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vercel/next.js
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Query BGS World Mineral Statistics for production, imports, and exports by commodity, country, and year
$ npx skills add lamm-mit/scienceclaw --skill bgs-production -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install lamm-mit/scienceclaw bgs-production --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/lamm-mit/scienceclaw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/bgs-production .claude/skills/bgs-production && 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 "bgs-production" agent skill from https://github.com/lamm-mit/scienceclaw/tree/main/skills/bgs-production into .claude/skills/bgs-production/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bgs-production", 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/lamm-mit/scienceclaw/tree/main/skills/bgs-productionType 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 lamm-mit/scienceclaw --skill bgs-production -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install lamm-mit/scienceclaw bgs-production --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/lamm-mit/scienceclaw.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/bgs-production .agents/skills/bgs-production && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "bgs-production" agent skill from https://github.com/lamm-mit/scienceclaw/tree/main/skills/bgs-production into .agents/skills/bgs-production/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bgs-production", 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 lamm-mit/scienceclaw --skill bgs-production -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install lamm-mit/scienceclaw bgs-production --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/lamm-mit/scienceclaw.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/bgs-production .cursor/skills/bgs-production && 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 "bgs-production" agent skill from https://github.com/lamm-mit/scienceclaw/tree/main/skills/bgs-production into .cursor/skills/bgs-production/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bgs-production", 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/lamm-mit/scienceclaw.git --path skills/bgs-production--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 lamm-mit/scienceclaw --skill bgs-production -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install lamm-mit/scienceclaw bgs-production --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/lamm-mit/scienceclaw.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/bgs-production .gemini/skills/bgs-production && 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 "bgs-production" agent skill from https://github.com/lamm-mit/scienceclaw/tree/main/skills/bgs-production into .gemini/skills/bgs-production/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bgs-production", 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 lamm-mit/scienceclaw bgs-productionInstalls 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 lamm-mit/scienceclaw --skill bgs-production -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/lamm-mit/scienceclaw.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/bgs-production .github/skills/bgs-production && 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 "bgs-production" agent skill from https://github.com/lamm-mit/scienceclaw/tree/main/skills/bgs-production into .github/skills/bgs-production/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bgs-production", 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 lamm-mit/scienceclaw --skill bgs-production -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install lamm-mit/scienceclaw bgs-production --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/lamm-mit/scienceclaw.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/bgs-production .opencode/skills/bgs-production && 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 "bgs-production" agent skill from https://github.com/lamm-mit/scienceclaw/tree/main/skills/bgs-production into .opencode/skills/bgs-production/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bgs-production", 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.
bgs-productionQuery BGS World Mineral Statistics for production, imports, and exports by commodity, country, and year
Bgs Production is an agent skill from lamm-mit/scienceclaw. Query BGS World Mineral Statistics for production, imports, and exports by commodity, country, and year
Its SKILL.md is about 670 tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including scripts (for example `scripts/bgs_query.py`).
It sits in Data & Analytics, covering Statistics. The licence is Apache-2.0.
Read from SKILL.md and the folder at commit ab9aba1. It shows what the files ask for, not the result of running them.
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.
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python3From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Bgs Production loads about 667 tokens when it runs. Until then it costs about 30 tokens; SKILL.md has 159 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.
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.
The full file from lamm-mit/scienceclaw at commit ab9aba1, republished under its Apache-2.0 licence (© lamm-mit). 159 words, ~667 tokens.
.claude/skills/bgs-production/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.Query the British Geological Survey's World Mineral Statistics database for mineral production, imports, and exports by commodity, country, and year. Covers global mineral data with country-level breakdowns.
python3 {baseDir}/scripts/bgs_query.py --query "lithium"python3 {baseDir}/scripts/bgs_query.py --query "Cobalt" --country "Congo"python3 {baseDir}/scripts/bgs_query.py --query "Copper" --year-from 2018 --year-to 2022python3 {baseDir}/scripts/bgs_query.py --query "Graphite" --ranking --top-n 10python3 {baseDir}/scripts/bgs_query.py --query "Nickel" --statistic-type "Exports"python3 {baseDir}/scripts/bgs_query.py --query "Rare earths" --format json --limit 20| Parameter | Description | Default |
|---|---|---|
--query | Commodity name to search for | Required |
--country | Filter by country name | - |
--year-from | Start year for date filter | - |
--year-to | End year for date filter | - |
--statistic-type | Statistic type: Production, Imports, Exports | Production |
--ranking | Show country ranking by production | false |
--top-n | Number of top countries in ranking | 15 |
--limit | Maximum records to return | 50 |
--format | Output format: summary, detailed, json | summary |
# Top lithium producers
python3 {baseDir}/scripts/bgs_query.py --query "Lithium" --ranking --top-n 10
# Cobalt production in Congo over time
python3 {baseDir}/scripts/bgs_query.py --query "Cobalt" --country "Congo" --year-from 2015 --format detailed
# Rare earth exports globally
python3 {baseDir}/scripts/bgs_query.py --query "Rare earths" --statistic-type "Exports" --format json
# Graphite production ranking for 2021
python3 {baseDir}/scripts/bgs_query.py --query "Graphite" --ranking --year-from 2021 --year-to 2021© lamm-mit, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file (scripts) in skills/bgs-production of lamm-mit/scienceclaw.
