The 36 Hottest Open-Source Projects — July 18, 2026

36 open-source projects ranked by daily star velocity. Today's top pick, emilkowalski/skills, gained 2,328 stars to reach 16,918 total.

41
hot products
+2496.0
top stars / day
Expert Analysis
The landscape

The day's list is heavily weighted toward the AI coding-agent ecosystem: at least eight of the 36 entries are skills, plugins, or infrastructure tools designed for platforms like Claude Code, Cursor, and Codex, making that the most visible cluster. A secondary grouping of autonomous trading and investment agents appears across four entries — Vibe-Trading, a polymarket arbitrage bot, a Chinese A-share multi-agent framework, and DojoAgents. Two independent PlayStation 5 emulator projects (sharpemu and KytyPS5) surfaced simultaneously despite no apparent connection, and a 1,324-exercise fitness dataset rounds out an unusually diverse field below the top tier.

The top pick

emilkowalski/skills, described as skills for design engineers, is the day's clear leader: +2,328 stars per day, a 13.76% daily growth rate, and 582 new stars in its measurement window against a base of 16,918 total. Its absolute daily rate is more than twice that of the second-ranked project, making it the fastest-moving entry on the list by a substantial margin. That combination of a high percentage rate and the largest raw delta on the board signals concentrated, rapid new interest rather than momentum carried by an already-massive star count.

Runner-up & trends

Nutlope/hallmark — an anti-AI-slop design skill for Claude Code, Cursor, and Codex — ranks second at +959.6 stars per day and a 7.76% daily growth rate, with 12,369 total stars. OpenCut-app/OpenCut, the open-source CapCut alternative, adds +781.4 stars per day against a large existing base of 75,123, reflecting broad and sustained interest rather than a single spike. JustVugg/colibri, which claims to run the 744B-parameter GLM-5.2 MoE model on a 25GB-RAM consumer machine using pure C with no dependencies, ranks fourth at +480.4 stars per day — notable for addressing a technically specific niche at a 3.04% daily growth rate.

How to choose

Readers primarily interested in AI coding workflows have the deepest selection here: emilkowalski/skills and Nutlope/hallmark lead, but google-labs-code/stitch-skills, MengTo/Skills, tt-a1i/archify, cobusgreyling/loop-engineering, langchain-ai/openwiki, and internet-court/internet-court-skill all address related agent-tooling problems at varying stages of maturity. Those focused on local LLM inference should look at colibri (#4) for its stated ability to stream a 744B model from disk on consumer hardware. Readers following open-source media tools or gaming preservation will find OpenCut and the two independently developed PS5 emulators — sharpemu and KytyPS5 — worth tracking as parallel efforts in their respective domains.

Newly hot projects 1 product

Communication & Collaboration 1 product

Browse team chat platforms, email servers, file-sharing systems, video conferencing tools, and project management software.

Previously hot projects 40 products

Web Development 2 products

Explore frameworks, runtimes, APIs, CMS platforms, GraphQL servers, and frontends used to build modern software for the browser and the web edge.

emilkowalski

skills

  • 18,731Stars
  • 77Hotness
  • 45Reliability
  • 4 monthsAge
  • +2164.6stars / day
  • +12.45%/ day
  • +1,054in 1d
Skills is a curated collection of prompts and instructions that help design engineers use AI coding assistants more effectively. It packages reusable guidance rather than a code library, distinguishing it from typical developer tools. It suits design engineers and frontend developers who want to apply consistent, well-tested practices when working with AI-assisted coding.

Hotness score

Jul 19, 2026

Current77

Previous74

Weekly average

100500
Full metrics details

Derived only from GitHub GraphQL starredAt events after daily star totals are reconciled.

127 observed daily rows. Missing days are not fabricated.

Per-day formula: 0.40 × Hot today + 0.40 × Hot week + 0.20 × Breakout.

  • Same-day multiplier = stars 1d ÷ max(1, stars 7d ÷ 7)
  • Weekly multiplier = stars 7d ÷ max(1, stars 30d ÷ 30 × 7)
  • Fortnight multiplier = stars 14d ÷ max(1, stars 90d ÷ 90 × 14)
  • Hot today = clamp(70 × log-scale(stars 1d, 1000) + 30 × breakout-scale(same-day, 4))
  • Hot week = clamp(75 × log-scale(stars 7d, 5000) + 25 × breakout-scale(weekly, 3))
  • Breakout = clamp(35 × breakout-scale(same-day, 4) + 40 × breakout-scale(weekly, 3) + 25 × breakout-scale(fortnight, 2.5))
DateStarsStars 1dStars 7dStars 14dStars 30dStars 90dSame-day multiplierWeekly multiplierFortnight multiplierHot todayHot weekBreakoutStored score

Reliability score

Jul 19, 2026

Current45

Previous45

Weekly average

100500
Full metrics details

Derived from the displayed continuity, closure, shipping, liveness, and support-burden components.

127 observed daily rows. Missing days are not fabricated.

Per-day formula: 0.30 × Continuity + 0.30 × Closure + 0.20 × Shipping + 0.10 × Liveness + 0.10 × Support burden.

