explaining-code
Skill0 starsChanged 5 months agoNo licenceView on GitHub
Use this skill when explaining code, APIs, libraries, frameworks, or technical mechanics — including inline commentary that comes up as part of answering another question. Triggers on phrases like "what does this do", "explain this", "how does X work", "walk me through", and on responses that include commentary on code. The skill has two rules: (1) explanations should be maximally didactic and transparent, assuming novice familiarity with the specific API and naming non-obvious mechanics (iterators vs lists, in-place vs copy, anonymous lambdas filling named slots, hidden defaults, scoping rules, `restrict` semantics, linkage of `inline`, jargon); (2) avoid all-caps words for emphasis in code comments, raw block text, or prose.
8 other projects use a version of this.
Adopted by
Most recently taken up by
- bostonaholic/skillstheir own version, first seen Oct 15, 2026
- kv0906/cc-skillstheir own version, first seen Oct 13, 2026
- bartstc/vite-ts-react-templatetheir own version, first seen Oct 6, 2026
- vigo/claude-skillstheir own version, first seen May 25, 2026
- kamilerman/YetAnotherAgentSkillstheir own version, first seen Apr 29, 2026
- nunomen/claude-skillstheir own version, first seen Mar 18, 2026
Other versions8 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 8
- bartstc/vite-ts-react-template★ 122same name
- kv0906/cc-skills★ 42same name
- GenerativeAgents/training-claude-code★ 4same name
- vigo/claude-skills★ 4same name
- bostonaholic/skills★ 2same name
- nunomen/claude-skills★ 1same name
- r123singh/claude-code-skills★ 1same name
- kamilerman/YetAnotherAgentSkills★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository6 other files it gives its agents.
- camb-devSkill
- cosmolike-devSkill
- cpp-loop-optimizationSkill
- docker-mlSkill
- porting-legacy-physics-codeSkill
- pytorch-teaching-notebook-styleSkill
The file
We split this skill into the rules it gives an agent
1 rule. 0 are common, 0 are distinctive, and 1 is very specific to this project.
0
Common
Most of the 8 edited versions we read keep these.
0
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.
“Common” is measured: kept by at least 6 in 10 of the 8 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
Reviews can't be read right now.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.