Open the folder on GitHubat commit ab9aba1
Bgs Production 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 |
|---|---|---|---|---|---|---|
| Bgs Production this skilllamm-mit/scienceclaw | 244 | — | ~667 | Automated safety check: Pass | Apache-2.0 | |
| Sandbox Benchvercel/next.js | 143k | — | ~4.1k | Automated safety check: Pass | MIT | |
| Statistical Analysisspacering-net/codeg | 3.9k | 3 repos | ~5k | Automated safety check: Pass | MIT | |
| StatsmodelszLanqing/codex-claude-academic-skills | 4.7k | 15 repos | ~4.9k | Automated safety check: Pass | BSD-3-Clause | |
| AI Daily DigestvigorX777/ai-daily-digest | 1.6k | — | ~1.3k | Automated safety check: Pass | None | |
| Statistical Powerspacering-net/codeg | 3.9k | 1 repos | ~3.6k | Automated safety check: Notes | MIT |
vercel/next.js
Benchmark React or Next.js changes on Vercel Sandbox VMs with paired A/B statistics: react PR/commit vs base, or Next.js PR/commit vs base, measured end-to-end through the bench/render-pipeline app…
spacering-net/codeg
Guided statistical analysis for research data - test selection, assumption checking, effect sizes, power analysis, Bayesian alternatives, and APA-formatted reporting.
zLanqing/codex-claude-academic-skills
Statistical models library for Python. An agent skill from zLanqing/codex-claude-academic-skills.
vigorX777/ai-daily-digest
Fetches RSS feeds from 90 top Hacker News blogs (curated by Karpathy), uses AI to score and filter articles, and generates a daily digest in Markdown with Chinese-translated titles, category…
spacering-net/codeg
Sample-size and statistical power calculations for planning studies.
higress-group/higress
Real-time agent conversation monitoring - monitors Higress access logs, aggregates conversations by session, tracks token usage.
lamm-mit/scienceclaw
Query FRED (Federal Reserve Economic Data) API for 800,000+ economic time series from 100+ sources.
lamm-mit/scienceclaw
Generates comprehensive drug research reports with compound disambiguation, evidence grading, and mandatory completeness sections.
lamm-mit/scienceclaw
Query and download public cancer imaging data from NCI Imaging Data Commons using idc-index.
lamm-mit/scienceclaw
Cloud-based quantum chemistry platform with Python API. An agent skill from lamm-mit/scienceclaw.
lamm-mit/scienceclaw
Create professional infographics using Nano Banana Pro AI with smart iterative refinement.
lamm-mit/scienceclaw
Generate comprehensive disease research reports using 100+ ToolUniverse tools.
Categories
Query BGS World Mineral Statistics for production, imports, and exports by commodity, country, and year. Bgs Production is an agent skill from lamm-mit/scienceclaw.
Bgs Production fits situations like: tasks that involve Statistics.
Run `npx skills add lamm-mit/scienceclaw --skill bgs-production -a claude-code`. Or copy the skill folder (skills/bgs-production in lamm-mit/scienceclaw) into .claude/skills/bgs-production in your project. Claude Code loads it when a task matches its description.
Run `npx skills add lamm-mit/scienceclaw --skill bgs-production -a codex`. Or copy the skill folder (skills/bgs-production in lamm-mit/scienceclaw) into .agents/skills/bgs-production in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add lamm-mit/scienceclaw --skill bgs-production -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/bgs-production, .gemini/skills/bgs-production, .github/skills/bgs-production and .opencode/skills/bgs-production in your project.
Going by SKILL.md and its folder, Bgs Production needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.
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.
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.
Bgs Production is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 667 tokens (SKILL.md is roughly 2.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Bgs Production: Sandbox Bench (vercel/next.js, 143k stars), Statistical Analysis (spacering-net/codeg, 3.9k stars), Statsmodels (zLanqing/codex-claude-academic-skills, 4.7k stars) and AI Daily Digest (vigorX777/ai-daily-digest, 1.6k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
lamm-mit (a GitHub user) maintains it in lamm-mit/scienceclaw, which has 244 GitHub stars. The repository holds 86 skills in this directory. The repository was last updated on August 21, 2026.
Source: lamm-mit/scienceclaw on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.