  • Continuity = 35% active ratio 90d + 20% active ratio 30d + 15% PR efficiency 90d + 10% PR efficiency 30d + 10% liveness + 10% observed-history coverage
  • Closure = 55% PR merge efficiency 90d + 45% issue close efficiency 90d
  • Shipping = 100 × (20% × release ratio 30d + 30% × release ratio 90d + 50% × release ratio 180d); ratios are releases ÷ 2, 6, and 12, capped at 1
  • Support burden = 100 − 2 × open issues per 1,000 stars
  • Liveness = 100 × exp(−pushed days ago ÷ 120)

Stars, issues, pull requests, and releases are daily observations. Pushed-days and license are repository snapshot-derived inputs and are not independent historical GitHub events.

DateIssues openedIssues closedPRs openedPRs mergedReleasesStarsOpen issuesPushed days agoContinuityClosureShippingLivenessSupport burdenLicenseObserved daysMissing daysNeeds healingStored score

AI & Machine Learning 16 products

Discover model tooling, training systems, inference runtimes, vector databases, data pipelines, and applied AI software used in production.

Nutlope

hallmark

  • 13,990Stars
  • 87Hotness
  • 40Reliability
  • 3 monthsAge
  • +887.3stars / day
  • +6.94%/ day
  • +849in 1d

Anti-AI-slop design skill for Claude Code, Cursor, and Codex.

Hotness score

Jul 19, 2026

Current87

Previous49

Weekly average

100500
Full metrics details

Derived only from GitHub GraphQL starredAt events after daily star totals are reconciled.

85 observed daily rows. Missing days are not fabricated.

Per-day formula: 0.40 × Hot today + 0.40 × Hot week + 0.20 × Breakout.

  • Same-day multiplier = stars 1d ÷ max(1, stars 7d ÷ 7)
  • Weekly multiplier = stars 7d ÷ max(1, stars 30d ÷ 30 × 7)
  • Fortnight multiplier = stars 14d ÷ max(1, stars 90d ÷ 90 × 14)
  • Hot today = clamp(70 × log-scale(stars 1d, 1000) + 30 × breakout-scale(same-day, 4))
  • Hot week = clamp(75 × log-scale(stars 7d, 5000) + 25 × breakout-scale(weekly, 3))
  • Breakout = clamp(35 × breakout-scale(same-day, 4) + 40 × breakout-scale(weekly, 3) + 25 × breakout-scale(fortnight, 2.5))
DateStarsStars 1dStars 7dStars 14dStars 30dStars 90dSame-day multiplierWeekly multiplierFortnight multiplierHot todayHot weekBreakoutStored score

Reliability score

Jul 19, 2026

Current40

Previous48

Weekly average

100500
Full metrics details

Derived from the displayed continuity, closure, shipping, liveness, and support-burden components.

85 observed daily rows. Missing days are not fabricated.

Per-day formula: 0.30 × Continuity + 0.30 × Closure + 0.20 × Shipping + 0.10 × Liveness + 0.10 × Support burden.

  • Continuity = 35% active ratio 90d + 20% active ratio 30d + 15% PR efficiency 90d + 10% PR efficiency 30d + 10% liveness + 10% observed-history coverage
  • Closure = 55% PR merge efficiency 90d + 45% issue close efficiency 90d
  • Shipping = 100 × (20% × release ratio 30d + 30% × release ratio 90d + 50% × release ratio 180d); ratios are releases ÷ 2, 6, and 12, capped at 1
  • Support burden = 100 − 2 × open issues per 1,000 stars
  • Liveness = 100 × exp(−pushed days ago ÷ 120)

Stars, issues, pull requests, and releases are daily observations. Pushed-days and license are repository snapshot-derived inputs and are not independent historical GitHub events.

DateIssues openedIssues closedPRs openedPRs mergedReleasesStarsOpen issuesPushed days agoContinuityClosureShippingLivenessSupport burdenLicenseObserved daysMissing daysNeeds healingStored score

iOfficeAI

OfficeCLI

  • 20,052Stars
  • 70Hotness
  • 77Reliability
  • 4 monthsAge
  • +504.4stars / day
  • +2.63%/ day
  • +427in 1d

OfficeCLI is the first and best Office suite purpose-built for AI agents to read, edit, and automate Word, Excel, and PowerPoint files. Free, open-source, single binary, no Office installation required.

Hotness score

Jul 19, 2026

Current70

Previous48

Weekly average

100500
Full metrics details

Derived only from GitHub GraphQL starredAt events after daily star totals are reconciled.

128 observed daily rows. Missing days are not fabricated.

Per-day formula: 0.40 × Hot today + 0.40 × Hot week + 0.20 × Breakout.

  • Same-day multiplier = stars 1d ÷ max(1, stars 7d ÷ 7)
  • Weekly multiplier = stars 7d ÷ max(1, stars 30d ÷ 30 × 7)
  • Fortnight multiplier = stars 14d ÷ max(1, stars 90d ÷ 90 × 14)
  • Hot today = clamp(70 × log-scale(stars 1d, 1000) + 30 × breakout-scale(same-day, 4))
  • Hot week = clamp(75 × log-scale(stars 7d, 5000) + 25 × breakout-scale(weekly, 3))
  • Breakout = clamp(35 × breakout-scale(same-day, 4) + 40 × breakout-scale(weekly, 3) + 25 × breakout-scale(fortnight, 2.5))
DateStarsStars 1dStars 7dStars 14dStars 30dStars 90dSame-day multiplierWeekly multiplierFortnight multiplierHot todayHot weekBreakoutStored score

Reliability score

Jul 19, 2026

Current77

Previous80

Weekly average

100500
Full metrics details

Derived from the displayed continuity, closure, shipping, liveness, and support-burden components.

