Skills/llm-wiki/examples/SKILL.md
Use when answering questions from this machine-learning knowledge base. Triggers: questions about transformers, attention cost and efficiency, and long-context scaling; 'what do we know about attention', 'check the ML wiki'. Read-only querying of compiled knowledge; to add, update, supersede, lint, or audit, use the llm-wiki skill instead.
npx skillsauth add sammcj/agentic-coding ml-llm-wikiInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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A self-contained markdown knowledge base on transformer architectures, attention cost and efficiency, and long-context scaling. This skill is for querying it: the knowledge is already compiled into articles under wiki/, so read those rather than re-deriving from scratch.
Keep this current: as the wiki grows, update the name and description above so they describe what it actually covers and trigger on the right questions.
(Sample note: this example wiki lives in examples/ within the llm-wiki repo. To load it as a skill, place the directory in your skills path named ml-llm-wiki, so the directory matches the name above.)
Maintenance - ingesting sources, superseding stale knowledge, linting, auditing - is not done here. Use the llm-wiki skill, which owns the write workflow and the file format. The llm-wiki skill is required to keep this wiki current; without it the wiki is still readable, but do not hand-edit articles outside the conventions in wiki/README.md.
One topic so far, machine-learning: how attention works, why its memory cost was once thought to be a hard quadratic limit and why that turned out to be an implementation artefact, and what makes long context practical.
wiki/index.md - the catalogue, grouped by topic. Start here to find relevant articles.grep -rl "<article>.md" wiki/ lists pages that link to a given article (backlinks).local/ directory exists, search it too and fold in any relevant personal notes, labelling each hit as local/ (uncommitted) so it is never mistaken for shared, committed knowledge. local/ is the user's own, gitignored and absent from the index.[Attention Efficiency](wiki/machine-learning/attention-efficiency.md).status: stale, say so and point to its replacement. Here, attention-cost.md is stale and superseded by attention-efficiency.md.wiki/gaps.md - the question may already be a tracked gap. Recording a new gap is a write, so it goes through the llm-wiki skill, not here.wiki/README.md explains the format - frontmatter, the raw/wiki split, and supersession-not-deletion - for anyone reading without a skill. Articles carry status: current | stale; stale pages are kept on purpose and point at their replacement.
To add a source, change an article, supersede knowledge, lint, or audit, invoke the llm-wiki skill. It is required for all writes and keeps the format consistent. This skill deliberately does not modify the wiki.
development
Use when building or maintaining a self-contained personal knowledge base (an LLM wiki) as plain markdown, optionally opened as an Obsidian vault. Triggers: ingesting sources into a wiki, querying wiki knowledge, linting wiki health, auditing article claims against their sources, superseding stale knowledge, 'add to wiki', or any mention of 'LLM wiki' or 'Karpathy wiki'.
tools
Provides guidance and tools for hardware design. Activate when using KiCAD, looking up electronic parts or designing PCBs.
testing
Grilling session that challenges your plan against the existing domain model, sharpens terminology, and updates documentation (CONTEXT.md, ADRs) inline as decisions crystallise.
development
any input (code, docs, papers, images, videos) to knowledge graph. Use when user asks any question about a codebase, documents, or project content - especially if graphify-out/ exists, treat the question as a /graphify query.