What is kaggle-solutions?

A searchable archive of top solutions from Kaggle competitions. Kaggle is a platform where people compete to build models for data problems; the archive includes solution write-ups, code repositories, notebooks, and an offline copy of selected solution text.

Use it to match a project to past competitions, study winning methods, and create an optimization checklist for validation, models, features, ensembles, or post-processing.

It reduces the time needed to find proven approaches to a similar data or machine-learning problem.

kaggle-solutions — Skill for Claude Code and Codex by zhulei227

Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo

git clone --depth 1 https://github.com/zhulei227/EasyMLOps

agentmods

npx agentmods add skills/zhulei227/easymlops/kaggle_solutions

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/zhulei227/easymlops/kaggle_solutions/github.svg)](https://agentmods.dev/skills/zhulei227/easymlops/kaggle_solutions)

Your own site

<a href="https://agentmods.dev/skills/zhulei227/easymlops/kaggle_solutions"><img src="https://agentmods.dev/badge/skills/zhulei227/easymlops/kaggle_solutions/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/zhulei227/easymlops/kaggle_solutions"><img src="https://agentmods.dev/badge/skills/zhulei227/easymlops/kaggle_solutions.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 105 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 2,063 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00105	$0.02063
Opus 5.5	$0.00042	$0.00825
Sonnet 5.5	$0.00021	$0.00413
Haiku 4.5	$0.00011	$0.00206

Measured 10d ago against content hash f95770099901, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

kaggle-solutions scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/kaggle_solutions/SKILL.md · 145 lines

How it starts

The opening of the file, as written. The whole thing — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Kaggle Solutions

Overview

Query the community-maintained Kaggle solutions archive (https://kaggle.farid.one, source repo faridrashidi/kaggle-solutions), read top solutions fully offline, and automatically match the current business task to similar past competitions to derive optimization recommendations.

Primary Workflow: match current business → optimize

Profile the task and match competitions — run scripts/match_task.py:
- Explicit description: python scripts/match_task.py "churn prediction for telecom users" --metric auc --out report.md
- Auto-profile a project directory (scans code/docs for task terms, metric hints and kaggle.com/c/ slugs): python scripts/match_task.py --dir path/to/project --out report.md The report contains: task profile, ranked similar competitions, techniques mined from offline winner pages (with original quotes), and an actionable optimization checklist (validation / models / features / ensembling / post-processing).
Read the winning approaches — for the top matches use read <number> <rank> (offline) and distill concrete steps into the user's task; cite technique quotes from the report.
Apply and iterate — turn the checklist into concrete changes for the user's pipeline (CV scheme, model choice, features, ensembling, post-processing), highest-frequency winner techniques first.
If the best-matched competitions lack offline pages, run download_solutions.py (see below) and re-run match_task.py.

Semantic search: `scripts/embedding_index.py` (numpy TF-IDF vectors)

Local vector index over both corpora (721 competitions + ~1280 offline winner pages), stored at data/index/tfidf.npz. No model download; queries go through the CN→EN map so Chinese works.

python scripts/embedding_index.py build          # (re)build — run after downloads grow
python scripts/embedding_index.py "churn prediction" --corpus solutions --top 10
python scripts/embedding_index.py "欺诈检测" --corpus competitions --top 5
python scripts/embedding_index.py --status

Read the full file on GitHub · 145 lines

Files

What ships with it

60 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

10d ago First seen · 145 lines · 105 tokens per session scan A f95770099901

Subscribe to this mod's changes

kaggle-solutions is a skill published in the GitHub repository zhulei227/EasyMLOps (23 stars, last pushed 3d ago), licensed Apache-2.0. It adds 105 tokens to every session and 2,063 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-28.

Data and AI Research

kaggle-solutions next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
kaggle-solutionszhulei227/EasyMLOps	Skill	23	3d ago	Apache-2.0	A	105	Claude Code, Codex
agent-platform-model-registrygoogle/skills	Skill	22k	yesterday	Apache-2.0	A	60	Claude Code, Codex
foundry-config-setupmicrosoft/agent-framework	Skill	15k	yesterday	MIT	A	65	Claude Code, Codex
google-cloud-solution-agentic-analytics-spark-knowledge-cataloggoogle/skills	Skill	22k	yesterday	Apache-2.0	A	132	Claude Code, Codex
training-checkwanshuiyin/Auto-claude-code-research-in-sleep	Skill	19k	3d ago	MIT	A	35	Claude Code
nemo-automodel-launcher-configNVIDIA/skills	Skill	3.9k	yesterday	Apache-2.0	A	30	Claude Code
finetuningmicrosoft/skills	Skill	3.2k	yesterday	MIT	A	132	Claude Code