Ideer Daily Paper
AI45Lab/iDeer
Daily paper/repo digest where YOU are the reader. An agent skill from AI45Lab/iDeer.
“Multi-source ML dataset discovery.”
Install Dataset Discovery
$ npx skills add LigphiDonk/Oh-my--paper --skill dataset-discovery -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install LigphiDonk/Oh-my--paper dataset-discovery --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/LigphiDonk/Oh-my--paper.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/dataset-discovery .claude/skills/dataset-discovery && 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 "dataset-discovery" agent skill from https://github.com/LigphiDonk/Oh-my--paper/tree/main/skills/dataset-discovery into .claude/skills/dataset-discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dataset-discovery", 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/LigphiDonk/Oh-my--paper/tree/main/skills/dataset-discoveryType 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 LigphiDonk/Oh-my--paper --skill dataset-discovery -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install LigphiDonk/Oh-my--paper dataset-discovery --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LigphiDonk/Oh-my--paper.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/dataset-discovery .agents/skills/dataset-discovery && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "dataset-discovery" agent skill from https://github.com/LigphiDonk/Oh-my--paper/tree/main/skills/dataset-discovery into .agents/skills/dataset-discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dataset-discovery", 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 LigphiDonk/Oh-my--paper --skill dataset-discovery -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install LigphiDonk/Oh-my--paper dataset-discovery --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LigphiDonk/Oh-my--paper.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/dataset-discovery .cursor/skills/dataset-discovery && 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 "dataset-discovery" agent skill from https://github.com/LigphiDonk/Oh-my--paper/tree/main/skills/dataset-discovery into .cursor/skills/dataset-discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dataset-discovery", 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/LigphiDonk/Oh-my--paper.git --path skills/dataset-discovery--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 LigphiDonk/Oh-my--paper --skill dataset-discovery -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install LigphiDonk/Oh-my--paper dataset-discovery --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LigphiDonk/Oh-my--paper.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/dataset-discovery .gemini/skills/dataset-discovery && 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 "dataset-discovery" agent skill from https://github.com/LigphiDonk/Oh-my--paper/tree/main/skills/dataset-discovery into .gemini/skills/dataset-discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dataset-discovery", 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 LigphiDonk/Oh-my--paper dataset-discoveryInstalls 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 LigphiDonk/Oh-my--paper --skill dataset-discovery -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/LigphiDonk/Oh-my--paper.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/dataset-discovery .github/skills/dataset-discovery && 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 "dataset-discovery" agent skill from https://github.com/LigphiDonk/Oh-my--paper/tree/main/skills/dataset-discovery into .github/skills/dataset-discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dataset-discovery", 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 LigphiDonk/Oh-my--paper --skill dataset-discovery -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install LigphiDonk/Oh-my--paper dataset-discovery --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LigphiDonk/Oh-my--paper.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/dataset-discovery .opencode/skills/dataset-discovery && 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 "dataset-discovery" agent skill from https://github.com/LigphiDonk/Oh-my--paper/tree/main/skills/dataset-discovery into .opencode/skills/dataset-discovery/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dataset-discovery", 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
dataset-discovery- GitHub stars
- 739
- Token cost
- ~1.3k tokens
- SKILL.md length
- 390 words
- Files
- 3 (incl. scripts)
- Skills in repo
- 27
- Repo updated
- First seen
- Licence
- MIT
At a glance
- Works in 5 steps: SCOPE → SEARCH → PRESENT → …
- SKILL.md covers Canonical Summary, Trigger Rules, Resource Use Rules and Execution Contract, plus 5 more sections
- Runs Python scripts from its folder; calls python3 and huggingface-cli
About this skill
Dataset Discovery is a skill in LigphiDonk/Oh-my--paper (739 stars). Its SKILL.md is about 1.3k tokens, with 2 other files in the folder (scripts). Licence: MIT.
