Status basis: npm_downloads_7d gained 637 in the last 3d vs 76 in the 3d before (ratio 8.4x, threshold 1.5x)
- Accelerating npm_downloads_7d gained 637 in the last 3d vs 76 in the 3d before (ratio 8.4x, threshold 1.5x)
- Accelerating npm_downloads_7d gained 76 in the last 3d after a flat 3d baseline (no prior movement to compare a ratio against)
- Cooling npm_downloads_7d momentum fell to 76 per 3d from 467 (<= 40% of the prior window)
- Accelerating npm_downloads_7d gained 76 in the last 3d after a flat 3d baseline (no prior movement to compare a ratio against)
- Cooling npm_downloads_7d momentum fell to 0 per 3d from 467 (<= 40% of the prior window)
- Cooling npm_downloads_7d momentum fell to 0 per 3d from 370 (<= 40% of the prior window)
- Cooling npm_downloads_7d momentum fell to 0 per 3d from 370 (<= 40% of the prior window)
- Accelerating npm_downloads_7d gained 370 in the last 3d after a flat 3d baseline (no prior movement to compare a ratio against)
- Accelerating npm_downloads_7d gained 370 in the last 3d after a flat 3d baseline (no prior movement to compare a ratio against)
- Cooling npm_downloads_7d momentum fell to -69 per 3d from 55 (<= 40% of the prior window)
- Cooling npm_downloads_7d momentum fell to -79 per 3d from 55 (<= 40% of the prior window)
- Cooling npm_downloads_7d momentum fell to -763 per 3d from 83 (<= 40% of the prior window)
- Anomaly daily change -380.0 is -3.3 standard deviations from this entity's own prior mean (19.4±121.1, baseline excludes this point) — unusual, not necessarily adoption
- Cooling npm_downloads_7d momentum fell to -383 per 3d from 480 (<= 40% of the prior window)
- Anomaly daily change -380.0 is -3.3 standard deviations from this entity's own prior mean (19.4±121.1, baseline excludes this point) — unusual, not necessarily adoption
- Cooling npm_downloads_7d momentum fell to -255 per 3d from 839 (<= 40% of the prior window)
- Cooling npm_downloads_7d momentum fell to 83 per 3d from 796 (<= 40% of the prior window)
- Cooling npm_downloads_7d momentum fell to 83 per 3d from 796 (<= 40% of the prior window)
- Accelerating npm_downloads_7d gained 839 in the last 3d vs 337 in the 3d before (ratio 2.5x, threshold 1.5x)
- Accelerating npm_downloads_7d gained 796 in the last 3d vs 166 in the 3d before (ratio 4.8x, threshold 1.5x)
- Anomaly daily change 397.0 is 3.9 standard deviations from this entity's own prior mean (20.2±97.7, baseline excludes this point) — unusual, not necessarily adoption
- Accelerating npm_downloads_7d gained 399 in the last 3d vs 2 in the 3d before (ratio 199.5x, threshold 1.5x)
- Anomaly daily change 397.0 is 3.9 standard deviations from this entity's own prior mean (20.2±97.7, baseline excludes this point) — unusual, not necessarily adoption
- Anomaly daily change 337.0 is 5.9 standard deviations from this entity's own prior mean (-12.6±58.8, baseline excludes this point) — unusual, not necessarily adoption
| Machine-callable | — | unknown | — |
| Open source | 1 | inferred | 1 quote(s) |
| Self-hostable | — | unknown | — |
| Bring your own key | — | unknown | — |
| Autonomy level | 2 | inferred | 1 quote(s) |
| Pricing model | — | unknown | — |
| Integrations | mcp | inferred | 1 quote(s) |
“Unknown” means we have not verified it — it is not a “no”. Hard filters never treat unknown as false.
It tackles the root cause of AI automation failures—UI state hallucination—making desktop bots significantly more trustworthy in real-world use.
Evidence quotesverbatim, from the product’s own materials
“public GitHub repository (README fetched)”— structural
“desktop-automation”— topics
“accessibility,accessibility-api,ai-agents,automation,cli,desktop-automation,macos,mcp,rust”— topics
“native desktop automation CLI designed for AI agents, built with Rust”— readme
FAQ
What is I spent 3 months making desktop automation stop lying to AI agents?
Fixes AI agent failures in desktop automation by giving them accurate access to real UI states instead of misleading abstractions.
What does I spent 3 months making desktop automation stop lying to AI agents do?
Enable AI agents to reliably execute multi-step desktop automation tasks by seeing the actual screen state, not simulated or abstracted representations.
Why does I spent 3 months making desktop automation stop lying to AI agents matter?
It tackles the root cause of AI automation failures—UI state hallucination—making desktop bots significantly more trustworthy in real-world use.
How much does I spent 3 months making desktop automation stop lying to AI agents cost?
Not specified
Is I spent 3 months making desktop automation stop lying to AI agents open source?
Yes — I spent 3 months making desktop automation stop lying to AI agents is open source.
What does I spent 3 months making desktop automation stop lying to AI agents integrate with?
mcp
How popular is I spent 3 months making desktop automation stop lying to AI agents?
As tracked by KanonAgent: 6 upvotes (first indexed 2026-08-15).
What are the best I spent 3 months making desktop automation stop lying to AI agents alternatives?
Similar AI agents tracked by KanonAgent: Stealth Venture, taste-skill, archify, open-design, deer-flow, ruflo.