128 observed daily rows. Missing days are not fabricated.

Per-day formula: 0.30 × Continuity + 0.30 × Closure + 0.20 × Shipping + 0.10 × Liveness + 0.10 × Support burden.

  • Continuity = 35% active ratio 90d + 20% active ratio 30d + 15% PR efficiency 90d + 10% PR efficiency 30d + 10% liveness + 10% observed-history coverage
  • Closure = 55% PR merge efficiency 90d + 45% issue close efficiency 90d
  • Shipping = 100 × (20% × release ratio 30d + 30% × release ratio 90d + 50% × release ratio 180d); ratios are releases ÷ 2, 6, and 12, capped at 1
  • Support burden = 100 − 2 × open issues per 1,000 stars
  • Liveness = 100 × exp(−pushed days ago ÷ 120)

Stars, issues, pull requests, and releases are daily observations. Pushed-days and license are repository snapshot-derived inputs and are not independent historical GitHub events.

DateIssues openedIssues closedPRs openedPRs mergedReleasesStarsOpen issuesPushed days agoContinuityClosureShippingLivenessSupport burdenLicenseObserved daysMissing daysNeeds healingStored score

JustVugg

colibri

  • 16,757Stars
  • 80Hotness
  • 59Reliability
  • 21 daysAge
  • +489.5stars / day
  • +3.06%/ day
  • +412in 1d

Run GLM-5.2 (744B MoE) on a 25GB-RAM consumer machine — pure C, zero deps, experts streamed from disk. Tiny engine, immense model. 🐦

Hotness score

Jul 19, 2026

Current80

Previous68

Weekly average

100500
Full metrics details

Derived only from GitHub GraphQL starredAt events after daily star totals are reconciled.

20 observed daily rows. Missing days are not fabricated.

Per-day formula: 0.40 × Hot today + 0.40 × Hot week + 0.20 × Breakout.

  • Same-day multiplier = stars 1d ÷ max(1, stars 7d ÷ 7)
  • Weekly multiplier = stars 7d ÷ max(1, stars 30d ÷ 30 × 7)
  • Fortnight multiplier = stars 14d ÷ max(1, stars 90d ÷ 90 × 14)
  • Hot today = clamp(70 × log-scale(stars 1d, 1000) + 30 × breakout-scale(same-day, 4))
  • Hot week = clamp(75 × log-scale(stars 7d, 5000) + 25 × breakout-scale(weekly, 3))
  • Breakout = clamp(35 × breakout-scale(same-day, 4) + 40 × breakout-scale(weekly, 3) + 25 × breakout-scale(fortnight, 2.5))
DateStarsStars 1dStars 7dStars 14dStars 30dStars 90dSame-day multiplierWeekly multiplierFortnight multiplierHot todayHot weekBreakoutStored score

Reliability score

Jul 19, 2026

Current59

Previous50

Weekly average

100500
Full metrics details

Derived from the displayed continuity, closure, shipping, liveness, and support-burden components.

20 observed daily rows. Missing days are not fabricated.

Per-day formula: 0.30 × Continuity + 0.30 × Closure + 0.20 × Shipping + 0.10 × Liveness + 0.10 × Support burden.

  • Continuity = 35% active ratio 90d + 20% active ratio 30d + 15% PR efficiency 90d + 10% PR efficiency 30d + 10% liveness + 10% observed-history coverage
  • Closure = 55% PR merge efficiency 90d + 45% issue close efficiency 90d
  • Shipping = 100 × (20% × release ratio 30d + 30% × release ratio 90d + 50% × release ratio 180d); ratios are releases ÷ 2, 6, and 12, capped at 1
  • Support burden = 100 − 2 × open issues per 1,000 stars
  • Liveness = 100 × exp(−pushed days ago ÷ 120)

Stars, issues, pull requests, and releases are daily observations. Pushed-days and license are repository snapshot-derived inputs and are not independent historical GitHub events.

DateIssues openedIssues closedPRs openedPRs mergedReleasesStarsOpen issuesPushed days agoContinuityClosureShippingLivenessSupport burdenLicenseObserved daysMissing daysNeeds healingStored score

hasaneyldrm

exercises-dataset

  • 16,205Stars
  • 63Hotness
  • 36Reliability
  • 4 monthsAge
  • +411.9stars / day
  • +2.62%/ day
  • +317in 1d

1,324-exercise fitness dataset — animation GIFs, 180×180 thumbnails, muscle-group & equipment data, and step-by-step instructions in 6 languages. The exercise data layer behind the LogPress app.

Hotness score

Jul 19, 2026

Current63

Previous60

Weekly average

100500
Full metrics details

Derived only from GitHub GraphQL starredAt events after daily star totals are reconciled.

125 observed daily rows. Missing days are not fabricated.

Per-day formula: 0.40 × Hot today + 0.40 × Hot week + 0.20 × Breakout.