Workflow steps
5 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 6baece9. 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
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python3huggingface-cli
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
Dataset Discovery loads about 1.3k tokens when it runs. Until then it costs about 13 tokens; SKILL.md has 390 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); the scripts in this folder are not scanned.
SKILL.md
The full file from LigphiDonk/Oh-my--paper at commit 6baece9, republished under its MIT licence (© LigphiDonk). 390 words, ~1,252 tokens.
Download SKILL.mdSave it as
.claude/skills/dataset-discovery/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.- name
- dataset-discovery
- description
- Multi-source ML dataset discovery.
- id
- dataset-discovery
- version
- 1.0.0
- stages
- survey, ideation, experiment
- tools
- read_file, search_project, write_file, run_terminal
- summary
- Multi-source ML dataset discovery. Search HuggingFace Hub, OpenML, GitHub, and paper cross-references for datasets relevant to a research task. Use when asked…
- primaryIntent
- data
- intents
- data, research
- capabilities
- search-retrieval, data-processing
- domains
- data-engineering
- keywords
- dataset-discovery, resource prep, search-retrieval, data-processing, data-engineering, dataset, discovery, multi, source, ml, search, huggingface
dataset-discovery
Canonical Summary
Multi-source ML dataset discovery. Search HuggingFace Hub, OpenML, GitHub, and paper cross-references for datasets relevant to a research task. Use when asked to "find datasets for", "search ML datasets", "what datasets exist for", or "dis...
Trigger Rules
Use this skill when the user request matches its research workflow scope. Prefer the bundled resources instead of recreating templates or reference material. Keep outputs traceable to project files, citations, scripts, or upstream evidence.
Resource Use Rules
- Treat
scripts/as optional helpers. Run them only when their dependencies are available, keep outputs in the project workspace, and explain a manual fallback if execution is blocked.
Execution Contract
- Resolve every relative path from this skill directory first.
- Prefer inspection before mutation when invoking bundled scripts.
- If a required runtime, CLI, credential, or API is unavailable, explain the blocker and continue with the best manual fallback instead of silently skipping the step.
- Do not write generated artifacts back into the skill directory; save them inside the active project workspace.
Upstream Instructions
Dataset Discovery Skill
Overview
Search multiple ML dataset sources (HuggingFace Hub, OpenML, GitHub, Semantic Scholar) and return a ranked, deduplicated list of relevant datasets.
Agent Workflow
Phase 1: SCOPE
Clarify the user's needs before searching:
- Research task: What problem or domain? (e.g., "sentiment analysis", "medical image segmentation")
- Modality: image / text / tabular / audio / any
- Size preference: small (< 10K rows), medium (10K–1M), large (> 1M), any
- License preference: permissive (MIT/Apache/CC-BY), any, or specific
Show full SKILL.md (151 more words)Show less
Phase 2: SEARCH
Run the search script with the user's query:
python3 scripts/search_ml_datasets.py search --query "<query>" --sources huggingface,openml,github,papers --max 30Options:
--sources: Comma-separated list fromhuggingface,openml,github,papers. Default: all four.--max: Maximum results to return after dedup + ranking. Default: 30.--modality: Filter by modality (image,text,tabular,audio).--workspace: Output directory. Default:./datasets/discovery/
Optionally also call HF MCP tool hub_repo_search with repo_types: ["dataset"] for semantic search to supplement results.
Phase 3: PRESENT
Show results as a markdown table:
| Name | Source | Downloads | Size | License | Tags | URL |
|---|
Sort by relevance score (highest first).
Phase 4: DETAIL
When the user wants more info on a specific dataset:
python3 scripts/search_ml_datasets.py detail --dataset-id "huggingface:stanfordnlp/imdb" --workspace ./datasets/discovery/Writes metadata.json and README.md to {workspace}/datasets/{source}_{slug}/.
