Configuring Horizon
coollabsio/coolify
A skill your agent uses whenever the user mentions Horizon by name in a Laravel context.
Global biodiversity data API for species occurrences and datasets
$ npx skills add wentorai/research-plugins --skill gbif-api -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install wentorai/research-plugins gbif-api --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/wentorai/research-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/domains/ecology/gbif-api .claude/skills/gbif-api && 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 "gbif-api" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/domains/ecology/gbif-api into .claude/skills/gbif-api/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gbif-api", 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/wentorai/research-plugins/tree/main/skills/domains/ecology/gbif-apiType 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 wentorai/research-plugins --skill gbif-api -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install wentorai/research-plugins gbif-api --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/domains/ecology/gbif-api .agents/skills/gbif-api && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "gbif-api" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/domains/ecology/gbif-api into .agents/skills/gbif-api/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gbif-api", 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 wentorai/research-plugins --skill gbif-api -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install wentorai/research-plugins gbif-api --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/domains/ecology/gbif-api .cursor/skills/gbif-api && 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 "gbif-api" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/domains/ecology/gbif-api into .cursor/skills/gbif-api/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gbif-api", 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/wentorai/research-plugins.git --path skills/domains/ecology/gbif-api--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 wentorai/research-plugins --skill gbif-api -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install wentorai/research-plugins gbif-api --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/domains/ecology/gbif-api .gemini/skills/gbif-api && 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 "gbif-api" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/domains/ecology/gbif-api into .gemini/skills/gbif-api/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gbif-api", 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 wentorai/research-plugins gbif-apiInstalls 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 wentorai/research-plugins --skill gbif-api -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/domains/ecology/gbif-api .github/skills/gbif-api && 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 "gbif-api" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/domains/ecology/gbif-api into .github/skills/gbif-api/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gbif-api", 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 wentorai/research-plugins --skill gbif-api -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install wentorai/research-plugins gbif-api --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/domains/ecology/gbif-api .opencode/skills/gbif-api && 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 "gbif-api" agent skill from https://github.com/wentorai/research-plugins/tree/main/skills/domains/ecology/gbif-api into .opencode/skills/gbif-api/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gbif-api", 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.
gbif-apiGlobal biodiversity data API for species occurrences and datasets
Gbif API is an agent skill from wentorai/research-plugins. Global biodiversity data API for species occurrences and datasets
Its SKILL.md is about 1.9k 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 Backend & APIs. The repository describes itself as: 350+ academic research skills, MCP configs, and plugins for Research-Claw and AI agents. The licence is MIT.
Read from SKILL.md and the folder at commit bf44b3c. 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.
Shell commands in SKILL.md call:
curlFrom the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
api.gbif.orgAlso links to:
gbif.orgFrom URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
TAXON_KEYFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Gbif API loads about 1.9k tokens when it runs. Until then it costs about 19 tokens; SKILL.md has 559 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); files beside SKILL.md are not scanned.
The full file from wentorai/research-plugins at commit bf44b3c, republished under its MIT licence (© wentorai). 559 words, ~1,880 tokens.
.claude/skills/gbif-api/SKILL.md (or your agent's skills folder).The Global Biodiversity Information Facility (GBIF) is an international network and data infrastructure funded by governments worldwide, aimed at providing open access to biodiversity data. GBIF aggregates hundreds of millions of species occurrence records from natural history collections, citizen science platforms, monitoring networks, and published literature across the globe.
The GBIF API provides programmatic access to this vast repository of biodiversity data. Researchers can search for species occurrences by taxonomy, geography, time period, and dataset. The API also supports taxonomic name matching, dataset discovery, and species profile lookups. It serves as a foundational resource for ecological research, conservation planning, biogeography, and environmental impact assessments.
Ecologists, conservation biologists, biogeographers, and environmental scientists rely on the GBIF API to retrieve georeferenced occurrence data for species distribution modeling, climate change impact analysis, invasive species tracking, and biodiversity hotspot identification. The data is freely available under open data licenses.
