
Turn any codebase, with its docs, SQL schemas, configs, and PDFs, into a queryable knowledge graph. A /graphify skill for Claude Code, Cursor, Codex, and Gemini CLI: local deterministic AST parsing, every edge explained, no vector store.
WIT gives an agent a set of scientific reasoning functions for moving from vague ideas to testable questions, evidence-led Results, and careful Discussion claims. It is built to extend and audit your thinking, not replace it with a fixed paper outline.
Builders who want their agent to help with research thinking, scientific writing, and claim checking.
You can turn rough research ideas into clearer questions, stronger papers, and more careful judgments.
Turns vague ideas into a testable scientific question space.
Helps organize Results around evidence and restrained interpretation.
Separates local Results-level interpretation from broader Discussion-level interpretation.
Generates competing hypotheses and helps choose the next high-information experiment.
Checks the claim–evidence chain and the paper’s reasoning flow.
Keeps the human involved in the scientific judgments that matter most.
WIT (Writing Is Thinking) is a human–LLM collaborative skill for scientific thinking and writing.
Advance the research. Grow the researcher.
WIT is designed not only to improve scientific work, but also to strengthen the researcher's ability to ask questions, interpret evidence, design experiments, and make scientific judgments.
Automate labor; augment judgment.
WIT uses the LLM to extend, challenge, scaffold, and audit the researcher's thinking—not simply to replace it. Core principle:
WIT specifies scientific reasoning functions, not a rigid surface template for papers.
It helps researchers:
If your agent supports Agent Skills / SKILL.md, install or expose the wit/ directory as the skill package and let the agent load wit/SKILL.md.
Otherwise, ask the AI to read:
wit/references/WIT-Scientific-thinking-and-writing-skill.md
Then invoke it directly:
Use WIT to open up this question: XXX.
This is a finding: XXX. Use WIT to expand it.
Use WIT to review the Results and Discussion.
Use WIT to audit the logical chain of this paper.
Use WIT in human–LLM collaboration mode: help me think, not just finish the task for me.
Audit the reasoning, not the template.
Three ideas summarize WIT:
Writing is thinking.
WIT is a question generator, not a checklist completer.
Advance the research. Grow the researcher.
For details, see WIT-Scientific-thinking-and-writing-skill.md.
中文说明见 README-cn.md.
WIT uses split licensing:
wit/SKILL.md and executable code/scripts — are licensed under the Apache License 2.0 (Apache-2.0).wit/references/, wit/tests/, and wit/case-studies/ — are licensed under the Creative Commons Attribution 4.0 International License (CC-BY-4.0).See LICENSE for the exact scope and attribution guidance. Full license texts are provided in LICENSE-APACHE-2.0 and LICENSE-CC-BY-4.0.
Sign in to join the discussion.
No comments yet. Be the first to say what this is good for.

Turn any codebase, with its docs, SQL schemas, configs, and PDFs, into a queryable knowledge graph. A /graphify skill for Claude Code, Cursor, Codex, and Gemini CLI: local deterministic AST parsing, every edge explained, no vector store.
Topic in, narrated explainer video out. A Claude Code / Codex skill that turns any topic into a black-canvas motion-graphics explainer video with TTS voiceover, subtitles and a chapter progress bar. Chinese or English; every frame drawn in code with Remotion.
Public repository for Agent Skills
Open-source AI job search: scan job portals, evaluate listings into a structured A-H report with a global 1-5 score, tailor your CV, track applications — runs locally in your AI coding CLI (Claude Code, Codex, OpenCode, Antigravity…)
Agent skill for beautiful, verifiable architecture, workflow, sequence, data-flow, and lifecycle diagrams—self-contained HTML with motion and crisp export.
A skill to stop your coding agent from burying the answer. ADHD-friendly output.