  • Same-day multiplier = stars 1d ÷ max(1, stars 7d ÷ 7)
  • Weekly multiplier = stars 7d ÷ max(1, stars 30d ÷ 30 × 7)
  • Fortnight multiplier = stars 14d ÷ max(1, stars 90d ÷ 90 × 14)
  • Hot today = clamp(70 × log-scale(stars 1d, 1000) + 30 × breakout-scale(same-day, 4))
  • Hot week = clamp(75 × log-scale(stars 7d, 5000) + 25 × breakout-scale(weekly, 3))
  • Breakout = clamp(35 × breakout-scale(same-day, 4) + 40 × breakout-scale(weekly, 3) + 25 × breakout-scale(fortnight, 2.5))
DateStarsStars 1dStars 7dStars 14dStars 30dStars 90dSame-day multiplierWeekly multiplierFortnight multiplierHot todayHot weekBreakoutStored score

Reliability score

Jul 19, 2026

Current36

Previous35

Weekly average

100500
Full metrics details

Derived from the displayed continuity, closure, shipping, liveness, and support-burden components.

125 observed daily rows. Missing days are not fabricated.

Per-day formula: 0.30 × Continuity + 0.30 × Closure + 0.20 × Shipping + 0.10 × Liveness + 0.10 × Support burden.

  • Continuity = 35% active ratio 90d + 20% active ratio 30d + 15% PR efficiency 90d + 10% PR efficiency 30d + 10% liveness + 10% observed-history coverage
  • Closure = 55% PR merge efficiency 90d + 45% issue close efficiency 90d
  • Shipping = 100 × (20% × release ratio 30d + 30% × release ratio 90d + 50% × release ratio 180d); ratios are releases ÷ 2, 6, and 12, capped at 1
  • Support burden = 100 − 2 × open issues per 1,000 stars
  • Liveness = 100 × exp(−pushed days ago ÷ 120)

Stars, issues, pull requests, and releases are daily observations. Pushed-days and license are repository snapshot-derived inputs and are not independent historical GitHub events.

DateIssues openedIssues closedPRs openedPRs mergedReleasesStarsOpen issuesPushed days agoContinuityClosureShippingLivenessSupport burdenLicenseObserved daysMissing daysNeeds healingStored score

ogulcancelik

herdr

  • 18,679Stars
  • 72Hotness
  • 79Reliability
  • 4 monthsAge
  • +380.2stars / day
  • +2.12%/ day
  • +320in 1d

agent multiplexer that lives in your terminal.

Hotness score

Jul 19, 2026

Current72

Previous39

Weekly average

100500
Full metrics details

Derived only from GitHub GraphQL starredAt events after daily star totals are reconciled.

116 observed daily rows. Missing days are not fabricated.

Per-day formula: 0.40 × Hot today + 0.40 × Hot week + 0.20 × Breakout.

  • Same-day multiplier = stars 1d ÷ max(1, stars 7d ÷ 7)
  • Weekly multiplier = stars 7d ÷ max(1, stars 30d ÷ 30 × 7)
  • Fortnight multiplier = stars 14d ÷ max(1, stars 90d ÷ 90 × 14)
  • Hot today = clamp(70 × log-scale(stars 1d, 1000) + 30 × breakout-scale(same-day, 4))
  • Hot week = clamp(75 × log-scale(stars 7d, 5000) + 25 × breakout-scale(weekly, 3))
  • Breakout = clamp(35 × breakout-scale(same-day, 4) + 40 × breakout-scale(weekly, 3) + 25 × breakout-scale(fortnight, 2.5))
DateStarsStars 1dStars 7dStars 14dStars 30dStars 90dSame-day multiplierWeekly multiplierFortnight multiplierHot todayHot weekBreakoutStored score

Reliability score

Jul 19, 2026

Current79

Previous79

Weekly average

100500
Full metrics details

Derived from the displayed continuity, closure, shipping, liveness, and support-burden components.

116 observed daily rows. Missing days are not fabricated.

Per-day formula: 0.30 × Continuity + 0.30 × Closure + 0.20 × Shipping + 0.10 × Liveness + 0.10 × Support burden.

  • Continuity = 35% active ratio 90d + 20% active ratio 30d + 15% PR efficiency 90d + 10% PR efficiency 30d + 10% liveness + 10% observed-history coverage
  • Closure = 55% PR merge efficiency 90d + 45% issue close efficiency 90d
  • Shipping = 100 × (20% × release ratio 30d + 30% × release ratio 90d + 50% × release ratio 180d); ratios are releases ÷ 2, 6, and 12, capped at 1
  • Support burden = 100 − 2 × open issues per 1,000 stars
  • Liveness = 100 × exp(−pushed days ago ÷ 120)

Stars, issues, pull requests, and releases are daily observations. Pushed-days and license are repository snapshot-derived inputs and are not independent historical GitHub events.

DateIssues openedIssues closedPRs openedPRs mergedReleasesStarsOpen issuesPushed days agoContinuityClosureShippingLivenessSupport burdenLicenseObserved daysMissing daysNeeds healingStored score

cobusgreyling

loop-engineering

  • 8,782Stars
  • 53Hotness
  • 71Reliability
  • about 1 monthAge
  • +172.4stars / day
  • +2.04%/ day
  • +146in 1d

Practical patterns, starters & CLI tools for loop engineering with AI coding agents. Design systems that prompt and orchestrate agents (inspired by Addy Osmani and Boris Cherny). Includes loop-audit, loop-init, loop-cost.

