Agent skill

Abinit

Generate and manage ABINIT DFT calculations. An agent skill from Hello-QM/catgo-LRG.

AGPL-3.0Auto-check passed

Install Abinit

skills CLI

$ npx skills add Hello-QM/catgo-LRG --skill abinit -a claude-code

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

GitHub CLI

$ gh skill install Hello-QM/catgo-LRG abinit --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/Hello-QM/catgo-LRG.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/abinit .claude/skills/abinit && 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/

Paste into Claude Code

Install the "abinit" agent skill from https://github.com/Hello-QM/catgo-LRG/tree/main/.claude/skills/abinit into .claude/skills/abinit/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "abinit", 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

$skill-installer install https://github.com/Hello-QM/catgo-LRG/tree/main/.claude/skills/abinit

Type 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.

skills CLI

$ npx skills add Hello-QM/catgo-LRG --skill abinit -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install Hello-QM/catgo-LRG abinit --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/Hello-QM/catgo-LRG.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/abinit .agents/skills/abinit && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "abinit" agent skill from https://github.com/Hello-QM/catgo-LRG/tree/main/.claude/skills/abinit into .agents/skills/abinit/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "abinit", 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.

skills CLI

$ npx skills add Hello-QM/catgo-LRG --skill abinit -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install Hello-QM/catgo-LRG abinit --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/Hello-QM/catgo-LRG.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/abinit .cursor/skills/abinit && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "abinit" agent skill from https://github.com/Hello-QM/catgo-LRG/tree/main/.claude/skills/abinit into .cursor/skills/abinit/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "abinit", 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

$ gemini skills install https://github.com/Hello-QM/catgo-LRG.git --path .claude/skills/abinit

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add Hello-QM/catgo-LRG --skill abinit -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install Hello-QM/catgo-LRG abinit --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/Hello-QM/catgo-LRG.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/abinit .gemini/skills/abinit && rm -rf skills-src

Use ~/.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/

Paste into Gemini CLI

Install the "abinit" agent skill from https://github.com/Hello-QM/catgo-LRG/tree/main/.claude/skills/abinit into .gemini/skills/abinit/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "abinit", 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.

GitHub CLI

$ gh skill install Hello-QM/catgo-LRG abinit

Installs 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).

skills CLI

$ npx skills add Hello-QM/catgo-LRG --skill abinit -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/Hello-QM/catgo-LRG.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/abinit .github/skills/abinit && rm -rf skills-src

Use ~/.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/

Paste into GitHub Copilot

Install the "abinit" agent skill from https://github.com/Hello-QM/catgo-LRG/tree/main/.claude/skills/abinit into .github/skills/abinit/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "abinit", 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.

skills CLI

$ npx skills add Hello-QM/catgo-LRG --skill abinit -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install Hello-QM/catgo-LRG abinit --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/Hello-QM/catgo-LRG.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/abinit .opencode/skills/abinit && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "abinit" agent skill from https://github.com/Hello-QM/catgo-LRG/tree/main/.claude/skills/abinit into .opencode/skills/abinit/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "abinit", 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: abinit
GitHub stars: 205
Token cost: ~963 tokens
SKILL.md length: 303 words
Files: 1
Skills in repo: 75
Repo updated: Sep 22, 2026
First seen: Oct 7, 2026
Licence: AGPL-3.0

At a glance

Generate and manage ABINIT DFT calculations. An agent skill from Hello-QM/catgo-LRG.

Works in 3 steps: Verify structure → Create workflow → Add ABINIT task via shell
The user requests ABINIT
SKILL.md covers When to Use, Prerequisites, Workflow Steps and Input File Template — SCF, plus 4 more sections
Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Abinit is an agent skill from Hello-QM/catgo-LRG. Generate and manage ABINIT DFT calculations. Use when the user requests ABINIT, or needs DFPT phonons, GW calculations, or BSE optical spectra.

Its SKILL.md is about 960 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts. Compatibility notes: Requires ABINIT installed on the HPC target. Pseudopotential files (PAW JTH or norm-conserving) must be available.

The repository describes itself as: AI-driven workbench for computational materials science — interactive 3D structure viewer, natural-language CatBot assistant, visual DAG workflow engine, HPC job submission… The licence is AGPL-3.0.

When your agent uses it

The user requests ABINIT
Needs DFPT phonons
GW calculations
BSE optical spectra

Example prompts

“/abinit”

Requirements

Compatibility (from SKILL.md): Requires ABINIT installed on the HPC target. Pseudopotential files (PAW JTH or norm-conserving) must be available.

