Agent skill

Catalysis Hub API

by wentorai in wentorai/research-plugins

Query computational catalysis reaction data via Catalysis Hub GraphQL

MITAuto-check passedBackend & APIs

Install Catalysis Hub API

skills CLI
$ npx skills add wentorai/research-plugins --skill catalysis-hub-api -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install wentorai/research-plugins catalysis-hub-api --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/domains/chemistry/catalysis-hub-api .claude/skills/catalysis-hub-api && rm -rf skills-src

Use ~/.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/

Facts

Skill name
catalysis-hub-api
GitHub stars
298
Used in
1 other repo
Token cost
~1.8k tokens
SKILL.md length
325 words
Files
1
Skills in repo
405
Repo updated
First seen
Licence
MIT

At a glance

Query computational catalysis reaction data via Catalysis Hub GraphQL

  • Tasks that involve GraphQL
  • SKILL.md covers Overview, Authentication, GraphQL Schema and Core Queries, plus 4 more sections
  • Calls curl; reaches api.catalysis-hub.org

What it does

Catalysis Hub API is an agent skill from wentorai/research-plugins. Query computational catalysis reaction data via Catalysis Hub GraphQL

Its SKILL.md is about 1.8k 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, covering GraphQL. It works with GraphQL. The repository describes itself as: 350+ academic research skills, MCP configs, and plugins for Research-Claw and AI agents. The licence is MIT.

When your agent uses it

  • Tasks that involve GraphQL

Example prompts

  • “/catalysis-hub-api”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit bf44b3c. 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

    Shell commands in SKILL.md call:

    • curl

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • api.catalysis-hub.org

    Also links to:

    • catalysis-hub.org
    • suncat.stanford.edu

    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

Catalysis Hub API loads about 1.8k tokens when it runs. Until then it costs about 22 tokens; SKILL.md has 325 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~22
When it runs · the whole SKILL.md, loaded when a task matches
~1.8k

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

The full file from wentorai/research-plugins at commit bf44b3c, republished under its MIT licence (© wentorai). 325 words, ~1,750 tokens.

Download SKILL.mdSave it as .claude/skills/catalysis-hub-api/SKILL.md (or your agent's skills folder).
name
catalysis-hub-api
description
Query computational catalysis reaction data via Catalysis Hub GraphQL

Catalysis Hub GraphQL API Guide

Overview

Catalysis Hub is an open-access database of DFT-calculated reaction energies and activation barriers for heterogeneous catalysis, developed at SUNCAT Center (Stanford/SLAC). It aggregates computational results from published studies, enabling researchers to search, compare, and reuse DFT data for catalyst screening and mechanism validation.

The GraphQL endpoint provides structured access to reactions, publications, and atomic structures. All data is linked to peer-reviewed publications and includes computational details (DFT code, XC functional, surface facet, coverage).

Authentication

No authentication required. Catalysis Hub is a free public service with no API keys.

GraphQL Schema

Endpoint: https://api.catalysis-hub.org/graphql

All queries use HTTP POST with a JSON query field. Responses follow the Relay connection pattern (edges/node).

Root Query Types
QueryDescription
reactionsDFT-computed reaction energies and barriers
publicationsPublished studies linked to reaction data
systemsAtomic structure data (ASE Atoms objects)
speciesChemical species involved in reactions
Reaction Fields

chemicalComposition, surfaceComposition, facet, reactionEnergy (eV), activationEnergy (eV), dftCode (e.g. Quantum-Espresso, VASP-5.4.4), dftFunctional (e.g. RPBE), reactants (JSON), products (JSON), Equation (e.g. 0.5O2(g) + * -> O*)

Publication Fields

title, authors (JSON), journal, year (Int), doi, reactions (linked Reaction list)

Core Queries

List Reactions
bash
curl -s -X POST "https://api.catalysis-hub.org/graphql" \
  -H "Content-Type: application/json" -d '{"query":"{ reactions(first: 3) { edges { node { chemicalComposition reactionEnergy activationEnergy surfaceComposition } } } }"}'

