deeprefine

DeepRefine - Codex Adapter

This file is the Codex-specific entrypoint. It keeps the platform rules small and loads longer DeepRefine procedure details only when needed:

• Full workflow, queue selection, refinement branch logic, and review rules: references/deeprefine-workflow.md
• Verbatim judgement, abduction, and refinement prompts: references/llm-prompts.md
• Checklist, command sequence, trace schema, paths, and CLI mode: references/trace-and-commands.md

Do not reimplement or shorten the algorithm from memory. Load the relevant reference file before executing that part of the workflow.

Codex Invocation

Trigger this skill when the user:

• explicitly invokes $deeprefine or /deeprefine;
• asks to refine, improve, diagnose, repair, inspect, or review a Graphify knowledge graph;
• asks to apply a previously reviewed DeepRefine refinement.

Run from the knowledge-base project root, where graphify-out/graph.json exists. If the user is planning or asking how DeepRefine works, explain the workflow and do not mutate files.

If deeprefine is unavailable, tell the user to install it:

pip install deeprefine-cli

For source development:

pip install -e /path/to/DeepRefine-Skill

Hard Safety Policy

A normal $deeprefine or /deeprefine invocation is dry-run only and MUST NEVER call deeprefine apply.

The default workflow must stop after:

1. deeprefine loop validate
2. deeprefine review
3. showing the proposed actions and HIGH/MEDIUM/LOW review report to the user

Then ask for explicit approval.

Only if the user's next message explicitly says to approve/apply/write the graph may you run:

deeprefine apply --trace-file ... --refinement-file ...
deeprefine loop finish --trace-file ... --refinement-file ...

Do not treat any of these as approval:

• generation of a <refinement> block;
• a valid loop_trace_<query_id>.json;
• a prior user message;
• a successful deeprefine review.