher on maintenance (1 vs 0). However, aiohttp-wsgi has stronger community adoption (234 vs 0 stars). Both agents should be evaluated based on your specific requirements.
Detailed Score Analysis
Five-dimensional trust breakdown for undercoveragent (pypi) and aiohttp-wsgi (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.
| Dimension | undercoveragent | aiohttp-wsgi |
|---|---|---|
| Security | 90/100 | 90/100 |
| Maintenance | 100/100 | 100/100 |
| Popularity | 100/100 | 100/100 |
| Quality | 65/100 | 65/100 |
| Community | 35/100 | 35/100 |
5-Dimension Breakdown
Security — undercoveragent vs aiohttp-wsgi
Security aggregates dependency vulnerability scans, known CVE exposure, supply-chain hygiene, and adherence to security best practices. On this dimension undercoveragent scores 90/100 (top-tier) while aiohttp-wsgi scores 90/100 (top-tier). The two are effectively tied on security (both at 90/100). The undercoveragent figure is derived from its pypi registry footprint; the aiohttp-wsgi 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 undercoveragent and 90/100 for aiohttp-wsgi, the combined midpoint is 90.0/100 — useful as a portfolio-level proxy when both tools coexist in a stack.
Maintenance — undercoveragent vs aiohttp-wsgi
Maintenance captures commit cadence, issue turnaround, release frequency, and the health of the project’s active contributor base. On this dimension undercoveragent scores 100/100 (top-tier) while aiohttp-wsgi scores 100/100 (top-tier). The two are effectively tied on maintenance (both at 100/100). The undercoveragent figure is derived from its pypi registry footprint; the aiohttp-wsgi 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 100/100 for undercoveragent and 100/100 for aiohttp-wsgi, the combined midpoint is 100.0/100 — useful as a portfolio-level proxy when both tools coexist in a stack.
Popularity — undercoveragent vs aiohttp-wsgi
Popularity measures adoption signals—weekly downloads, dependent packages, GitHub stars, and cross-registry citation density. On this dimension undercoveragent scores 100/100 (top-tier) while aiohttp-wsgi scores 100/100 (top-tier). The two are effectively tied on popularity (both at 100/100). The undercoveragent figure is derived from its pypi registry footprint; the aiohttp-wsgi 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 100/100 for undercoveragent and 100/100 for aiohttp-wsgi, the combined midpoint is 100.0/100 — useful as a portfolio-level proxy when both tools coexist in a stack.
Quality — undercoveragent vs aiohttp-wsgi
Quality evaluates documentation completeness, test coverage indicators, typed-API availability, and the presence of examples or tutorials. On this dimension undercoveragent scores 65/100 (mid-band) while aiohttp-wsgi scores 65/100 (mid-band). The two are effectively tied on quality (both at 65/100). The undercoveragent figure is derived from its pypi registry footprint; the aiohttp-wsgi 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 undercoveragent and 65/100 for aiohttp-wsgi, the combined midpoint is 65.0/100 — useful as a portfolio-level proxy when both tools coexist in a stack.
Community — undercoveragent vs aiohttp-wsgi
Community looks at contributor breadth, issue-response participation, Stack Overflow answer volume, and third-party tutorial ecosystem. On this dimension undercoveragent scores 35/100 (weak) while aiohttp-wsgi scores 35/100 (weak). The two are effectively tied on community (both at 35/100). The undercoveragent figure is derived from its pypi registry footprint; the aiohttp-wsgi 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 undercoveragent and 35/100 for aiohttp-wsgi, 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, undercoveragent averages 78.0/100 (range 35–100) and aiohttp-wsgi averages 78.0/100 (range 35–100). undercoveragent leads on 0 dimensions, aiohttp-wsgi leads on 0, with 5 tied.
| Band | Range | undercoveragent dims | aiohttp-wsgi dims |
|---|---|---|---|
| Top-tier | 85–100 | 3 | 3 |
| Strong | 70–85 | 0 | 0 |
| Mid-band | 55–70 | 1 | 1 |
| Below-avg | 40–55 | 0 | 0 |
| Weak | 0–40 | 1 | 1 |
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
| Dimension | undercoveragent | aiohttp-wsgi | Delta | Leader |
|---|---|---|---|---|
| Security | 90 | 90 | +0 | tied |
| Maintenance | 100 | 100 | +0 | tied |
| Popularity | 100 | 100 | +0 | tied |
| Quality | 65 | 65 | +0 | tied |
| Community | 35 | 35 | +0 | tied |
Combined 5-dimension average: undercoveragent 78.0/100, aiohttp-wsgi 78.0/100, overall spread +0.0 points.
- Max spread: 0 points on Security
- Min spread: 0 points on Security
- Dimensions within 10 points: 5/5
- undercoveragent above 70 on: 3/5 dimensions
- aiohttp-wsgi above 70 on: 3/5 dimensions
Detailed Analysis
Security
undercoveragent leads on security with a score of 0/100 compared to aiohttp-wsgi's 0/100. This score reflects dependency vulnerability analysis, known CVE exposure, and security best practices. A higher security score means fewer known vulnerabilities and better security hygiene in the codebase.
Maintenance & Activity
undercoveragent demonstrates stronger maintenance activity (1/100 vs 0/100). This metric captures commit frequency, issue response times, and release cadence. Actively maintained tools receive faster security patches and are less likely to accumulate technical debt.
Documentation
undercoveragent has better documentation (1/100 vs 0/100). Good documentation reduces onboarding time and helps teams adopt the tool safely. This score evaluates README completeness, API documentation, code examples, and tutorial availability.
Community & Adoption
undercoveragent has 0 GitHub stars while aiohttp-wsgi has 234. aiohttp-wsgi 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 undercoveragent if you need:
- Higher overall trust score — more reliable for production use
- More actively maintained with faster release cadence
- Better documentation for faster onboarding
Choose aiohttp-wsgi if you need:
- Larger community (234 vs 0 stars)
Switching from undercoveragent to aiohttp-wsgi (or vice versa)
When migrating between undercoveragent and aiohttp-wsgi, consider these factors:
- API Compatibility: undercoveragent (marketing) and aiohttp-wsgi (uncategorized) serve different categories, so migration may require significant refactoring.
- Security Review: Run a security audit after migration. Check the undercoveragent safety report and aiohttp-wsgi safety report for known issues.
- Testing: Ensure your test suite covers all integration points before switching in production.
- Community Support: undercoveragent has 0 stars and aiohttp-wsgi has 234. Larger communities typically mean better Stack Overflow answers and migration guides.
Related Pages
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Last updated: 2026-05-31 | 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.