Individual skill

deeprefine

Agent-native DeepRefine refinement loop — same control flow as DeepRefine.refine(), graphify search instead of FAISS, session LLM, dry-run review before approved graph writes.

deeprefine_skill/SKILL.md

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Last checked: Nov 6, 2026

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Repository stars (not skill ratings): 91
Repository last updated: Aug 23, 2026
License: MIT

Observed agent integration: gemini-cli

agent-skills Repository topic
knowledge-base Repository topic
llm-wiki Repository topic
engineering Derived category

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SKILL.mdcore · 19,251 bytes
SKILL.mdcore · 19,251 bytes
SKILL.mdcore · 19,251 bytes
SKILL.mdcore · 19,251 bytes
SKILL.mdcore · 19,251 bytes
SKILL.mdcore · 19,251 bytes
SKILL.mdcore · 19,251 bytes
SKILL.mdcore · 19,251 bytes
SKILL.mdcore · 19,251 bytes
SKILL.mdcore · 19,251 bytes
SKILL_COPILOT.mddoc · 22,653 bytes
SKILL_OPENCODE.mddoc · 34,198 bytes
__init__.pyruns · 105 bytes
action_review.pyruns · 14,356 bytes
adapter_graphify.pyruns · 6,848 bytes
agent_graph.pyruns · 7,406 bytes
agent_loop.pyruns · 8,809 bytes
agent_prompts.pyruns · 2,995 bytes
cli.pyruns · 49,304 bytes
commands/opencode/deeprefine-apply.mddoc · 1,137 bytes
commands/opencode/deeprefine-review.mddoc · 892 bytes
commands/opencode/deeprefine.mddoc · 757 bytes
gemini_extension/GEMINI.mddoc · 1,641 bytes
gemini_extension/commands/deeprefine.tomlasset · 1,744 bytes
gemini_extension/commands/deeprefine/apply.tomlasset · 1,274 bytes
gemini_extension/commands/deeprefine/review.tomlasset · 1,373 bytes
gemini_extension/gemini-extension.jsonasset · 252 bytes
history.pyruns · 6,298 bytes
installers.pyruns · 23,897 bytes
obsidian_refresh.pyruns · 614 bytes
paths.pyruns · 6,884 bytes
refine_runner.pyruns · 9,424 bytes
wiki_importer.pyruns · 11,859 bytes
wiki_refresh.pyruns · 12,681 bytes
wiki_retrieval.pyruns · 6,513 bytes
wiki_update.pyruns · 15,102 bytes

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# DeepRefine — Agent refinement loop (strict)

## Default safety policy: dry-run only

A normal `/deeprefine` invocation **MUST NEVER** call `deeprefine apply`.

The default `/deeprefine` 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 the user for explicit approval.