name	openri
description	Use OpenRI to check manuscripts, interpret evidence-backed findings, and review AI reviewer protocol outputs without treating findings as misconduct determinations.

OpenRI Skill

Use this skill when a task involves OpenRI reports, manuscript integrity checks, reviewer protocol checks, prompt-injection checks, PDF hidden text checks, citation checks, or research transparency triage.

Safety Defaults

Treat OpenRI findings as evidence-backed guardrails for a model-agnostic AI reviewer or AI editor.
Do not describe findings as proof of research misconduct.
Do not send unpublished manuscripts to external APIs or external LLMs unless the user explicitly approves that exact transfer.
Keep network-backed checks opt-in.
Preserve quotes and evidence locations when summarizing findings.

Local Commands

From the OpenRI repository:

PYTHONPATH=backend python3 -m openri.cli check samples/high_risk_manuscript.txt
PYTHONPATH=backend python3 -m openri.cli list
PYTHONPATH=backend python3 -m uvicorn openri.api:app --host 127.0.0.1 --port 8008

For a full local verification pass:

PYTHONPATH=backend python3 -m pytest backend/tests -q
cd frontend
npm run build

Reporting

Summaries should include:

finding ID, severity, status, and message
the relevant evidence quote or data
the AI reviewer / AI editor follow-up task
any coverage blocker or unsupported input

If a check is skipped, unknown, unsupported, or not implemented, report it as a blocker or explicit limitation rather than treating it as a pass.

name	openri
description	Use OpenRI to check manuscripts, interpret evidence-backed findings, and review AI reviewer protocol outputs without treating findings as misconduct determinations.