No authentication required for read access. The GBIF API is publicly accessible without any API key or token. All search and retrieval endpoints are open. User authentication is only required for data publishing operations (creating datasets and uploading occurrences), which requires a GBIF account.
Search for georeferenced biodiversity observation and specimen records across all GBIF-indexed datasets.
GET https://api.gbif.org/v1/occurrence/search| Parameter | Type | Required | Description |
|---|---|---|---|
| q | string | No | Full-text search query |
| taxonKey | int | No | GBIF backbone taxonomy key |
| scientificName | string | No | Scientific name to filter by |
| country | string | No | ISO 3166-1 alpha-2 country code |
| hasCoordinate | bool | No | Filter for georeferenced records only |
| year | string | No | Year or range (e.g., 2020,2024) |
| limit | int | No | Number of results (default 20, max 300) |
| offset | int | No | Pagination offset |
curl "https://api.gbif.org/v1/occurrence/search?scientificName=Panthera+tigris&hasCoordinate=true&limit=10"count (total matches), results array with key, scientificName, decimalLatitude, decimalLongitude, country, basisOfRecord, eventDate, datasetKey, publishingOrgKey, and media links.Match a species name against the GBIF backbone taxonomy to resolve canonical names and get taxonomy keys.
GET https://api.gbif.org/v1/species/match| Parameter | Type | Required | Description |
|---|---|---|---|
| name | string | Yes | Scientific name to match |
| kingdom | string | No | Kingdom filter for disambiguation |
| strict | bool | No | If true, only return exact matches |
curl "https://api.gbif.org/v1/species/match?name=Homo+sapiens"usageKey, scientificName, canonicalName, rank, status, kingdom, phylum, class, order, family, genus, species, confidence score, and matchType.Search for and retrieve metadata about GBIF-indexed datasets from publishers worldwide.
GET https://api.gbif.org/v1/dataset| Parameter | Type | Required | Description |
|---|---|---|---|
| q | string | No | Full-text search query |
| type | string | No | Dataset type: OCCURRENCE, CHECKLIST, etc. |
| publishingOrg | string | No | Publishing organization UUID |
| limit | int | No | Number of results (default 20, max 1000) |
| offset | int | No | Pagination offset |
curl "https://api.gbif.org/v1/dataset?q=bird+monitoring&type=OCCURRENCE&limit=5"count, results array with key, title, description, type, publishingOrganizationKey, license, recordCount, and endpoints.No formal rate limits are enforced on the GBIF API. However, GBIF recommends responsible use patterns. Large data downloads (millions of records) should use the asynchronous download API at https://api.gbif.org/v1/occurrence/download/request rather than paginating through the search endpoint. The search endpoint is limited to 100,000 records maximum per query via pagination.
Retrieve georeferenced occurrence data for species distribution modeling:
import requests
params = {
"taxonKey": 2480498, # Panthera tigris
"hasCoordinate": True,
"limit": 300
}
resp = requests.get("https://api.gbif.org/v1/occurrence/search", params=params)
data = resp.json()
coordinates = [(r["decimalLongitude"], r["decimalLatitude"])
for r in data["results"]
if "decimalLongitude" in r and "decimalLatitude" in r]
print(f"Retrieved {len(coordinates)} georeferenced occurrences of {data['results'][0]['scientificName']}")Resolve a list of species names against the GBIF backbone taxonomy:
import requests
names = ["Homo sapiens", "Canis lupus", "Quercus robur", "Drosophila melanogaster"]
for name in names:
resp = requests.get("https://api.gbif.org/v1/species/match", params={"name": name})
match = resp.json()
print(f"{name} -> {match['canonicalName']} (key: {match['usageKey']}, confidence: {match['confidence']})")For large-scale analyses requiring millions of records, use the asynchronous download API:
curl -X POST "https://api.gbif.org/v1/occurrence/download/request" \
-H "Content-Type: application/json" \
-u username:password \
-d '{"creator":"username","predicate":{"type":"equals","key":"TAXON_KEY","value":"2480498"}}'© wentorai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in skills/domains/ecology/gbif-api of wentorai/research-plugins.
Open the folder on GitHubat commit bf44b3c
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in wentorai/research-plugins, which our catalogue first saw on October 7, 2026.
