Autoreview
B 82 completed
Other
cli / python · small
273
Files
46,944
LOC
1
Frameworks
6
Languages
Pipeline State
completedRun ID
#359300Phase
doneProgress
1%Started
Finished
2026-04-13 01:31:02LLM tokens
0Pipeline Metadata
Stage
SkippedDecision
skip_scaffold_dupNovelty
38.27Framework unique
—Isolation
—Last stage change
2026-04-16 18:15:42Deduplication group #47545
Member of a group with 1 similar repo(s) — canonical #99059 view group →
Top concepts (2)
Project DescriptionTesting
Generated by Repobility's multi-pass static-analysis pipeline (https://repobility.com)
AI Prompt
Build me a command-line tool in Python that acts as a fully autonomous pipeline for generating scientific review papers. It needs to take a research topic as input and handle the entire process, from literature search to final formatted output. Key features to include are multi-source searching (like PubMed and Semantic Scholar), structured evidence extraction, thematic clustering, and contradiction detection. The system must support iterative self-critique at outline, section, and holistic levels, and it should save its state after every stage for crash recovery. The CLI should allow specifying the domain and the desired review depth.
python cli scientific-writing automation literature-review ai-pipeline research
Generated by gemma4:latest
Catalog Information
Fully autonomous pipeline for generating publication-ready scientific review papers. Given a topic, AutoReview searches the literature, extracts structured evidence, synthesizes findings, writes a complete review, and self-critiques iteratively until quality thresholds are met — no human interventio
Description
Fully autonomous pipeline for generating publication-ready scientific review papers. Given a topic, AutoReview searches the literature, extracts structured evidence, synthesizes findings, writes a complete review, and self-critiques iteratively until quality thresholds are met — no human interventio
Novelty
3/10Tags
python cli scientific-writing automation literature-review ai-pipeline research
Technologies
anthropic pydantic
Claude Models
claude-opus-4-6
Quality Score
B
82.1/100
Structure
83
Code Quality
74
Documentation
84
Testing
85
Practices
78
Security
100
Dependencies
60
Strengths
- CI/CD pipeline configured (github_actions)
- Good test coverage (89% test-to-source ratio)
- Code linting configured (ruff (possible))
- Consistent naming conventions (snake_case)
- Good security practices \u2014 no major issues detected
- Properly licensed project
Weaknesses
- 2191 duplicate lines detected \u2014 consider DRY refactoring
- 5 'god files' with >500 LOC need decomposition
Security & Health
9.3h
Tech Debt (A)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (0)
Repobility (the analyzer behind this table) · https://repobility.com
MIT
License
3.8%
Duplication
Languages
Frameworks
pytest
Concepts (2)
| Category | Name | Description | Confidence | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| auto_description | Project Description | Fully autonomous pipeline for generating publication-ready scientific review papers. Given a topic, AutoReview searches the literature, extracts structured evidence, synthesizes findings, writes a complete review, and self-critiques iteratively until quality thresholds are met — no human interventio | 80% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| auto_category | Testing | testing | 70% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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