Mar 5, 2026 at 7:04 AM 6 signals analysed No manual reviews · fully automatedTrust Signal Breakdown medium 23 sub-signals across 6 dimensions
Vulnerability & Safety ×0.25 4.9 CVEs, dependency health, and supply chain integrity
3 of 3 sub-signals with data
Known CVEs 40% 5.0
No known CVEs
via OSV.dev
Dependency Health 30% 5.0
11 dependencies (minimal)
via npm / PyPI
Supply Chain 30% 4.8
14 transitive CVEs found (penalty: -0.25)
via npm provenance
Operational Reliability ×0.15 4.8 Uptime, latency, error rates, and incident history
4 of 4 sub-signals with data
Uptime 35% 5.0
100.00% over 4 checks
via Health checks
Response Latency 25% 5.0
p99: 194ms, p50: 178ms
via Health checks
Error Rate 20% 5.0
0.00% error rate (0/4)
via Health checks
Incident History 20% 4.0
1 incidents in last 90 days
via Incidents table
Maintenance Activity ×0.15 0.0 Commit recency, release cadence, issue response, CI/CD
0 of 4 sub-signals with data
Commit Recency no data —
Weight redistributed to sub-signals with data
Release Cadence no data —
Weight redistributed to sub-signals with data
Issue Response no data —
Weight redistributed to sub-signals with data
CI/CD Presence no data —
Weight redistributed to sub-signals with data
Adoption ×0.15 2.0 Downloads, stars, dependents, and growth trajectory
2 of 4 sub-signals with data
Download Volume 67% 2.0
195 weekly downloads
via npm / PyPI
GitHub Stars no data —
Weight redistributed to sub-signals with data
Dependent Packages no data —
Weight redistributed to sub-signals with data
Growth Trend 33% 2.0
-14.5% week-over-week
via npm
Transparency ×0.15 0.0 License, documentation, security policy, changelog
0 of 4 sub-signals with data
Open Source no data —
Weight redistributed to sub-signals with data
Documentation no data —
Weight redistributed to sub-signals with data
Security Policy no data —
Weight redistributed to sub-signals with data
Changelog no data —
Weight redistributed to sub-signals with data
Publisher Trust ×0.15 4.3 Track record, org maturity, community standing
4 of 4 sub-signals with data
Track Record 30% 4.0
Internal: 3.0 (22 services), External: 4.0 (4295 followers, 42540 stars)
via Fabric index
Org Maturity 30% 5.0
User account, 13.2 years old
via GitHub
Community Standing 20% 5.0
163 public repositories
via GitHub
Cross-Platform 20% 3.0
Present on 2 platform(s): github, npm
via Registry scan
About this scoreScored across 23 sub-signals in 6 dimensions Scoring engine v1 (beta) — actively being expanded Phase 1: Core sub-signal architecture (live) Phase 2: Permission scope & expanded collection (in progress)
Trust Assessment AI Assessment
dspy.ts is a TypeScript framework published by ruvnet under MIT license, claiming 100% compatibility with the Python DSPy library while adding multi-agent orchestration and self-learning capabilities. The package shows clean vulnerability records and stable operations, but maintenance and transparency scores are zero, indicating minimal documented maintenance activity or governance practices. With only 195 weekly downloads and a single maintainer, the service carries concentration risk typical of early-stage framework projects despite its ambitious feature claims.
Generated by Fabric AI · Mar 4, 2026 at 4:18 AM
Package Availability (30d)
100.00%
p50: 178ms · p99: 194ms
Avg Latency
137ms
averaged across 30d health checks
Weekly Downloads
—
no package registry data
Incidents & Alerts last 90 days
Score History 71 snapshots
Feb 26 Mar 5
Supply Chain & Dependencies trust chain
Showing 6 of 11 dependencies Show more →
Data Sources 6 indexed
◎
OSV.dev CVE database · vulnerability scanning for npm & PyPI packages
◈
GitHub API Commits, issues, releases, repo metadata, transparency checks
⬡
npm Registry Package metadata, weekly downloads, maintainers, dependencies
⬡
PyPI Package metadata, weekly downloads, dependency tree
△
HTTP Health Checks 15-min pings · uptime, latency, status monitoring
◎
PyPI Stats Download statistics and trends
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