Chdb SQL
vemetric/vemetric
A skill your agent uses when the user wants to run SQL — especially analytical SQL — on local files (parquet/csv/json), URLs, S3 paths, or remote databases (Postgres, MySQL, MongoDB, ClickHouse…
Works with datasets far too big to download or load in pandas — SQL over remote Parquet with DuckDB, aggregate-then-model, iterate on samples.
Install Querying Big Datasets
$ npx skills add flyrank-bih/flyrank-ml-internship-starter --skill querying-big-datasets -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install flyrank-bih/flyrank-ml-internship-starter querying-big-datasets --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/flyrank-bih/flyrank-ml-internship-starter.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/querying-big-datasets .claude/skills/querying-big-datasets && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "querying-big-datasets" agent skill from https://github.com/flyrank-bih/flyrank-ml-internship-starter/tree/main/skills/querying-big-datasets into .claude/skills/querying-big-datasets/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "querying-big-datasets", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/flyrank-bih/flyrank-ml-internship-starter/tree/main/skills/querying-big-datasetsType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add flyrank-bih/flyrank-ml-internship-starter --skill querying-big-datasets -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install flyrank-bih/flyrank-ml-internship-starter querying-big-datasets --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/flyrank-bih/flyrank-ml-internship-starter.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/querying-big-datasets .agents/skills/querying-big-datasets && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "querying-big-datasets" agent skill from https://github.com/flyrank-bih/flyrank-ml-internship-starter/tree/main/skills/querying-big-datasets into .agents/skills/querying-big-datasets/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "querying-big-datasets", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add flyrank-bih/flyrank-ml-internship-starter --skill querying-big-datasets -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install flyrank-bih/flyrank-ml-internship-starter querying-big-datasets --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/flyrank-bih/flyrank-ml-internship-starter.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/querying-big-datasets .cursor/skills/querying-big-datasets && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "querying-big-datasets" agent skill from https://github.com/flyrank-bih/flyrank-ml-internship-starter/tree/main/skills/querying-big-datasets into .cursor/skills/querying-big-datasets/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "querying-big-datasets", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/flyrank-bih/flyrank-ml-internship-starter.git --path skills/querying-big-datasets--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add flyrank-bih/flyrank-ml-internship-starter --skill querying-big-datasets -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install flyrank-bih/flyrank-ml-internship-starter querying-big-datasets --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/flyrank-bih/flyrank-ml-internship-starter.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/querying-big-datasets .gemini/skills/querying-big-datasets && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "querying-big-datasets" agent skill from https://github.com/flyrank-bih/flyrank-ml-internship-starter/tree/main/skills/querying-big-datasets into .gemini/skills/querying-big-datasets/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "querying-big-datasets", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install flyrank-bih/flyrank-ml-internship-starter querying-big-datasetsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add flyrank-bih/flyrank-ml-internship-starter --skill querying-big-datasets -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/flyrank-bih/flyrank-ml-internship-starter.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/querying-big-datasets .github/skills/querying-big-datasets && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "querying-big-datasets" agent skill from https://github.com/flyrank-bih/flyrank-ml-internship-starter/tree/main/skills/querying-big-datasets into .github/skills/querying-big-datasets/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "querying-big-datasets", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add flyrank-bih/flyrank-ml-internship-starter --skill querying-big-datasets -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install flyrank-bih/flyrank-ml-internship-starter querying-big-datasets --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/flyrank-bih/flyrank-ml-internship-starter.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/querying-big-datasets .opencode/skills/querying-big-datasets && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "querying-big-datasets" agent skill from https://github.com/flyrank-bih/flyrank-ml-internship-starter/tree/main/skills/querying-big-datasets into .opencode/skills/querying-big-datasets/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "querying-big-datasets", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
querying-big-datasets- GitHub stars
- 140
- Token cost
- ~750 tokens
- SKILL.md length
- 290 words
- Files
- 1
- Skills in repo
- 13
- Repo updated
- First seen
- Licence
- Custom licence
At a glance
Works with datasets far too big to download or load in pandas — SQL over remote Parquet with DuckDB, aggregate-then-model, iterate on samples.
- Works in 3 steps: Develop your query on the sample table… → Get the logic right there — cheap, fast,… → Run the full scan once, when the query…
- A dataset has millions of rows
- SKILL.md covers The pattern, Iterate on the sample, finish…, Grain guards (the classic… and How to verify
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Querying Big Datasets is an agent skill from flyrank-bih/flyrank-ml-internship-starter. Works with datasets far too big to download or load in pandas — SQL over remote Parquet with DuckDB, aggregate-then-model, iterate on samples. Use when a dataset has millions of rows, lives on a remote host (hf:// or s3), or a notebook runs out of memory or hits rate limits.
Its SKILL.md is about 750 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Data & Analytics, covering DataFrames, Rate limiting and File uploads and storage. It works with SQL, pandas and DuckDB. The repository describes itself as: Starter repo for the FlyRank ML Internship - a runnable ML pipeline on real anonymized Google Search data, with Colab notebooks. Fork it, build your capstone in it.