Hotness score

Jul 19, 2026

Current53

Previous60

Weekly average

100500
Full metrics details

Derived only from GitHub GraphQL starredAt events after daily star totals are reconciled.

42 observed daily rows. Missing days are not fabricated.

Per-day formula: 0.40 × Hot today + 0.40 × Hot week + 0.20 × Breakout.

  • Same-day multiplier = stars 1d ÷ max(1, stars 7d ÷ 7)
  • Weekly multiplier = stars 7d ÷ max(1, stars 30d ÷ 30 × 7)
  • Fortnight multiplier = stars 14d ÷ max(1, stars 90d ÷ 90 × 14)
  • Hot today = clamp(70 × log-scale(stars 1d, 1000) + 30 × breakout-scale(same-day, 4))
  • Hot week = clamp(75 × log-scale(stars 7d, 5000) + 25 × breakout-scale(weekly, 3))
  • Breakout = clamp(35 × breakout-scale(same-day, 4) + 40 × breakout-scale(weekly, 3) + 25 × breakout-scale(fortnight, 2.5))
DateStarsStars 1dStars 7dStars 14dStars 30dStars 90dSame-day multiplierWeekly multiplierFortnight multiplierHot todayHot weekBreakoutStored score

Reliability score

Jul 19, 2026

Current71

Previous68

Weekly average

100500
Full metrics details

Derived from the displayed continuity, closure, shipping, liveness, and support-burden components.

42 observed daily rows. Missing days are not fabricated.

Per-day formula: 0.30 × Continuity + 0.30 × Closure + 0.20 × Shipping + 0.10 × Liveness + 0.10 × Support burden.

  • Continuity = 35% active ratio 90d + 20% active ratio 30d + 15% PR efficiency 90d + 10% PR efficiency 30d + 10% liveness + 10% observed-history coverage
  • Closure = 55% PR merge efficiency 90d + 45% issue close efficiency 90d
  • Shipping = 100 × (20% × release ratio 30d + 30% × release ratio 90d + 50% × release ratio 180d); ratios are releases ÷ 2, 6, and 12, capped at 1
  • Support burden = 100 − 2 × open issues per 1,000 stars
  • Liveness = 100 × exp(−pushed days ago ÷ 120)

Stars, issues, pull requests, and releases are daily observations. Pushed-days and license are repository snapshot-derived inputs and are not independent historical GitHub events.

DateIssues openedIssues closedPRs openedPRs mergedReleasesStarsOpen issuesPushed days agoContinuityClosureShippingLivenessSupport burdenLicenseObserved daysMissing daysNeeds healingStored score

bradautomates

claude-video

  • 9,356Stars
  • 59Hotness
  • 51Reliability
  • 3 monthsAge
  • +155.3stars / day
  • +1.71%/ day
  • +148in 1d

Give Claude the ability to watch any video. /watch downloads, extracts frames, transcribes, hands it all to Claude.

Hotness score

Jul 19, 2026

Current59

Previous81

Weekly average

100500
Full metrics details

Derived only from GitHub GraphQL starredAt events after daily star totals are reconciled.

88 observed daily rows. Missing days are not fabricated.

Per-day formula: 0.40 × Hot today + 0.40 × Hot week + 0.20 × Breakout.

  • Same-day multiplier = stars 1d ÷ max(1, stars 7d ÷ 7)
  • Weekly multiplier = stars 7d ÷ max(1, stars 30d ÷ 30 × 7)
  • Fortnight multiplier = stars 14d ÷ max(1, stars 90d ÷ 90 × 14)
  • Hot today = clamp(70 × log-scale(stars 1d, 1000) + 30 × breakout-scale(same-day, 4))
  • Hot week = clamp(75 × log-scale(stars 7d, 5000) + 25 × breakout-scale(weekly, 3))
  • Breakout = clamp(35 × breakout-scale(same-day, 4) + 40 × breakout-scale(weekly, 3) + 25 × breakout-scale(fortnight, 2.5))
DateStarsStars 1dStars 7dStars 14dStars 30dStars 90dSame-day multiplierWeekly multiplierFortnight multiplierHot todayHot weekBreakoutStored score

Reliability score

Jul 19, 2026

Current51

Previous50

Weekly average

100500
Full metrics details

Derived from the displayed continuity, closure, shipping, liveness, and support-burden components.

88 observed daily rows. Missing days are not fabricated.

Per-day formula: 0.30 × Continuity + 0.30 × Closure + 0.20 × Shipping + 0.10 × Liveness + 0.10 × Support burden.

  • Continuity = 35% active ratio 90d + 20% active ratio 30d + 15% PR efficiency 90d + 10% PR efficiency 30d + 10% liveness + 10% observed-history coverage
  • Closure = 55% PR merge efficiency 90d + 45% issue close efficiency 90d
  • Shipping = 100 × (20% × release ratio 30d + 30% × release ratio 90d + 50% × release ratio 180d); ratios are releases ÷ 2, 6, and 12, capped at 1
  • Support burden = 100 − 2 × open issues per 1,000 stars
  • Liveness = 100 × exp(−pushed days ago ÷ 120)

Stars, issues, pull requests, and releases are daily observations. Pushed-days and license are repository snapshot-derived inputs and are not independent historical GitHub events.