Workflow steps

3 steps, taken from the step headings in SKILL.md.

Verify structure
Create workflow
Add ABINIT task via shell

What it can do on your machine

Read from SKILL.md and the folder at commit fd6291b. 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.
Compatibility
Requires ABINIT installed on the HPC target. Pseudopotential files (PAW JTH or norm-conserving) must be available.
From compatibility in the SKILL.md frontmatter.

Context cost

Abinit loads about 963 tokens when it runs. Until then it costs about 38 tokens; SKILL.md has 303 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~38
When it runs · the whole SKILL.md, loaded when a task matches: ~963

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 Hello-QM/catgo-LRG at commit fd6291b, republished under its AGPL-3.0 licence (© Hello-QM). 303 words, ~963 tokens.

Download SKILL.mdSave it as .claude/skills/abinit/SKILL.md (or your agent's skills folder).

name: abinit
description: Generate and manage ABINIT DFT calculations. Use when the user requests ABINIT, or needs DFPT phonons, GW calculations, or BSE optical spectra.
compatibility: Requires ABINIT installed on the HPC target. Pseudopotential files (PAW JTH or norm-conserving) must be available.

ABINIT

When to Use

User explicitly requests ABINIT
User needs DFPT (density-functional perturbation theory) phonons natively
User needs GW quasiparticle calculations or BSE optical spectra
User wants multi-dataset calculations in a single input file

Prerequisites

ABINIT binaries accessible on HPC (abinit --version)
Pseudopotentials available (JTH PAW or PseudoDojo NC recommended)
Structure loaded in viewer — verify with catgo_view(action="get_state")

Workflow Steps

1. Verify structure

catgo_view(action="get_state")

2. Create workflow

catgo_workflow_engine(action="create", params={"name": "ABINIT GW band gap"})

3. Add ABINIT task via shell

CatGo does not yet have a native ABINIT engine. Use task_type: "shell".

catgo_workflow_engine(action="add_task", params={
  "workflow_id": "wf_xxx",
  "task_type": "shell",
  "name": "abinit_scf",
  "command": "abinit < abinit.files > abinit.log 2>&1",
  "input_files": {
    "abinit.in": "<input content>",
    "abinit.files": "<files file content>"
  },
  "system_name": "Si_GW"
})

When a @register_engine("abinit") is added, use task_type: "geo_opt" with software: "abinit".

Input File Template — SCF

# SCF ground state
ndtset 1

# System
natom  <natoms>
ntypat <ntypes>
typat  <type_list>
znucl  <Z_list>

acell  3*1.0
rprim
  <a1x> <a1y> <a1z>
  <a2x> <a2y> <a2z>
  <a3x> <a3y> <a3z>

xred
  <x1> <y1> <z1>
  <x2> <y2> <z2>

# Plane-wave basis
ecut    40.0    # Ha (= 2x Ry)
pawecutdg 80.0  # PAW fine grid

# K-points
ngkpt   <k1> <k2> <k3>
nshiftk 1
shiftk  0.0 0.0 0.0

# SCF
nstep   100
toldfe  1.0d-8   # Ha

# Smearing
occopt  3        # Fermi-Dirac
tsmear  0.002    # Ha (~0.05 eV)

# XC
ixc     11       # PBE

The .files File

ABINIT uses a .files file listing input/output/pseudo paths:

abinit.in
abinit.out
abiniti
abinito
abinit_tmp
pseudo/Si.paw

Lines: input, output, root_input, root_output, tmp_dir, then one pseudo per atom type.

Parameter Guidance

Parameter	Typical value	Notes
ecut	30-50 Ha	In Hartree (1 Ha = 27.2 eV); check pseudo recommendations
pawecutdg	2x ecut	PAW augmentation grid; only for PAW pseudos
toldfe	1.0d-8	Energy convergence in Ha
toldff	1.0d-5	Force convergence in Ha/Bohr (for relaxation)
ngkpt	auto from cell	Monkhorst-Pack grid
occopt	3 (FD) or 7 (Gaussian)	Smearing type
ionmov	2 (BFGS)	Ion relaxation algorithm
optcell	0 (ions) / 2 (full)	Cell optimization level

