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majiayu000/claude-skill-registry
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Agent skill
Data Collection
by brycewang-stanford in brycewang-stanford/Auto-Empirical-Research-Skills
A skill your agent uses when collecting data for a research project, downloading time series, building a dataset, accessing economic or social data APIs, or scraping data from a non-API source.
Install Data Collection
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill data-collection -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Auto-Empirical-Research-Skills data-collection --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/brycewang-stanford/Auto-Empirical-Research-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/60-regisely-superpapers/skills/data-collection .claude/skills/data-collection && 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 "data-collection" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/60-regisely-superpapers/skills/data-collection into .claude/skills/data-collection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-collection", 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/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/60-regisely-superpapers/skills/data-collectionType 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 brycewang-stanford/Auto-Empirical-Research-Skills --skill data-collection -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Auto-Empirical-Research-Skills data-collection --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/60-regisely-superpapers/skills/data-collection .agents/skills/data-collection && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "data-collection" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/60-regisely-superpapers/skills/data-collection into .agents/skills/data-collection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-collection", 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 brycewang-stanford/Auto-Empirical-Research-Skills --skill data-collection -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Auto-Empirical-Research-Skills data-collection --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/60-regisely-superpapers/skills/data-collection .cursor/skills/data-collection && 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 "data-collection" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/60-regisely-superpapers/skills/data-collection into .cursor/skills/data-collection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-collection", 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/brycewang-stanford/Auto-Empirical-Research-Skills.git --path skills/60-regisely-superpapers/skills/data-collection--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 brycewang-stanford/Auto-Empirical-Research-Skills --skill data-collection -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Auto-Empirical-Research-Skills data-collection --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/60-regisely-superpapers/skills/data-collection .gemini/skills/data-collection && 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 "data-collection" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/60-regisely-superpapers/skills/data-collection into .gemini/skills/data-collection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-collection", 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 brycewang-stanford/Auto-Empirical-Research-Skills data-collectionInstalls 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 brycewang-stanford/Auto-Empirical-Research-Skills --skill data-collection -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/60-regisely-superpapers/skills/data-collection .github/skills/data-collection && 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 "data-collection" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/60-regisely-superpapers/skills/data-collection into .github/skills/data-collection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-collection", 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 brycewang-stanford/Auto-Empirical-Research-Skills --skill data-collection -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install brycewang-stanford/Auto-Empirical-Research-Skills data-collection --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/60-regisely-superpapers/skills/data-collection .opencode/skills/data-collection && 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 "data-collection" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/60-regisely-superpapers/skills/data-collection into .opencode/skills/data-collection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-collection", 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
data-collection- GitHub stars
- 4.5k
- Token cost
- ~975 tokens
- SKILL.md length
- 501 words
- Files
- 2 (incl. references)
- Skills in repo
- 369
- Repo updated
- First seen
- Licence
- Custom licence
At a glance
A skill your agent uses when collecting data for a research project, downloading time series, building a dataset, accessing economic or social data APIs, or scraping data from a non-API source.
- Works in 7 steps: Identify data needs from the research… → Find appropriate sources. Start with… → Prefer APIs over scraping. APIs are… → …
- Collecting data for a research project
- SKILL.md covers Overview, When to Use, Mandatory Steps and Source Discovery Process, plus 2 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Data Collection is an agent skill from brycewang-stanford/Auto-Empirical-Research-Skills. Use when collecting data for a research project, downloading time series, building a dataset, accessing economic or social data APIs, or scraping data from a non-API source. Handles source discovery, respectful collection, local caching, and manifest documentation.
Its SKILL.md is about 980 tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/common-sources.md`).
It sits in Data & Analytics, covering Web scraping, Forecasting and time series and Caching. The repository describes itself as: 🔬 A curated collection of 23,000+ agent skills for empirical research across 8 social science disciplines. | 精选 23,000+ AI Agent 技能库，覆盖8大社会科学学科的实证研究。CoPaper.AI…
When your agent uses it
- Collecting data for a research project
- Downloading time series
- Building a dataset
- Accessing economic
Example prompts
- “/data-collection”
Workflow steps
7 steps, taken from the first numbered list in SKILL.md.
- Identify data needs from the research question. Variables, units (country, firm, individual, pixel), frequency, period, geography, and any…
- Find appropriate sources. Start with references/common-sources.md. If the user's needs are not covered there, search the web for the…
- Prefer APIs over scraping. APIs are versioned, documented, and legal. Scraping is the last resort when no API is available.
- When scraping is necessary, be respectful
- Save raw data in data/raw/ in a versionable format. Parquet is preferred for tabular data; CSV is acceptable for small datasets. Never…
- Document every dataset in data/manifest.md following the format from replication-driven-research: name, source, URL or API endpoint…
- Cache locally. Check data/raw/ before fetching. Only invoke the network if the file is missing or the user has explicitly requested a…
What it can do on your machine
Read from SKILL.md and the folder at commit 9fa87d8. 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.
