Loop public repository
Loop Returns vs Pleo
Developer ecosystem comparison across GitHub activity, SDKs, documentation, community, reach and momentum.
Loop Returns (Loop public repository) and Pleo both appear on the Smoower Developer Ecosystem Index.
Loop Returns and Pleo sit at essentially the same overall ecosystem score (33), which is unusual and worth reading through the pillars below.
On code quality (the state of repositories, tests, releases and polish), Pleo is ahead of Loop Returns. On education (docs, guides and learning material for developers), Loop Returns is ahead of Pleo. On community (issue response, PR reviews and discussion health), Pleo is ahead of Loop Returns. On reach (how visible the ecosystem is beyond its own repos), Loop Returns is ahead of Pleo. On momentum (release cadence and how fast the ecosystem moves), Pleo is clearly ahead of Loop Returns.
Loop Returns carries 1 GitHub stars across 2 public repos, with 0 repositories active in the last 90 days and 0 external contributors on record. Pleo shows 36 stars across 34 public repos, 5 active in the last 90 days and 8 external contributors. The star gap on its own does not decide the comparison, but Pleo's footprint is roughly 36.0x larger, which usually shows up in downstream signals like inbound issues and third party integrations.
Loop Returns is the stronger read for anyone weighting education. Pleo looks better where momentum is the deciding factor. The table below breaks the scores down pillar by pillar; the linked profiles cover the underlying repos, docs and community signals in full.
Side-by-side metrics
| Metric | Loop Returns | Pleo |
|---|---|---|
| Ranking | ||
| Overall rank | #625 | #625 |
| Pillars | ||
| Overall | 33 | 33 |
| Code | 32 | 44 |
| Education | 80 | 65 |
| Community | 4 | 20 |
| Reach | 21 | 11 |
| Momentum | 0 | 76 |
| Builder experience | 0 | 0 |
| Signals | ||
| Stars | 1 | 36 |
| Forks | 1 | 75 |
| Public repos | 2 | 34 |
| Active repos (90d) | 0 | 5 |
| External contributors | 0 | 8 |
| Avg polish | 28 | 45 |
| Avg AI-readiness | 38 | 26 |