Response (truncated):

json
{"data":{"reactions":{"edges":[
  {"node":{"chemicalComposition":"Nb9Sn3","reactionEnergy":-9.687,"activationEnergy":null,"surfaceComposition":"Nb3Sn"}},
  {"node":{"chemicalComposition":"Ir3V9","reactionEnergy":-8.395,"activationEnergy":null,"surfaceComposition":"V3Ir"}},
  {"node":{"chemicalComposition":"Ir9Ni3","reactionEnergy":-2.005,"activationEnergy":null,"surfaceComposition":"Ir3Ni"}}
]}}}
Filter by Surface Composition
bash
curl -s -X POST "https://api.catalysis-hub.org/graphql" \
  -H "Content-Type: application/json" -d '{"query":"{ reactions(first: 2, surfaceComposition: \"Pt\") { edges { node { chemicalComposition surfaceComposition facet reactionEnergy dftCode dftFunctional Equation } } } }"}'

Response (truncated):

json
{"data":{"reactions":{"edges":[
  {"node":{"chemicalComposition":"Pt28","surfaceComposition":"Pt","facet":"100","reactionEnergy":0.856,"dftCode":"Quantum-Espresso","dftFunctional":"RPBE","Equation":"0.5N2(g) + * -> N*"}},
  {"node":{"chemicalComposition":"Pt28","surfaceComposition":"Pt","facet":"100","reactionEnergy":-0.984,"dftCode":"Quantum-Espresso","dftFunctional":"RPBE","Equation":"0.5O2(g) + * -> O*"}}
]}}}
Search by Chemical Composition (partial match with ~ prefix)
bash
curl -s -X POST "https://api.catalysis-hub.org/graphql" \
  -H "Content-Type: application/json" -d '{"query":"{ reactions(first: 3, chemicalComposition: \"~CO\") { edges { node { chemicalComposition reactionEnergy dftCode } } } }"}'

Response (truncated):

json
{"data":{"reactions":{"edges":[
  {"node":{"chemicalComposition":"Co9Cr2FeMnNiO20","reactionEnergy":1.910,"dftCode":"VASP-5.4.4"}},
  {"node":{"chemicalComposition":"Co9Cr2FeMnNiO20","reactionEnergy":0.648,"dftCode":"VASP-5.4.4"}},
  {"node":{"chemicalComposition":"Co10CrFeMnNiO20","reactionEnergy":3.167,"dftCode":"VASP-5.4.4"}}
]}}}
Query Publications
bash
curl -s -X POST "https://api.catalysis-hub.org/graphql" \
  -H "Content-Type: application/json" -d '{"query":"{ publications(first: 2, year: 2019) { edges { node { title authors journal year doi } } } }"}'

Response (truncated):

json
{"data":{"publications":{"edges":[
  {"node":{"title":"High-Throughput Calculations of Catalytic Properties of Bimetallic Alloy Surfaces","authors":"[\"Mamun, Osman\",\"Winther, Kirsten T.\",\"Boes, Jacob R.\",\"Bligaard, Thomas\"]","journal":"Scientific Data","year":2019,"doi":"10.1038/s41597-019-0080-z"}},
  {"node":{"title":"Selective high-temperature CO2 electrolysis enabled by oxidized carbon intermediates","journal":"Nature Energy","year":2019,"doi":"10.1038/s41560-019-0457-4"}}
]}}}

Rate Limits

  • No documented rate limits; add 200-500ms delays between requests as courtesy
  • Use first to limit results; pagination via cursor-based after argument

Academic Use Cases

  • Catalyst Screening: Compare adsorption energies across bimetallic alloy surfaces to identify candidates for target reactions (ORR, NRR, HER)
  • DFT Validation: Cross-reference your DFT results against published values matched by surface, facet, and functional
  • Scaling Relations: Retrieve adsorption energies across surfaces to build Bronsted-Evans-Polanyi (BEP) relations
  • Literature Discovery: Find publications by year or linked reactions for citation and methodology verification