DateIssues openedIssues closedPRs openedPRs mergedReleasesStarsOpen issuesPushed days agoContinuityClosureShippingLivenessSupport burdenLicenseObserved daysMissing daysNeeds healingStored score

Media & Creative Tools 6 products

Organize video, audio, imaging, 3D modeling, CAD, animation, and content-production software used by creators and product teams.

Finance & Business Applications 3 products

Cover ERP, CRM, accounting, blockchain, e-commerce, and business-process software used to run organizations and financial workflows.

HKUDS

Vibe-Trading

  • 25,598Stars
  • 71Hotness
  • 83Reliability
  • 4 monthsAge
  • +375.5stars / day
  • +1.51%/ day
  • +316in 1d

"Vibe-Trading: Your Personal Trading Agent"

Hotness score

Jul 19, 2026

Current71

Previous49

Weekly average

100500
Full metrics details

Derived only from GitHub GraphQL starredAt events after daily star totals are reconciled.

111 observed daily rows. Missing days are not fabricated.

Per-day formula: 0.40 × Hot today + 0.40 × Hot week + 0.20 × Breakout.

  • Same-day multiplier = stars 1d ÷ max(1, stars 7d ÷ 7)
  • Weekly multiplier = stars 7d ÷ max(1, stars 30d ÷ 30 × 7)
  • Fortnight multiplier = stars 14d ÷ max(1, stars 90d ÷ 90 × 14)
  • Hot today = clamp(70 × log-scale(stars 1d, 1000) + 30 × breakout-scale(same-day, 4))
  • Hot week = clamp(75 × log-scale(stars 7d, 5000) + 25 × breakout-scale(weekly, 3))
  • Breakout = clamp(35 × breakout-scale(same-day, 4) + 40 × breakout-scale(weekly, 3) + 25 × breakout-scale(fortnight, 2.5))
DateStarsStars 1dStars 7dStars 14dStars 30dStars 90dSame-day multiplierWeekly multiplierFortnight multiplierHot todayHot weekBreakoutStored score

Reliability score

Jul 19, 2026

Current83

Previous83

Weekly average

100500
Full metrics details

Derived from the displayed continuity, closure, shipping, liveness, and support-burden components.

111 observed daily rows. Missing days are not fabricated.

Per-day formula: 0.30 × Continuity + 0.30 × Closure + 0.20 × Shipping + 0.10 × Liveness + 0.10 × Support burden.

  • Continuity = 35% active ratio 90d + 20% active ratio 30d + 15% PR efficiency 90d + 10% PR efficiency 30d + 10% liveness + 10% observed-history coverage
  • Closure = 55% PR merge efficiency 90d + 45% issue close efficiency 90d
  • Shipping = 100 × (20% × release ratio 30d + 30% × release ratio 90d + 50% × release ratio 180d); ratios are releases ÷ 2, 6, and 12, capped at 1
  • Support burden = 100 − 2 × open issues per 1,000 stars
  • Liveness = 100 × exp(−pushed days ago ÷ 120)

Stars, issues, pull requests, and releases are daily observations. Pushed-days and license are repository snapshot-derived inputs and are not independent historical GitHub events.

DateIssues openedIssues closedPRs openedPRs mergedReleasesStarsOpen issuesPushed days agoContinuityClosureShippingLivenessSupport burdenLicenseObserved daysMissing daysNeeds healingStored score

Operating Systems & System Software 2 products

Catalog OS components, kernels, compilers, bootloaders, virtualization layers, filesystems, and low-level runtime software.

Software Development Tools 3 products

Gather editors, CLIs, build systems, package managers, code quality, documentation generators, and the everyday tools used to ship code.

Hotness score

Jul 19, 2026

Current65

Previous59

Weekly average

100500
Full metrics details

Derived only from GitHub GraphQL starredAt events after daily star totals are reconciled.

97 observed daily rows. Missing days are not fabricated.

Per-day formula: 0.40 × Hot today + 0.40 × Hot week + 0.20 × Breakout.

  • Same-day multiplier = stars 1d ÷ max(1, stars 7d ÷ 7)
  • Weekly multiplier = stars 7d ÷ max(1, stars 30d ÷ 30 × 7)
  • Fortnight multiplier = stars 14d ÷ max(1, stars 90d ÷ 90 × 14)
  • Hot today = clamp(70 × log-scale(stars 1d, 1000) + 30 × breakout-scale(same-day, 4))
  • Hot week = clamp(75 × log-scale(stars 7d, 5000) + 25 × breakout-scale(weekly, 3))
  • Breakout = clamp(35 × breakout-scale(same-day, 4) + 40 × breakout-scale(weekly, 3) + 25 × breakout-scale(fortnight, 2.5))
DateStarsStars 1dStars 7dStars 14dStars 30dStars 90dSame-day multiplierWeekly multiplierFortnight multiplierHot todayHot weekBreakoutStored score

Reliability score

Jul 19, 2026

Current72

Previous69

Weekly average

100500
Full metrics details

Derived from the displayed continuity, closure, shipping, liveness, and support-burden components.

97 observed daily rows. Missing days are not fabricated.