Gbif API 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 |
|---|---|---|---|---|---|---|
| Gbif API this skillwentorai/research-plugins | 298 | 1 repos | ~1.9k | Automated safety check: Pass | MIT | |
| Configuring Horizoncoollabsio/coolify | 63k | 4 repos | ~898 | Automated safety check: Pass | MIT | |
| Nestjs Best Practicesrolling-scopes/rsschool-app | 10k | 6 repos | ~1.2k | Automated safety check: Pass | MIT | |
| Sub2API AdminWei-Shaw/sub2api | 43k | 1 repos | ~717 | Automated safety check: Pass | LGPL-3.0 | |
| Firecrawl Build Onboardingfirecrawl/firecrawl | 190k | 1 repos | ~1.4k | Automated safety check: Notes | ISC | |
| Obsidian BasesAtmosphere/atmosphere | 3.8k | 22 repos | ~3.2k | Automated safety check: Pass | Apache-2.0 |
coollabsio/coolify
A skill your agent uses whenever the user mentions Horizon by name in a Laravel context.
rolling-scopes/rsschool-app
NestJS best practices and architecture patterns for building production-ready applications.
Wei-Shaw/sub2api
Manages a Sub2API deployment from the command line: accounts, redeem and invitation codes, groups, proxies, imports, exports and raw admin API calls.
firecrawl/firecrawl
Gets Firecrawl working in a project: signs you in through the browser, saves FIRECRAWL_API_KEY to .env and picks the first SDK or REST path.
Atmosphere/atmosphere
Create and edit Obsidian Bases (.base files) with views, filters, formulas, and summaries.
coollabsio/coolify
ACTIVATE when the user works on authentication in Laravel. An agent skill from coollabsio/coolify.
wentorai/research-plugins
Craft structured research abstracts that maximize clarity and journal acceptance
wentorai/research-plugins
Manage academic citations across BibTeX, APA, MLA, and Chicago formats
wentorai/research-plugins
Summarize academic papers with structured extraction of key elements
wentorai/research-plugins
Evidence-based study techniques for academic learning and retention
wentorai/research-plugins
Adjust writing tone and register for academic audiences and venues
wentorai/research-plugins
Academic translation, post-editing, and Chinglish correction guide
Categories
Global biodiversity data API for species occurrences and datasets. Gbif API is an agent skill from wentorai/research-plugins.
Gbif API fits situations like: backend & APIs work in your project.
Run `npx skills add wentorai/research-plugins --skill gbif-api -a claude-code`. Or copy the skill folder (skills/domains/ecology/gbif-api in wentorai/research-plugins) into .claude/skills/gbif-api in your project. Claude Code loads it when a task matches its description.
Run `npx skills add wentorai/research-plugins --skill gbif-api -a codex`. Or copy the skill folder (skills/domains/ecology/gbif-api in wentorai/research-plugins) into .agents/skills/gbif-api 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 wentorai/research-plugins --skill gbif-api -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/gbif-api, .gemini/skills/gbif-api, .github/skills/gbif-api and .opencode/skills/gbif-api in your project.
Going by SKILL.md and its folder, Gbif API needs the command-line tools its instructions call (curl) and credentials named TAXON_KEY. Our summary lists: Python 3; A credential in TAXON_KEY.
SKILL.md names 2 domains. In commands or code: api.gbif.org; the agent is likely to contact it when it follows the instructions. As links in the text: gbif.org. 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. Review the folder before installing.
Gbif API is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.9k tokens (SKILL.md is roughly 7.5k 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 Gbif API: Configuring Horizon (coollabsio/coolify, 63k stars), Nestjs Best Practices (rolling-scopes/rsschool-app, 10k stars), Sub2API Admin (Wei-Shaw/sub2api, 43k stars) and Firecrawl Build Onboarding (firecrawl/firecrawl, 190k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
wentorai (a GitHub user) maintains it in wentorai/research-plugins, which has 298 GitHub stars. The repository holds 405 skills in this directory. The repository was last updated on June 19, 2026.
Source: wentorai/research-plugins on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.