Trust Signal Breakdown high 23 sub-signals across 6 dimensions
Vulnerability & Safety ×0.25 5.0 CVEs, dependency health, and supply chain integrity
1 of 3 sub-signals with data
Known CVEs 100% 5.0
No known CVEs
via OSV.dev
Dependency Health no data —
Weight redistributed to sub-signals with data
Supply Chain no data —
Weight redistributed to sub-signals with data
Operational Reliability ×0.15 5.0 Uptime, latency, error rates, and incident history
4 of 4 sub-signals with data
Uptime 35% 5.0
100.00% over 1 checks
via Health checks
Response Latency 25% 5.0
p99: 185ms, p50: 185ms
via Health checks
Error Rate 20% 5.0
0.00% error rate (0/1)
via Health checks
Incident History 20% 5.0
0 incidents in last 90 days
via Incidents table
Maintenance Activity ×0.15 3.1 Commit recency, release cadence, issue response, CI/CD
3 of 4 sub-signals with data
Commit Recency 37% 5.0
via GitHub
Release Cadence 31% 2.0
via GitHub
Issue Response no data —
Weight redistributed to sub-signals with data
CI/CD Presence 31% 2.0
via GitHub Actions
Adoption ×0.15 1.9 Downloads, stars, dependents, and growth trajectory
3 of 4 sub-signals with data
Download Volume 43% 1.0
11 weekly downloads
via npm / PyPI
GitHub Stars 36% 1.0
70 stars
via GitHub
Dependent Packages no data —
Weight redistributed to sub-signals with data
Growth Trend 21% 5.0
+266.7% week-over-week
via npm
Transparency ×0.15 3.4 License, documentation, security policy, changelog
4 of 4 sub-signals with data
Open Source 30% 5.0
Public repo with OSI-approved license (mit)
via GitHub
Documentation 25% 4.0
Good README (>2000 bytes with examples)
via GitHub
Security Policy 20% 2.0
No SECURITY.md found
via GitHub
Changelog 25% 2.0
No CHANGELOG.md and no releases found
via GitHub
Publisher Trust ×0.15 2.4 Track record, org maturity, community standing
4 of 4 sub-signals with data
Track Record 30% 2.5
Internal: 1.0 (0 services), External: 2.5 (13 followers, 2976 stars)
via Fabric index
Org Maturity 30% 1.5
Organization, 0.1 years old
via GitHub
Community Standing 20% 1.0
2 public repositories
via GitHub
Cross-Platform 20% 5.0
Present on 3 platform(s): github, npm, pypi
via Registry scan
Scored 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
Fractals (MIT license, TinyAGI) is a recursive task orchestrator that decomposes high-level tasks into executable subtasks and runs them in isolated git worktrees using agent swarms. The service shows perfect reliability with no vulnerabilities and 100% uptime, but remains experimental infrastructure with minimal adoption (11 weekly downloads) and a single maintainer. Limited community validation and single-point-of-failure maintenance present notable operational risk for production deployments.
Generated by Fabric AI · Mar 6, 2026 at 2:16 AM
Package Availability (30d)
100.00%
p50: 185ms · p99: 185ms
Avg Latency
185ms
averaged across 30d health checks
Weekly Downloads
11+267%
npm + PyPI weekly
Transparency & Compliance 3/5 passed
Incidents & Alerts last 90 days
Community & Ecosystem adoption signals
11
Weekly Downloads
npm + PyPI
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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