Per-day formula: 0.30 × Continuity + 0.30 × Closure + 0.20 × Shipping + 0.10 × Liveness + 0.10 × Support burden.

  • Continuity = 35% active ratio 90d + 20% active ratio 30d + 15% PR efficiency 90d + 10% PR efficiency 30d + 10% liveness + 10% observed-history coverage
  • Closure = 55% PR merge efficiency 90d + 45% issue close efficiency 90d
  • Shipping = 100 × (20% × release ratio 30d + 30% × release ratio 90d + 50% × release ratio 180d); ratios are releases ÷ 2, 6, and 12, capped at 1
  • Support burden = 100 − 2 × open issues per 1,000 stars
  • Liveness = 100 × exp(−pushed days ago ÷ 120)

Stars, issues, pull requests, and releases are daily observations. Pushed-days and license are repository snapshot-derived inputs and are not independent historical GitHub events.

DateIssues openedIssues closedPRs openedPRs mergedReleasesStarsOpen issuesPushed days agoContinuityClosureShippingLivenessSupport burdenLicenseObserved daysMissing daysNeeds healingStored score

langchain-ai

openwiki

  • 12,594Stars
  • 72Hotness
  • 69Reliability
  • 30 daysAge
  • +160.3stars / day
  • +1.31%/ day
  • +135in 1d

OpenWiki is a CLI that writes and maintains agent documentation for your codebase.

Hotness score

Jul 19, 2026

Current72

Previous79

Weekly average

100500
Full metrics details

Derived only from GitHub GraphQL starredAt events after daily star totals are reconciled.

29 observed daily rows. Missing days are not fabricated.

Per-day formula: 0.40 × Hot today + 0.40 × Hot week + 0.20 × Breakout.

  • Same-day multiplier = stars 1d ÷ max(1, stars 7d ÷ 7)
  • Weekly multiplier = stars 7d ÷ max(1, stars 30d ÷ 30 × 7)
  • Fortnight multiplier = stars 14d ÷ max(1, stars 90d ÷ 90 × 14)
  • Hot today = clamp(70 × log-scale(stars 1d, 1000) + 30 × breakout-scale(same-day, 4))
  • Hot week = clamp(75 × log-scale(stars 7d, 5000) + 25 × breakout-scale(weekly, 3))
  • Breakout = clamp(35 × breakout-scale(same-day, 4) + 40 × breakout-scale(weekly, 3) + 25 × breakout-scale(fortnight, 2.5))
DateStarsStars 1dStars 7dStars 14dStars 30dStars 90dSame-day multiplierWeekly multiplierFortnight multiplierHot todayHot weekBreakoutStored score

Reliability score

Jul 19, 2026

Current69

Previous58

Weekly average

100500
Full metrics details

Derived from the displayed continuity, closure, shipping, liveness, and support-burden components.

29 observed daily rows. Missing days are not fabricated.

Per-day formula: 0.30 × Continuity + 0.30 × Closure + 0.20 × Shipping + 0.10 × Liveness + 0.10 × Support burden.

  • Continuity = 35% active ratio 90d + 20% active ratio 30d + 15% PR efficiency 90d + 10% PR efficiency 30d + 10% liveness + 10% observed-history coverage
  • Closure = 55% PR merge efficiency 90d + 45% issue close efficiency 90d
  • Shipping = 100 × (20% × release ratio 30d + 30% × release ratio 90d + 50% × release ratio 180d); ratios are releases ÷ 2, 6, and 12, capped at 1
  • Support burden = 100 − 2 × open issues per 1,000 stars
  • Liveness = 100 × exp(−pushed days ago ÷ 120)

Stars, issues, pull requests, and releases are daily observations. Pushed-days and license are repository snapshot-derived inputs and are not independent historical GitHub events.

DateIssues openedIssues closedPRs openedPRs mergedReleasesStarsOpen issuesPushed days agoContinuityClosureShippingLivenessSupport burdenLicenseObserved daysMissing daysNeeds healingStored score

Networking & Communications 1 product

Capture servers, proxies, API gateways, service meshes, messaging stacks, email protocols, and realtime communication infrastructure.

Yu9191

wloc

  • 5,825Stars
  • 72Hotness
  • 52Reliability
  • 29 daysAge
  • +172.6stars / day
  • +3.11%/ day
  • +163in 1d

修改 Apple 网络定位(gs-loc)返回坐标 · 支持 Surge / Quantumult X / Loon / Stash · 快捷指令一键设置/恢复定位

Hotness score

Jul 19, 2026

Current72

Previous67

Weekly average

100500
Full metrics details

Derived only from GitHub GraphQL starredAt events after daily star totals are reconciled.

27 observed daily rows. Missing days are not fabricated.

Per-day formula: 0.40 × Hot today + 0.40 × Hot week + 0.20 × Breakout.