Phase 5: PULL
When the user wants to preview data:
python3 scripts/search_ml_datasets.py pull --dataset-id "huggingface:stanfordnlp/imdb" --sample-rows 20 --workspace ./datasets/discovery/Writes sample.jsonl to {workspace}/datasets/{source}_{slug}/.
For full dataset download, confirm with the user first, then use huggingface-cli download or equivalent.
Workspace Layout
{workspace}/ # default: ./datasets/discovery/
search-{YYYY-MM-DD}.json # search results log
datasets/
{source}_{slug}/
metadata.json # detailed metadata
README.md # human-readable summary
sample.jsonl # sample rowsDependencies
- Python 3.8+
requests(stdlib-adjacent, universally available)ghCLI (for GitHub source only)- No other packages required
© LigphiDonk, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 2 other files (scripts) in skills/dataset-discovery of LigphiDonk/Oh-my--paper.
- SKILL.md
- scripts/search_ml_datasets.py
- tests/prompts.txt
Open the folder on GitHubat commit 6baece9
Compare with similar skills
Dataset Discovery 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 |
|---|---|---|---|---|---|---|
| Dataset Discovery this skillLigphiDonk/Oh-my--paper | 739 | — | ~1.3k | Automated safety check: Pass | MIT | |
| Ideer Daily PaperAI45Lab/iDeer | 416 | — | ~2.3k | Automated safety check: Notes | AGPL-3.0 | |
| Hugging Face Paper Pageshuggingface/skills | 11k | 3 repos | ~2.3k | Automated safety check: Pass | Apache-2.0 | |
| Academic AioAperivue/medsci-skills | 333 | — | ~4.8k | Automated safety check: Pass | MIT | |
| Morning AIdavepoon/buildwithclaude | 3.6k | — | ~405 | Automated safety check: Pass | MIT | |
| ML Dataset DiscoveryOpenLAIR/dr-claw | 1.2k | — | ~741 | Automated safety check: Pass | Custom licence |
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Related
Works with
Categories
Questions about Dataset Discovery
How do I install Dataset Discovery in Claude Code?
Run `npx skills add LigphiDonk/Oh-my--paper --skill dataset-discovery -a claude-code`. Or copy the skill folder (skills/dataset-discovery in LigphiDonk/Oh-my--paper) into .claude/skills/dataset-discovery in your project. Claude Code loads it when a task matches its description.
How do I install Dataset Discovery in Codex?
Run `npx skills add LigphiDonk/Oh-my--paper --skill dataset-discovery -a codex`. Or copy the skill folder (skills/dataset-discovery in LigphiDonk/Oh-my--paper) into .agents/skills/dataset-discovery in your project. Codex loads it when a task matches its description.
Can I use Dataset Discovery 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 LigphiDonk/Oh-my--paper --skill dataset-discovery -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/dataset-discovery, .gemini/skills/dataset-discovery, .github/skills/dataset-discovery and .opencode/skills/dataset-discovery in your project.
What does Dataset Discovery need to run?
Going by SKILL.md and its folder, Dataset Discovery needs Python for the scripts in its folder and the command-line tools its instructions call (python3 and huggingface-cli).
Does Dataset Discovery 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 Dataset Discovery 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Dataset Discovery use?
Dataset Discovery is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Dataset Discovery use?
About 1.3k tokens (SKILL.md is roughly 5k 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 Dataset Discovery?
Skills that share tags, products or a category with Dataset Discovery: Ideer Daily Paper (AI45Lab/iDeer, 416 stars), Hugging Face Paper Pages (huggingface/skills, 11k stars), Academic Aio (Aperivue/medsci-skills, 333 stars) and Morning AI (davepoon/buildwithclaude, 3.6k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Dataset Discovery?
LigphiDonk (a GitHub user) maintains it in LigphiDonk/Oh-my--paper, which has 739 GitHub stars. The repository holds 27 skills in this directory. The repository was last updated on April 15, 2026.
Source: LigphiDonk/Oh-my--paper on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.