ml-experiment
Skill1 starsChanged 18 days agoMITView on GitHub
Run or report a model experiment with an honest eval. Use for training, fine-tuning, or a dataset gate. Do not invent accuracy.
3 other projects use a version of this.
Adopted by
Most recently taken up by
- gigio1023/agent-skillstheir own version, first seen Oct 13, 2026
- gigio1023/gigio-skillstheir own version, first seen Oct 13, 2026
- Leeroo-AI/supermltheir own version, first seen Mar 15, 2026
Other versions3 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 3
- Leeroo-AI/superml★ 195same name
- gigio1023/agent-skills★ 2same name
- gigio1023/gigio-skills★ 2same 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 repository67 other files it gives its agents.
- AGENTS.mdAGENTS.md
- skills/humanizer/AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- agent-reachSkill
- animateSkill
- backend-architectureSkill
- ci-security-scanning-with-strixSkill
- diagram-generatorSkill
- eas-app-storesSkill
- emil-design-engSkill
- expo-data-fetchingSkill
- expo-dev-clientSkill
- expo-native-uiSkill
- expo-project-structureSkill
- expo-routerSkill
- expo-upgradeSkill
- final-showcaseSkill
- fix-security-vulnerabilities-with-strixSkill
- fresh-context-reviewSkill
- gsap-coreSkill
- gsap-performanceSkill
- gsap-reactSkill
- gsap-scrolltriggerSkill
- gsap-timelineSkill
- hallmarkSkill
- humanizerSkill
- impeccableSkill
- obsidian-markdownSkill
- orchestra-conductorSkill
- orchestra-docsSkill
- orchestra-shipSkill
- orchestra-vaultSkill
- penetration-testing-with-strixSkill
- ponytail-auditSkill
- ponytail-reviewSkill
- ponytailSkill
- postgres-best-practicesSkill
- pretty-mermaidSkill
- prompt-forgeSkill
- r3f-shadersSkill
- react-best-practicesSkill
- reaSkill
- refero-designSkill
- research-paperSkill
- resource-scoutSkill
- review-animationsSkill
- semgrep-adapterSkill
- ship-safeSkill
- skill-security-checkSkill
- stitch::code-to-designSkill
- stitch::extract-design-mdSkill
- stitch::extract-static-htmlSkill
- stitch::generate-designSkill
- stitch::manage-design-systemSkill
- stitch::react-componentsSkill
- stitch::upload-to-stitchSkill
- store-releaseSkill
- supabaseSkill
- systematic-debuggingSkill
- taste-designSkill
- The first 60 shown.
The file
We split this skill into the rules it gives an agent
1 rule. 0 are common, 1 is distinctive, and 0 are very specific to this project.
0
Common
Most of the 3 edited versions we read keep these.
1
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 15
If the number is not in a log, say it was not measured.
“Common” is measured: kept by at least 6 in 10 of the 3 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.
Files
ML experiment
| Rule | Detail |
| Data | Name the dataset and the split before training |
| Eval | Report the metric the split actually produced |
| Repeat | Record seed, command, and commit |
| Soup | Use the fine-tune tool only when the user names it |
If the number is not in a log, say it was not measured.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
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.