  • Same-day multiplier = stars 1d ÷ max(1, stars 7d ÷ 7)
  • Weekly multiplier = stars 7d ÷ max(1, stars 30d ÷ 30 × 7)
  • Fortnight multiplier = stars 14d ÷ max(1, stars 90d ÷ 90 × 14)
  • Hot today = clamp(70 × log-scale(stars 1d, 1000) + 30 × breakout-scale(same-day, 4))
  • Hot week = clamp(75 × log-scale(stars 7d, 5000) + 25 × breakout-scale(weekly, 3))
  • Breakout = clamp(35 × breakout-scale(same-day, 4) + 40 × breakout-scale(weekly, 3) + 25 × breakout-scale(fortnight, 2.5))
DateStarsStars 1dStars 7dStars 14dStars 30dStars 90dSame-day multiplierWeekly multiplierFortnight multiplierHot todayHot weekBreakoutStored score

Reliability score

Jul 19, 2026

Current52

Previous54

Weekly average

100500
Full metrics details

Derived from the displayed continuity, closure, shipping, liveness, and support-burden components.

27 observed daily rows. Missing days are not fabricated.

Per-day formula: 0.30 × Continuity + 0.30 × Closure + 0.20 × Shipping + 0.10 × Liveness + 0.10 × Support burden.

  • Continuity = 35% active ratio 90d + 20% active ratio 30d + 15% PR efficiency 90d + 10% PR efficiency 30d + 10% liveness + 10% observed-history coverage
  • Closure = 55% PR merge efficiency 90d + 45% issue close efficiency 90d
  • Shipping = 100 × (20% × release ratio 30d + 30% × release ratio 90d + 50% × release ratio 180d); ratios are releases ÷ 2, 6, and 12, capped at 1
  • Support burden = 100 − 2 × open issues per 1,000 stars
  • Liveness = 100 × exp(−pushed days ago ÷ 120)

Stars, issues, pull requests, and releases are daily observations. Pushed-days and license are repository snapshot-derived inputs and are not independent historical GitHub events.

DateIssues openedIssues closedPRs openedPRs mergedReleasesStarsOpen issuesPushed days agoContinuityClosureShippingLivenessSupport burdenLicenseObserved daysMissing daysNeeds healingStored score

Databases & Storage 1 product

Organize relational, document, graph, key-value, time-series, and embedded database engines plus replication and migration tooling.

Security & Privacy 1 product

Group authentication, authorization, secrets management, encryption, vulnerability scanning, and application security software.

DevOps & Infrastructure 1 product

Track deployment platforms, CI/CD systems, containers, configuration management, cloud cost tooling, and platform engineering stacks.

More hot products 4 products

safishamsi

graphify

  • 92,079Stars
  • 66Hotness
  • 74Reliability
  • 4 monthsAge
  • +2496.0stars / day
  • +2.75%/ day
  • +624in 1d

AI coding assistant skill (Claude Code, Codex, OpenCode, Cursor, Gemini CLI, and more). Turn any folder of code, SQL schemas, R scripts, shell scripts, docs, papers, images, or videos into a queryable knowledge graph. App code + database schema + infrastructure in one graph.

Hotness score

Jul 19, 2026

Current66

Previous59

Weekly average

100500
Full metrics details

Derived only from GitHub GraphQL starredAt events after daily star totals are reconciled.

109 observed daily rows. Missing days are not fabricated.

Per-day formula: 0.40 × Hot today + 0.40 × Hot week + 0.20 × Breakout.

  • Same-day multiplier = stars 1d ÷ max(1, stars 7d ÷ 7)
  • Weekly multiplier = stars 7d ÷ max(1, stars 30d ÷ 30 × 7)
  • Fortnight multiplier = stars 14d ÷ max(1, stars 90d ÷ 90 × 14)
  • Hot today = clamp(70 × log-scale(stars 1d, 1000) + 30 × breakout-scale(same-day, 4))
  • Hot week = clamp(75 × log-scale(stars 7d, 5000) + 25 × breakout-scale(weekly, 3))
  • Breakout = clamp(35 × breakout-scale(same-day, 4) + 40 × breakout-scale(weekly, 3) + 25 × breakout-scale(fortnight, 2.5))
DateStarsStars 1dStars 7dStars 14dStars 30dStars 90dSame-day multiplierWeekly multiplierFortnight multiplierHot todayHot weekBreakoutStored score

Reliability score

Jul 19, 2026

Current74

Previous74

Weekly average

100500
Full metrics details

Derived from the displayed continuity, closure, shipping, liveness, and support-burden components.

109 observed daily rows. Missing days are not fabricated.

Per-day formula: 0.30 × Continuity + 0.30 × Closure + 0.20 × Shipping + 0.10 × Liveness + 0.10 × Support burden.

  • Continuity = 35% active ratio 90d + 20% active ratio 30d + 15% PR efficiency 90d + 10% PR efficiency 30d + 10% liveness + 10% observed-history coverage
  • Closure = 55% PR merge efficiency 90d + 45% issue close efficiency 90d
  • Shipping = 100 × (20% × release ratio 30d + 30% × release ratio 90d + 50% × release ratio 180d); ratios are releases ÷ 2, 6, and 12, capped at 1
  • Support burden = 100 − 2 × open issues per 1,000 stars
  • Liveness = 100 × exp(−pushed days ago ÷ 120)

Stars, issues, pull requests, and releases are daily observations. Pushed-days and license are repository snapshot-derived inputs and are not independent historical GitHub events.

DateIssues openedIssues closedPRs openedPRs mergedReleasesStarsOpen issuesPushed days agoContinuityClosureShippingLivenessSupport burdenLicenseObserved daysMissing daysNeeds healingStored score

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