Status basis: npm_downloads_7d gained 24430 in the last 3d vs 15602 in the 3d before (ratio 1.6x, threshold 1.5x)
- Accelerating npm_downloads_7d gained 24430 in the last 3d vs 15602 in the 3d before (ratio 1.6x, threshold 1.5x)
- Cooling npm_downloads_7d momentum fell to 22738 per 3d from 61325 (<= 40% of the prior window)
- Cooling npm_downloads_7d momentum fell to 15602 per 3d from 88836 (<= 40% of the prior window)
- Cooling npm_downloads_7d momentum fell to 15602 per 3d from 88836 (<= 40% of the prior window)
- Accelerating npm_downloads_7d gained 61325 in the last 3d vs 18768 in the 3d before (ratio 3.3x, threshold 1.5x)
- Anomaly daily change 23516.0 is 3.5 standard deviations from this entity's own prior mean (389.8±6590.2, baseline excludes this point) — unusual, not necessarily adoption
- Accelerating npm_downloads_7d gained 61325 in the last 3d vs 18768 in the 3d before (ratio 3.3x, threshold 1.5x)
- Accelerating npm_downloads_7d gained 40975 in the last 3d vs 1027 in the 3d before (ratio 39.9x, threshold 1.5x)
- Anomaly daily change 22207.0 is 3.7 standard deviations from this entity's own prior mean (32.1±6017.6, baseline excludes this point) — unusual, not necessarily adoption
- Accelerating npm_downloads_7d gained 18768 in the last 3d vs 1027 in the 3d before (ratio 18.3x, threshold 1.5x)
- Anomaly daily change 43113.0 is 18.9 standard deviations from this entity's own prior mean (-685.9±2316.8, baseline excludes this point) — unusual, not necessarily adoption
- Cooling npm_downloads_7d momentum fell to -24345 per 3d from 1027 (<= 40% of the prior window)
- Anomaly daily change -8115.0 is -3.6 standard deviations from this entity's own prior mean (-559.9±2123.0, baseline excludes this point) — unusual, not necessarily adoption
- Accelerating npm_downloads_7d gained 18768 in the last 3d vs 1027 in the 3d before (ratio 18.3x, threshold 1.5x)
- Accelerating npm_downloads_7d gained 1027 in the last 3d after a flat 3d baseline (no prior movement to compare a ratio against)
- Cooling npm_downloads_7d momentum fell to -24345 per 3d from 1027 (<= 40% of the prior window)
- Anomaly daily change -8115.0 is -3.6 standard deviations from this entity's own prior mean (-559.9±2123.0, baseline excludes this point) — unusual, not necessarily adoption
- Cooling npm_downloads_7d momentum fell to 1027 per 3d from 2735 (<= 40% of the prior window)
- Accelerating npm_downloads_7d gained 1027 in the last 3d after a flat 3d baseline (no prior movement to compare a ratio against)
- Cooling npm_downloads_7d momentum fell to 1027 per 3d from 2735 (<= 40% of the prior window)
- Cooling npm_downloads_7d momentum fell to 1027 per 3d from 2735 (<= 40% of the prior window)
- Cooling npm_downloads_7d momentum fell to -6561 per 3d from 1558 (<= 40% of the prior window)
- Cooling npm_downloads_7d momentum fell to -6561 per 3d from 2211 (<= 40% of the prior window)
- Cooling npm_downloads_7d momentum fell to 0 per 3d from 4206 (<= 40% of the prior window)
| Machine-callable | — | unknown | — |
| Open source | 1 | verified | 1 quote(s) |
| Self-hostable | — | unknown | — |
| Bring your own key | — | unknown | — |
| Autonomy level | — | unknown | — |
| Pricing model | — | unknown | — |
| Integrations | — | unknown | — |
“Unknown” means we have not verified it — it is not a “no”. Hard filters never treat unknown as false.
It fills a critical gap in AI agents by adding visual understanding, making it a foundational component for multimodal AI workflows.
Evidence quotesverbatim, from the product’s own materials
“public GitHub repository (README fetched)”— structural
“The FIRST vision plugin for DeepSeek Harness (dsh)”— readme
“one command, `npx -y @deepseek-ai/dsh plugin --profile web add @liustack/[email protected]`”— readme
FAQ
What is modlens?
Modlens is a vision plugin for DeepSeek Harness that turns images like UI screenshots and charts into structured JSON by analyzing text, layout, and meaning.
What does modlens do?
Enable AI coding assistants to interpret image inputs and generate structured code or insights based on visual content.
Why does modlens matter?
It fills a critical gap in AI agents by adding visual understanding, making it a foundational component for multimodal AI workflows.
How much does modlens cost?
Free
Is modlens free?
Yes — modlens has a free tier. Pricing as stated on its own page: Free
Is modlens open source?
Yes — modlens is open source.
How popular is modlens?
As tracked by KanonAgent: 3.0k upvotes (first indexed 2026-08-15).
When did modlens take off?
KanonAgent flagged modlens as breaking out on 2026-08-17 on GitHub (at 462 stars/day that moment). The breakout log is append-only: https://kanonagent.com/rising
What are the best modlens alternatives?
Similar AI agents tracked by KanonAgent: Stealth Venture, archify, open-design, deer-flow, ruflo, career-ops.