Methodology
ToolTicker measures publicly observable activity — not revenue, private usage or market share.
01Power Score
Stable DiffusionStability AI
Current #1 · coverage 30+30+20+20
Full coverage — all four components present. Each contribution is the component percentile × its official weight; together with the momentum booster they sum exactly to the Power Score.
The formula is public, the components are named, and the weights were ratified on 2026-08-17 (method prototype-v7): 30% size + 30% growth + 20% mentions + 20% search plus a momentum booster so a genuinely-hot new entrant can rise before it has installed-scale, while an all-round dominant leader keeps the lead. Every score on the site expands to this exact breakdown — click any Power Score on a ranking page.
02Components
Size
30%Current observable adoption
How is this calculated?
The tool's most representative public usage counter — whichever of npm, GitHub, HuggingFace, the VS Code marketplace or Discord best reflects its adoption. The counter actually used and its raw value are recorded per tool, per day (visible on every tool page). A lifetime-only counter that sits beside a flow counter of the same kind is scored on its current flow: the VS Code marketplace publishes only all-time installs, so that counter is scored as its weekly install rate over the trailing 30 days — same window, same unit as the npm weekly downloads it is ranked against.
Growth
30%↗ 30-day velocity
How is this calculated?
The 30-day delta of the size series. Vendors provide history only for npm; for every other tool, growth is bootstrapped from the daily snapshots this site collects — it becomes real for all tools after ~30 days of history.
Mentions
20%◉ public discussion
How is this calculated?
Combined mention signal: Hacker News story mentions (quoted, disambiguated queries) + Reddit post volume over the trailing 14 days, counted per tool in its own subreddit via the Arctic-Shift mirror (native Reddit JSON requires auth; each subreddit verified to exist). X is excluded by owner decision (metered per-result cost). Two discourse surfaces, percentile-ranked together.
Search
20%⌕ search demand
How is this calculated?
90-day mean of the Google Trends interest index (unofficial API; disambiguated per-tool queries). Rate-limit holes are recorded as holes, never filled with zeros.
Momentum booster · method v5
A tool’s Power is its weighted component sum — 30 size + 30 growth + 20 mentions + 20 search, renormalized over the components present — plus a bounded kick proportional to how far its current heat runs ahead of its installed scale:
booster = clamp((momentum − size) × 0.12, 0, 12)
momentum = mean(growth, mentions, search) percentiles · capped at +12
The point: a genuinely-hot new entrant can overtake a big-but-cold incumbent and reach the top before it has installed-scale — a brand-new model blowing up on HN and Google Trends is no longer permanently anchored by its (still-tiny) download count. The kick is capped and fades as the spike normalizes; an all-round dominant leader (hot and big) keeps #1, and a cold incumbent with no momentum gets nothing. This replaced the 2026-08-14 45/25/15/15 freeze.
03Coverage
Full index
- ✓Has observable usage data
- ✓Competes in the global ranking
- ✓Full Power Score (30/30/20/20 + booster)
Twenty of twenty-six tracked tools qualify today.
Watchlist
- ○No public usage counter (verified)
- ○Scored on attention only — 60 search + 40 mentions
- ○Ranked among themselves, never merged into the index
A partial score must not compete with full-signal tools.
Normalization — different counters, comparable percentiles
Raw signal
Percentile (log-scale, one global cohort)
Log-scale percentiles make wildly different counter units (74.4M installs vs 15.1M weekly downloads) comparable before weighting.
Power Score
computed in one global cohort of all 26 tools
Category rank
position among Coding (or Image) tools
Power is global; rank is category-relative. Cross-category Power scores are therefore comparable — today Stable Diffusion (85.8) is more publicly active than Codex (75.9), even though they never share a leaderboard.
04Confidence
Confidence affects how much we trust the score. It does not directly increase the score. It is computed from signal coverage, never assigned; missing signals are holes, never zeros.
05Sources
All sources are free and public. Every snapshot is versioned JSON in git — the index updates from data, not from a dashboard.
06History
Collected 4× daily (00/06/12/18 UTC) · the index is a time series, not a directory
Snapshot #060 · 12 OCT 2026
History building
The shorter windows unlock as history accumulates — the index literally grows more useful every day.
07Limitations
What this index does not measure
It ranks what is publicly observable — downloads, stars, installs, community size, mentions and search interest. It structurally favors tools with open, observable footprints. Nothing here is investment advice, and no vendor was consulted or compensated.
Full disclosure & method notes
Scores are computed from frozen, ratified weights (method prototype-v7); every snapshot is versioned JSON in git; holes are holes. Percentiles run over the log-scale value in one global cohort of all twenty-six tools.
During the shadow-collection phase the index is a preview of the real product: the first weeks of history are what bootstrap growth and longer timeframes. The methodology and weights are public so that the ranking can be audited, argued with, and rebuilt.
Want to argue with the weights? That is a feature, not a bug — adjustable weights are planned on this very page.