| name | ml-llm-wiki |
| description | 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, audit, or critique, use the llm-wiki skill instead. |
Machine Learning Wiki
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 and deeper analysis - ingesting sources, superseding stale knowledge, linting, auditing, critiquing reasoning - 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.
What's inside
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.
How to query
- Read
wiki/index.md - the catalogue, grouped by topic. Start here to find relevant articles.
- Read the articles it points to. Follow body links for related material;
grep -rl "<article>.md" wiki/ lists pages that link to a given article (backlinks).
- If a
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.
- Answer from the wiki's content in preference to general knowledge. Cite articles with markdown links, e.g.
[Attention Efficiency](wiki/machine-learning/attention-efficiency.md).
- If a cited article has
status: stale, say so and point to its replacement. Here, attention-cost.md is stale and superseded by attention-efficiency.md.
- If the wiki has no answer, check
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.
Conventions
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.
Updating
To add a source, change an article, supersede knowledge, lint, audit, or critique, invoke the llm-wiki skill. It is required for all writes and keeps the format consistent. This skill deliberately does not modify the wiki.
Tips
- Use sub-agents with well defined goals, scope and context to parallelise work and reduce context rot in the main conversation.
