Agentic Research Directory

Framework

e2er (End-to-End Research)

Configurable AI-enabled research infrastructure organizing templates, specialist agents, reusable skills and researcher review pauses, with dossiers for checking study files and replication outputs.

Workflow level n/a Source: Repository-documented Outcome: Not empirically evaluated here

Research applicability

Useful for researchers organizing empirical studies and auditable replication attempts while retaining methodological review.

Getting started

Untested editorial guidance: read setup and backend limitations, install in an isolated environment, run the documented doctor check and begin with a small public-data study with explicit review pauses.

Maintenance

README retrieved on 2026-10-17; future maintenance not verified.

License

Consult repository and each dependency/data licence; no independent legal audit.

Workflow & human oversight

Workflow level left unspecified for this resource-level listing. Researchers choose scope, inspect inputs and methods, and verify generated outputs before reuse.

Workflow level is not an evidence score; higher is not better evidence.

Approach

The reviewed README sections describe adjustable research steps, hash-based file checking and rebuilding tables from saved estimates. A replication template accepts Zenodo packages with R or Python code, executes them in a network-disabled container after plan review, and records numerical comparisons for researcher assessment.

Limitations

Partial README review covering introduction, verification, replication, setup and study/review commands; linked dossiers and remaining documentation were not audited. File integrity is not scientific validity. Author replication examples and backend tests were not independently reproduced. The documented replication path excludes Stata and MATLAB; Windows and the Gemini backend are described as untested.

Reproducibility

Primary README source check only; no installation, execution, security test or performance reproduction.

Adoption requirements

Python 3.11–3.14 and supported AI access through a documented CLI subscription or API provider; supplied literature and data. The replication template also requires Docker. Review provider costs, permissions and data-disclosure risks; backend containment differs.

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