Python Example

python
import requests

ENDPOINT = "https://api.catalysis-hub.org/graphql"

def query_catalysis_hub(query):
    """Execute a GraphQL query against Catalysis Hub."""
    resp = requests.post(ENDPOINT, json={"query": query})
    resp.raise_for_status()
    return resp.json()["data"]

# Screen adsorption energies on Pt surfaces
data = query_catalysis_hub("""
{
  reactions(first: 20, surfaceComposition: "Pt") {
    edges { node { Equation facet reactionEnergy dftFunctional } }
  }
}
""")
for edge in data["reactions"]["edges"]:
    r = edge["node"]
    print(f"{r['Equation']:<30} facet={r['facet']}  E={r['reactionEnergy']:+.3f} eV")

# Publications with linked reactions
pubs = query_catalysis_hub("""
{
  publications(first: 5, year: 2019) {
    edges { node { title doi reactions { surfaceComposition Equation } } }
  }
}
""")
for edge in pubs["publications"]["edges"]:
    pub = edge["node"]
    print(f"{pub['title']} | DOI: {pub['doi']} | {len(pub.get('reactions') or [])} reactions")

References

© wentorai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/domains/chemistry/catalysis-hub-api of wentorai/research-plugins.

Open the folder on GitHubat commit bf44b3c

Used in 1 other repository

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.

Compare with similar skills

Catalysis Hub 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.

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GraphQL Operations with CodegenChrisWiles/claude-code-showcase6.1k3 repos~1.5kAutomated safety check: PassNone
API Design Principlesjh941213/my-cc-harness12618 repos~3.4kAutomated safety check: PassNone
API And Interface Designdzhalaevd/Donatello1358 repos~2.6kAutomated safety check: PassApache-2.0

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Works with

Categories

Questions about Catalysis Hub API

What does Catalysis Hub API do?

Query computational catalysis reaction data via Catalysis Hub GraphQL. Catalysis Hub API is an agent skill from wentorai/research-plugins.

When should I use Catalysis Hub API?

Catalysis Hub API fits situations like: tasks that involve GraphQL.

How do I install Catalysis Hub API in Claude Code?

Run `npx skills add wentorai/research-plugins --skill catalysis-hub-api -a claude-code`. Or copy the skill folder (skills/domains/chemistry/catalysis-hub-api in wentorai/research-plugins) into .claude/skills/catalysis-hub-api in your project. Claude Code loads it when a task matches its description.

How do I install Catalysis Hub API in Codex?

Run `npx skills add wentorai/research-plugins --skill catalysis-hub-api -a codex`. Or copy the skill folder (skills/domains/chemistry/catalysis-hub-api in wentorai/research-plugins) into .agents/skills/catalysis-hub-api in your project. Codex loads it when a task matches its description.

Can I use Catalysis Hub API 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 wentorai/research-plugins --skill catalysis-hub-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/catalysis-hub-api, .gemini/skills/catalysis-hub-api, .github/skills/catalysis-hub-api and .opencode/skills/catalysis-hub-api in your project.

What does Catalysis Hub API need to run?

Going by SKILL.md and its folder, Catalysis Hub API needs the command-line tools its instructions call (curl). Our summary lists: Python 3.

Does Catalysis Hub API access the network?

SKILL.md names 3 domains. In commands or code: api.catalysis-hub.org; the agent is likely to contact it when it follows the instructions. As links in the text: catalysis-hub.org and suncat.stanford.edu. This is read from the text; nothing was executed.

Is Catalysis Hub API 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 Catalysis Hub API use?

Catalysis Hub API 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 Catalysis Hub API use?

About 1.8k tokens (SKILL.md is roughly 7k 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 Catalysis Hub API?

Skills that share tags, products or a category with Catalysis Hub API: Nodejs Backend Patterns (ever-works/ever-works, 162 stars), API Designer (Jeffallan/claude-skills, 12k stars), GraphQL Operations with Codegen (ChrisWiles/claude-code-showcase, 6.1k stars) and API Design Principles (jh941213/my-cc-harness, 126 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Catalysis Hub API?

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.