Agent skill · Code Review & Quality

deeprefine

Claude Code adapter for the DeepRefine agent-native refinement loop. Use when the user invokes /deeprefine, or asks to refine, diagnose, review, or apply changes to a Graphify / LLM-Wiki knowledge graph. Must follow the canonical DeepRefine skill rules and stop for review before graph writes.

HKUST-KnowCompgithub.com/HKUST-KnowCompGitHub ↗
claude-coderead-onlyMIT
Install
npx skills add HKUST-KnowComp/DeepRefine-Skill --skill claude_skill --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 4
SKILL.md size: 6 KB
Bundled scripts: none
Allowed tools: Bash(deeprefine*)ReadGrepGlob
Path: deeprefine_skill/claude_skill/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 89
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# DeepRefine - Claude Code Adapter This file is the Claude Code-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](references/deeprefine-workflow.md) - Verbatim judgement, abduction, and refinement prompts: [references/llm-prompts.md](references/llm-prompts.md) - Checklist, command sequence, trace schema, paths, and CLI mode: [references/trace-and-commands.md](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. ## Claude Code Invocation Trigger this skill when the user: - explicitly invokes `/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 instal

What's inside
Steps it walks through
  1. Claude Code Invocation
  2. Hard Safety Policy
  3. Mode Selection
  4. Full workflow
  5. Review only
  6. Apply only
  7. Non-Negotiable Rules
  8. What to Load From References
Ships with 3 files
  • references/deeprefine-workflow.md
  • references/llm-prompts.md
  • references/trace-and-commands.md
Commands it runs
pip install deeprefine-cli
pip install -e /path/to/DeepRefine-Skill
deeprefine apply --trace-file ... --refinement-file ...
deeprefine loop finish --trace-file ... --refinement-file ...
deeprefine loop validate --trace-file ... --refinement-file ...
deeprefine review --trace-file ... --refinement-file ...
deeprefine apply --allow-low-confidence --trace-file ... --refinement-file ...
More from DeepRefine-Skill
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About this skill
What does the deeprefine skill do?

Claude Code adapter for the DeepRefine agent-native refinement loop. Use when the user invokes /deeprefine, or asks to refine, diagnose, review, or apply changes to a Graphify / LLM-Wiki knowledge graph. Must follow the canonical DeepRefine skill rules and stop for review before graph writes.

How do I install it?

Run `npx skills add HKUST-KnowComp/DeepRefine-Skill --skill claude_skill --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From HKUST-KnowComp/DeepRefine-Skill, a repository with 89 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going