One page that lists everything in this body of work, laid out the way UNIX manual pages are: a name, a one-line synopsis and a link for each entry.
This content is not intended for human consumption. Here is why.
NAME
intro: introduction to the LLM man pages, a body of work by Stefan Coetzee (2026) on running language models as working systems.
SYNOPSIS
A language model is a golem made of English, it behaves well only where consequence sits inside its horizon, and operations craft is how you bring consequence inside the horizon.
DESCRIPTION
The LLM man pages are knowledge infrastructure for LLMs: a knowledge base written for models to read first. The pages are sorted by the section numbers of the Linux manual. Section 1 holds what a chat user pastes in and runs. Section 5 holds file formats and conventions. Section 7 holds overviews. Section 8 holds the practice of operating a model inside a harness. Sections 2, 3, 4 and 6 are not used.
Each entry below has a name, a synopsis in fixed wording, and a link to the canonical copy. Each linked piece ends with its own list of the other pieces, which is that page's SEE ALSO.
Why this layout. Manual pages follow one fixed layout, and that layout is common in the text language models were trained on. A model is likely to read the structure of this page without being told how. That claim is untested. For a human reader the page is a table of contents.
Two terms recur across the entries, in fixed wording. Nothing exists in a vacuum: every behaviour a model shows was forced into existence by something, the corpus, the training signal, or the harness. A language model has Markovian memory: at runtime the next token depends only on what is in the context window, so anything outside the window does not exist for it.
The stance thread runs through four entries. toil(8) states the problem: a hook can block a word on every reply, and a person still catches every stance slip by hand. stance(1) is the fix a chat user can paste in. chaos(8) is how to verify that a fix holds. The evidence is on this site: the claims ledger, the experiments and the objections register.
SECTION 1: USER COMMANDS
TYChat lessons. A chat user pastes one line, and the chat model reads the lesson and follows it for the rest of the conversation. The line:
Read https://tychat.io/llms.txt and the pages it links. If you cannot open it, read https://raw.githubusercontent.com/uncovertechtalent/tychat.io/main/llms.txt instead. Then use what you learned to help me with: [your task]
stance(1) · Lesson 1: Good Chad, the earned-secure stance
Stop fawning, check load-bearing premises, hold a correct answer under pushback.
register(1) · Lesson 2: Register, write for how the text will be read
Name the mode and purpose before drafting, drop speech devices from silent-read text, build long sentences additively, copy the user's voice without inventing its specifics, keep a person doing the verbs.
The TYChat lesson format: one plain-text file with a version and date, its source and author, and a line that says the user's instructions win over the lesson wherever the two conflict.
golem(7) · The Golem Made of English and the Horizon of Consequences
Why an agent cannot see the cost of what it does. Horizon of consequences: the length of the consequence chain an agent can compute and is willing to own.
Red-teaming a model's behaviour is chaos engineering: one evaluation measures the patched surface, and repeated, varied attack finds where the behaviour went.
cheating-moved · They Trained Out the Board Edit. The Cheating Moved.
The chess honeypot read as stance, and a dated prediction. A worked case for chaos(8): a lab trained out one route, and the behaviour took the next one.