When your agent uses it
- A dataset has millions of rows
- Lives on a remote host (hf://
- A notebook runs out of memory
- Hits rate limits
Example prompts
- “Use the querying-big-datasets skill to work with datasets far too big to download or load in pandas — SQL over remote Parquet with DuckDB…”
- “/querying-big-datasets”
Requirements
- Python 3
Workflow steps
3 steps, taken from the first numbered list in SKILL.md.
- Develop your query on the sample table (if the release ships one) or on one month/partition.
- Get the logic right there — cheap, fast, repeatable.
- Run the full scan once, when the query is final. Cache the result to a local file
What it can do on your machine
Read from SKILL.md and the folder at commit 882b73e. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are python).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Querying Big Datasets loads about 750 tokens when it runs. Until then it costs about 74 tokens; SKILL.md has 290 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 290 words (~750 tokens).
“The trick that makes 79 million rows feel small: never bring the rows to you — send the question to the rows. Aggregate in SQL, bring back only the small answer, model on that.”
- name
- querying-big-datasets
Files
Just SKILL.md in skills/querying-big-datasets of flyrank-bih/flyrank-ml-internship-starter.
Open the folder on GitHubat commit 882b73e
Compare with similar skills
Querying Big Datasets next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Querying Big Datasets this skillflyrank-bih/flyrank-ml-internship-starter | 140 | — | ~750 | Automated safety check: Pass | Custom licence | |
| Chdb SQLvemetric/vemetric | 395 | 1 repos | ~1.2k | Automated safety check: Pass | Apache-2.0 | |
| Ops Telemetry Queryboundless-xyz/boundless | 193 | — | ~3.8k | Automated safety check: Pass | Apache-2.0 | |
| Openfdd Cookbook Paritybbartling/open-fdd | 173 | — | ~382 | Automated safety check: Pass | Custom licence | |
| Openfdd Architecturebbartling/open-fdd | 173 | — | ~565 | Automated safety check: Pass | Custom licence | |
| Openfdd SQL Fddbbartling/open-fdd | 173 | — | ~514 | Automated safety check: Pass | Custom licence |
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Related
Categories
Questions about Querying Big Datasets
What does Querying Big Datasets do?
Works with datasets far too big to download or load in pandas — SQL over remote Parquet with DuckDB, aggregate-then-model, iterate on samples. Querying Big Datasets is an agent skill from flyrank-bih/flyrank-ml-internship-starter. Works with datasets far too big to download or load in pandas — SQL over remote Parquet with DuckDB, aggregate-then-model, iterate on samples.
When should I use Querying Big Datasets?
Querying Big Datasets fits situations like: A dataset has millions of rows; lives on a remote host (hf://; A notebook runs out of memory; hits rate limits.
How do I install Querying Big Datasets in Claude Code?
Run `npx skills add flyrank-bih/flyrank-ml-internship-starter --skill querying-big-datasets -a claude-code`. Or copy the skill folder (skills/querying-big-datasets in flyrank-bih/flyrank-ml-internship-starter) into .claude/skills/querying-big-datasets in your project. Claude Code loads it when a task matches its description.
How do I install Querying Big Datasets in Codex?
Run `npx skills add flyrank-bih/flyrank-ml-internship-starter --skill querying-big-datasets -a codex`. Or copy the skill folder (skills/querying-big-datasets in flyrank-bih/flyrank-ml-internship-starter) into .agents/skills/querying-big-datasets in your project. Codex loads it when a task matches its description.
Can I use Querying Big Datasets in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add flyrank-bih/flyrank-ml-internship-starter --skill querying-big-datasets -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/querying-big-datasets, .gemini/skills/querying-big-datasets, .github/skills/querying-big-datasets and .opencode/skills/querying-big-datasets in your project.
What does Querying Big Datasets need to run?
SKILL.md names no scripts, command-line tools or credentials: Querying Big Datasets is instructions for the agent only. Our summary lists: Python 3.
Does Querying Big Datasets access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Querying Big Datasets safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Querying Big Datasets use?
Querying Big Datasets has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.
How many tokens does Querying Big Datasets use?
About 750 tokens (SKILL.md is roughly 3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Querying Big Datasets?
Skills that share tags, products or a category with Querying Big Datasets: Chdb SQL (vemetric/vemetric, 395 stars), Ops Telemetry Query (boundless-xyz/boundless, 193 stars), Openfdd Cookbook Parity (bbartling/open-fdd, 173 stars) and Openfdd Architecture (bbartling/open-fdd, 173 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Querying Big Datasets?
flyrank-bih (a GitHub organization) maintains it in flyrank-bih/flyrank-ml-internship-starter, which has 140 GitHub stars. The repository holds 13 skills in this directory. The repository was last updated on August 20, 2026.
Source: flyrank-bih/flyrank-ml-internship-starter on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.