# Paitesanshi/LLM-Agent-Survey

Repository: https://github.com/Paitesanshi/LLM-Agent-Survey
Canonical: https://ross.abutalabs.com/products/llm-agent-survey
License Family: other
Last push: 2025-02-20T00:59:30+00:00

## Health v2 (maintenance only)
Score: 31/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 7, release rhythm 35, longevity 80
- inputs: {"age_days": 1126, "days_push": 560, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2911, forks 164 (observed 2026-08-28T04:07:29.233460+00:00)

## What it is
A curated survey repository accompanying the paper 'A Survey on Large Language Model based Autonomous Agents', covering the construction, application, and evaluation of LLM-based autonomous agents. It provides organized references, taxonomies, and continuous updates for researchers in the field.

## Use cases
- find papers on llm-based autonomous agents
- learn how llm agents are constructed and evaluated
- survey of agent memory planning and action modules
- get an overview of llm agent applications in science and engineering
- find references for academic research on ai agents
- understand evaluation methods for llm agents

## When to choose
- you need a comprehensive, well-cited academic overview of LLM-based autonomous agents
- you are starting research on agent architectures like profile, memory, planning, and action modules
- you want a continuously updated reading list of agent papers

## When to avoid
- you need runnable agent framework code rather than a survey of literature
- you want hands-on tutorials or implementation guides
- you need coverage of non-LLM agent systems

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation, agent-framework
- domain: artificial-intelligence, large-language-models, tutorials
- platform: cross-platform
- tags: survey-paper, llm-agents, academic-research, reading-list, ai-agents

## Member repositories
- Paitesanshi/LLM-Agent-Survey (main) score 31

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:29.233460+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T07:34:15.168860+00:00, confidence not recorded.
  - readme: https://github.com/Paitesanshi/LLM-Agent-Survey (fetched 2026-08-28T04:07:29.233460+00:00, sha 958b14c9c47c)
- Data as of 2026-08-30T08:39:29.467469+00:00.