Ross ROSS = Recommend OSS · open-source software intelligence for agents

OpenNSWM-Lab/FAROS

A blueprint-driven AutoResearch runtime for orchestrating AI research workflows from idea generation and experiments to paper writing and peer review. observed · 2026-08-28

github.com/OpenNSWM-Lab/FAROS · Python observed · 2026-08-28

Health v2 · maintenance only

58/100

  • Activity 99
  • Release rhythm 35
  • Longevity 8

Flags: no_releases young no_license

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 112
  • days_rel: n/a
  • days_push: 9
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

3001 stars · 350 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

FAROS is a blueprint-driven AutoResearch runtime that orchestrates end-to-end AI research workflows, from idea generation through experiments, paper writing, and peer review. It is built around composable Blueprints, Capabilities, Profiles, and Providers, currently shipping an LLM-domain baseline (FAROS-LLM) with file-backed persistence and venue-aware LaTeX paper generation.

Use cases

  • automate the full research pipeline from idea to paper and review
  • generate academic papers with LaTeX tailored to a venue
  • orchestrate multi-agent LLM research workflows from blueprints
  • run an AI scientist system that proposes and evaluates research ideas
  • automate peer review of generated papers
  • build custom research workflow runtimes with pluggable providers

When to choose

  • you want a configurable, blueprint-based alternative to hardcoded AI-scientist agents
  • you need an end-to-end LLM research pipeline including paper writing and review
  • you want file-backed run, event, and artifact persistence for research runs
  • you are experimenting with automated scientific discovery in the LLM domain

When to avoid

  • you need full DAG scheduling and parallel orchestration, which is not yet included
  • you need a mature cross-domain or non-LLM provider ecosystem
  • you require a polished frontend console or DB-backed runtime metadata
  • you need a permissively licensed project - no license is currently specified

Facets

framework · maturity experimental

agent-framework workflow-automation llm-inference prompt-engineering rag artificial-intelligence large-language-models developer-tools python cross-platform ai-scientist autoresearch research-automation paper-generation multi-agent blueprint-driven scientific-workflow peer-review-automation ai-agents automation nodejs docker

1 source

Member repositories

RepositoryRoleHealth v2
OpenNSWM-Lab/FAROSmain58

For agents

markdown · JSON · MCP: product_card(name="OpenNSWM-Lab/FAROS")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem