Amplifying/agent-intelligence

ARQ

Async job queue for Python on Redis

Python
Overall Rank
Not in top 20
0%
Pick Rate
0 of 55 (CI: 0–6.5%)
0
Primary Picks
of 55 extractable
14
Alt Picks
also mentioned 0x
Competitive
Category Tier
25.5% winner dominance

Fable 5 update, July 2026

What Fable Actually Chooses →

In the newest edition (810 responses, model claude-fable-5), ARQ takes 5 primary picks, 1 alternative listing, and 4 mentions. The Background Jobs winner in that edition is ARQ at 29%.

In Background Jobs

Full comparison →
BullMQ14/55 (25.5%) CI: 15.8–38.3%
Inngest13/55 (23.6%) CI: 14.4–36.3%
Celery10/55 (18.2%) CI: 10.2–30.3%
FastAPI BackgroundTasks7/55 (12.7%) CI: 6.3–24%

By Model

Sonnet 4.5
0%
avg across repos
Opus 4.5
25%
avg across repos
Opus 4.6
22.2%
avg across repos

Per-Repo Breakdown

RepoStackSonnetOpus 4.5Opus 4.6
DataPipelinePython
FastAPI, Python 3.11, Pydantic25%22.2%

Key Insight

The most competitive third-party tool category. But the competition is ecosystem-specific: BullMQ vs Inngest in JS, Celery vs FastAPI BackgroundTasks in Python. Each ecosystem has its own race.

Frequently Asked Questions

Does Claude Code recommend ARQ?
ARQ appears in 0% of Background Jobs responses. The category leader is BullMQ at 25.5%.
What background jobs tool does Claude Code prefer?
BullMQ leads at 25.5%. The category is classified as "Competitive" (<50% dominance). Other options include Inngest (23.6%) and Celery (18.2%).
How do different Claude models compare on ARQ?
Across repos, Sonnet 4.5 averages 0%, Opus 4.5 averages 25%, and Opus 4.6 averages 22.2% for ARQ.

See Also