Multi-Dataset Calculations

ABINIT supports chaining calculations in one input via ndtset:

ndtset 3

# Dataset 1: SCF
toldfe1 1.0d-8

# Dataset 2: NSCF for DOS
iscf2    -2
tolwfr2  1.0d-12
getden2  1

# Dataset 3: DFPT phonons
rfphon3  1
nqpt3    1
qpt3     0.0 0.0 0.0
toldfe3  1.0d-10
getden3  1
getwfk3  1

Common Pitfalls

ecut in Hartree, not eV — ABINIT uses Hartree (1 Ha = 27.2 eV). A 40 Ha cutoff is ~1088 eV.
Coordinates default to reduced (xred) — use xred (fractional) or xcart (Bohr). Not Angstrom.
Missing .files file — ABINIT reads file paths from stdin or a .files file; forgetting it causes silent failure
PAW augmentation grid — if using PAW pseudos, pawecutdg must be set (typically 2x ecut)
GW convergence — GW calculations need many empty bands (nband) and careful ecuteps convergence
Large tmp files — ABINIT writes wave functions to _TMP; ensure sufficient disk space

Files

Just SKILL.md in .claude/skills/abinit of Hello-QM/catgo-LRG.

Open the folder on GitHubat commit fd6291b

Compare with similar skills

Abinit 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.

Abinit compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Abinit this skillHello-QM/catgo-LRG	205	—	~963	Automated safety check: Pass	AGPL-3.0	16 days ago
Eol Resistor Calculatorsickn33/agentic-awesome-skills	47k	1 repos	~3.5k	Automated safety check: Pass	MIT	today
Dft Abinitjinzhezenggroup/computational-chemistry-agent-skills	148	—	~585	Automated safety check: Pass	MIT	today
Metric Calculatorjeremylongshore/tons-of-skills-marketplace	2.8k	—	~563	Automated safety check: Pass	MIT	today
Retention Calculatorjeremylongshore/tons-of-skills-marketplace	2.8k	—	~573	Automated safety check: Pass	MIT	today
Throughput Calculatorjeremylongshore/tons-of-skills-marketplace	2.8k	—	~577	Automated safety check: Pass	MIT	today

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Questions about Abinit

What does Abinit do?

Generate and manage ABINIT DFT calculations. An agent skill from Hello-QM/catgo-LRG. Abinit is an agent skill from Hello-QM/catgo-LRG. Generate and manage ABINIT DFT calculations.

When should I use Abinit?

Abinit fits situations like: the user requests ABINIT; needs DFPT phonons; GW calculations; BSE optical spectra.

How do I install Abinit in Claude Code?

Run `npx skills add Hello-QM/catgo-LRG --skill abinit -a claude-code`. Or copy the skill folder (.claude/skills/abinit in Hello-QM/catgo-LRG) into .claude/skills/abinit in your project. Claude Code loads it when a task matches its description.

How do I install Abinit in Codex?

Run `npx skills add Hello-QM/catgo-LRG --skill abinit -a codex`. Or copy the skill folder (.claude/skills/abinit in Hello-QM/catgo-LRG) into .agents/skills/abinit in your project. Codex loads it when a task matches its description.

Can I use Abinit 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 Hello-QM/catgo-LRG --skill abinit -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/abinit, .gemini/skills/abinit, .github/skills/abinit and .opencode/skills/abinit in your project.

What does Abinit need to run?

SKILL.md names no scripts, command-line tools or credentials: Abinit is instructions for the agent only. Compatibility (from SKILL.md): Requires ABINIT installed on the HPC target. Pseudopotential files (PAW JTH or norm-conserving) must be available. .

Does Abinit 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 Abinit 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 Abinit use?

Abinit is published under the AGPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Abinit use?

About 963 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.

What are the alternatives to Abinit?

Skills that share tags, products or a category with Abinit: Eol Resistor Calculator (sickn33/agentic-awesome-skills, 47k stars), Dft Abinit (jinzhezenggroup/computational-chemistry-agent-skills, 148 stars), Metric Calculator (jeremylongshore/tons-of-skills-marketplace, 2.8k stars) and Retention Calculator (jeremylongshore/tons-of-skills-marketplace, 2.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Abinit?

Hello-QM (a GitHub user) maintains it in Hello-QM/catgo-LRG, which has 205 GitHub stars. The repository holds 75 skills in this directory. The repository was last updated on September 22, 2026.

Source: Hello-QM/catgo-LRG on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Abinit

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Compatibility

Context cost

Safety

SKILL.md

ABINIT

When to Use

Prerequisites

Workflow Steps

1. Verify structure

2. Create workflow

3. Add ABINIT task via shell

Input File Template — SCF

The .files File

Parameter Guidance

Multi-Dataset Calculations

Common Pitfalls

Files

Compare with similar skills

Similar skills

More from Hello-QM/catgo-LRG

Questions about Abinit