voyager67/Reasoningai.studio

Turn research questions into defensible findings—with evidence you can trace at every step.
An evidence-first research toolkit for AI agents and human researchers: 64 focused skills, 12 reusable prompts, practical research templates, and local Python utilities for more transparent, reproducible research.
## Research workflows, not generic prompts
ReasoningAI Studio brings research tasks into one coherent, inspectable workflow. Its 64 standalone English-language skills cover the research lifecycle—from framing a question and finding literature to evaluating evidence, designing experiments, auditing machine-learning results, writing a paper, and responding to peer review.
The collection combines 34 ReasoningAI workflows with 30 clearly namespaced ResearchForge Skills, authored by the same project maintainer. All 64 skills are licensed under CC BY 4.0; see NOTICE.md for provenance and the two prompt-file MIT exceptions.
## What's included
64 portable agent skills with defined inputs, task-specific steps, concrete outputs, and research-integrity boundaries.
12 copy-ready English prompts for literature synthesis, paper reading, methods review, claim auditing, reproducibility, statistics, and research communication.
Local Python utilities for scholarly metadata search, DOI lookup, BibTeX checks, screening ledgers, PRISMA-style count summaries, claim-evidence audits, SHA-256 manifests, and common secret-pattern scans.
Research scripts and templates for bibliography verification, dataset auditing, reproducibility preflight, research protocols, evidence matrices, experiment plans, and claim-evidence tracking.
Synthetic examples and automated tests so you can inspect the expected inputs and validate the local tools without using private research data.
Browse the complete skill catalog, architecture, and research ecosystem references.
## Quick start
Requires Python 3.10 or newer. The local utilities use the Python standard library; no runtime third-party packages are required.
bash
python -m pip install .
python -m reasoningai doctor
python -m reasoningai search "retrieval augmented generation" --provider openalex --limit 10
To use a skill, open skills/ /SKILL.md in a compatible AI assistant. Start with the skill catalog and load only the workflow relevant to the task.
## Local research utilities
bash
# Audit a clean illustrative BibTeX file
python -m reasoningai bib-audit examples/references.bib
# Demonstrate duplicate-DOI detection (this fixture is expected to report an issue)
python -m reasoningai bib-audit examples/references-with-duplicates.bib
# Verify DOI metadata against Crossref; --offline prevents network requests
python scripts/verify_bibliography.py examples/researchforge-illustrative-references.bib --offline
# Audit a CSV or JSONL dataset for duplicate rows and exact-text split leakage
python scripts/audit_dataset.py examples/researchforge-synthetic-dataset.csv --text-column text --label-column label --split-column split
# Run a heuristic reproducibility preflight on a project folder
python scripts/check_reproducibility.py .
# Validate all skill files