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
Data Collection loads about 975 tokens when it runs, and up to ~3.8k if it reads all its reference files. Until then it costs about 70 tokens; SKILL.md has 501 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 501 words (~975 tokens).
“This skill guides data collection from the research question to a versionable artifact in data/raw/. It is field-agnostic and open-ended about sources — the references/common-sources.md file is a starting point, not a boundary. For any research question, the skill uses…”
- name
- data-collection
Files
SKILL.md and 1 other file (references) in skills/60-regisely-superpapers/skills/data-collection of brycewang-stanford/Auto-Empirical-Research-Skills.
- SKILL.md
- references/common-sources.md
Open the folder on GitHubat commit 9fa87d8
Compare with similar skills
Data Collection 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 |
|---|---|---|---|---|---|---|
| Data Collection this skillbrycewang-stanford/Auto-Empirical-Research-Skills | 4.5k | — | ~975 | Automated safety check: Pass | Custom licence | |
| Apify Trend Analysismajiayu000/claude-skill-registry | 666 | 3 repos | ~1.1k | Automated safety check: Notes | MIT | |
| AWS Databaseaws/agent-toolkit-for-aws | 2.8k | — | ~2k | Automated safety check: Pass | Apache-2.0 | |
| TimesFM Forecastinggoogle-research/timesfm | 34k | — | ~4.7k | Automated safety check: Pass | Apache-2.0 | |
| Tmuxtrpc-group/trpc-agent-go | 1.8k | 23 repos | ~868 | Automated safety check: Pass | Apache-2.0 | |
| Timesfm ForecastingzLanqing/codex-claude-academic-skills | 4.6k | 6 repos | ~7.5k | Automated safety check: Notes | Apache-2.0 |
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Forecasts any univariate time series zero-shot with Google's TimesFM model, returning point forecasts and calibrated prediction intervals without training.
Tmux
trpc-group/trpc-agent-go
Remote-control tmux sessions for interactive CLIs by sending keystrokes and scraping pane output.
Timesfm Forecasting
zLanqing/codex-claude-academic-skills
Zero-shot time series forecasting with Google's TimesFM foundation model.
Statsmodels
zLanqing/codex-claude-academic-skills
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Related
Categories
Questions about Data Collection
What does Data Collection do?
A skill your agent uses when collecting data for a research project, downloading time series, building a dataset, accessing economic or social data APIs, or scraping data from a non-API source. Data Collection is an agent skill from brycewang-stanford/Auto-Empirical-Research-Skills. Use when collecting data for a research project, downloading time series, building a dataset, accessing economic or social data APIs, or scraping data from a non-API source.
When should I use Data Collection?
Data Collection fits situations like: collecting data for a research project; downloading time series; building a dataset; accessing economic.
How do I install Data Collection in Claude Code?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill data-collection -a claude-code`. Or copy the skill folder (skills/60-regisely-superpapers/skills/data-collection in brycewang-stanford/Auto-Empirical-Research-Skills) into .claude/skills/data-collection in your project. Claude Code loads it when a task matches its description.
How do I install Data Collection in Codex?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill data-collection -a codex`. Or copy the skill folder (skills/60-regisely-superpapers/skills/data-collection in brycewang-stanford/Auto-Empirical-Research-Skills) into .agents/skills/data-collection in your project. Codex loads it when a task matches its description.
Can I use Data Collection 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 brycewang-stanford/Auto-Empirical-Research-Skills --skill data-collection -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/data-collection, .gemini/skills/data-collection, .github/skills/data-collection and .opencode/skills/data-collection in your project.
What does Data Collection need to run?
SKILL.md names no scripts, command-line tools or credentials: Data Collection is instructions for the agent only.
Does Data Collection 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 Data Collection 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 Data Collection use?
Data Collection 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 Data Collection use?
About 975 tokens (SKILL.md is roughly 3.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.9k tokens, read only when the agent opens those files.
What are the alternatives to Data Collection?
Skills that share tags, products or a category with Data Collection: Apify Trend Analysis (majiayu000/claude-skill-registry, 666 stars), AWS Database (aws/agent-toolkit-for-aws, 2.8k stars), TimesFM Forecasting (google-research/timesfm, 34k stars) and Tmux (trpc-group/trpc-agent-go, 1.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Data Collection?
brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Auto-Empirical-Research-Skills, which has 4,517 GitHub stars. The repository holds 369 skills in this directory. The repository was last updated on October 5, 2026.
Source: brycewang-stanford/Auto-Empirical-Research-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.