How we measure builder mindshare
Smoower scores each company from public signals only, grouped into the two sides of builder mindshare: Foundation — what the company ships (code & polish, education, AI readiness, builder experience) — and Traction — how the ecosystem responds (adoption, community, reach, momentum). Everything here is computed from data anyone can verify.
A note on the word "mindshare": the attention itself lives in people's heads. What we can measure is your public footprint — the signals that attention leaves behind on GitHub, in packages, docs and across the ecosystem. We treat that footprint as a verifiable proxy for mindshare, not the thing itself.
Guides
How it's measured
Foundation
Is it good enough to build on?Repo health, structure, tests/CI and releases — how polished what you ship is.
Docs quality + how AI-ready READMEs are for assistants and new devs.
llms.txt, hosted MCP and AI-docs pages — can AI assistants find and use you.
Samples, templates, fork leverage and downstream usage.
Traction
Is the ecosystem paying attention?Package downloads/velocity, dependents and stars — is the market using it.
External contributors, discussions, sentiment, Discord, programmes.
External mentions (HN/Reddit/Stack Overflow) + dev content + YouTube audience.
Active repos + publishing cadence (trend proxies; full growth coming).
How the overall score works
Each pillar is scored 0–100 from its own sub-metrics, then combined into a single weighted average split evenly across the two tiers — Foundation ≈ 50%, Traction ≈ 50%. Code & Polish and Adoption carry the most weight within their tiers; the rest fill in behind them. Pillars with no signal drop out of the average instead of scoring a zero.
When a signal is missing — no docs URL, no package registry, no Discord — its weight drops out instead of penalizing the org with a zero. We only score what we can see.
Data sources
- • GitHub REST + GraphQL (repos, PRs, contributors, discussions)
- • Firecrawl (docs structure, blog/YouTube content)
- • npm, PyPI, NuGet, RubyGems, Crates, Packagist, Go
- • Reddit + Hacker News search
- • Stack Overflow tag stats
- • Live MCP probes (mcp.<domain>, /mcp, /sse, …)
Refreshed daily. Manually triggered re-analysis is available on each org page.
Limitations
- • Public-data only. Private repos, internal dashboards, and paid-only content are invisible to us.
- • Signal not certainty. A high score reflects strong public artifacts, not whether a program is well-run internally.
- • Not a vendor ranking. We measure DevRel surface area, not product quality.
- • LLM-graded signals (docs grade, sentiment) carry model bias and are sampled rather than exhaustive.