Converters, AI integrations, prompt templates, and training resources
Custom GPT that converts any text — articles, notes, transcripts — into clean CLN format. Paste your content, get structured output.
Claude natively understands CLN when you include the specification in your system prompt or project knowledge. Ideal for summarization and analysis workflows.
Any LLM (GPT-4, Gemini, Mistral, Llama) can output CLN with the right prompt. See prompt templates below.
Copy-paste these prompts into any AI chat to get CLN-formatted output.
System Prompt
You are a structured thinking assistant. Always respond
in CLN (Cognitive Ladder Notation) format:
Header at column 0: SUMMARY: / ANALYSIS: / TASK: / MDA:
Operators at 4-space indent:
= definition/essence . action/step
| resource/tool @ metadata/status
! risk/warning ? unknown/question
* note/context + pro - con
Rules: one fact per line, no filler words, no markdown,
4-space indentation per level, operators aligned.
Prompt
^summarize this in CLN format. Focus on: definitions (=),
key actions (.), risks (!), and open questions (?).
Keep it under 20 lines.
Prompt
^mda this decision at depth 2. Include: first-order
pros/cons, second-order consequences, recommended action
with @owner and @timeline.
Prompt
Structure these meeting notes in CLN. Extract:
= decisions, . action items (with @owner), ! blockers,
? items for next meeting.
The best way to learn CLN is to practice conversion. Here's a progressive training program using the Text-to-CLN Converter GPT.
CLN TASK: CLN Training Program — 4 Weeks . Week 1: Read and Compare . paste 3 articles into Converter GPT daily . compare CLN output to original prose . notice: which information was definition? action? risk? goal: internalize the 9 operator types . Week 2: Edit AI Output . get CLN from Converter GPT . manually refine: fix operator choices, improve hierarchy . add missing risks, questions, metadata goal: develop editorial judgment on structure . Week 3: Write CLN First . read article, then write CLN from memory (no AI) . compare your version to AI-generated version . identify gaps in your structural instinct goal: build structural intuition . Week 4: Real-Time CLN . take meeting notes directly in CLN . structure decisions and analyses live . share CLN artifacts with colleagues goal: CLN becomes your default thinking format + by Week 4, you'll classify information automatically * this is psychotechture in action
Use CLN for code review notes, architecture decisions, and sprint retrospectives directly in your terminal workflow.
Store CLN summaries as .txt files. Grep by operator: grep "^\s*!" *.txt = all risks across all notes.
Use CLN in code blocks inside Notion pages. The monospace formatting preserves alignment and operator visibility.
Chain structured prompts using CLN as I/O format. ^mda, ^summarize, ^risks become executable nodes in analysis workflows.
= definition · . action · ! risk · ? question