Eol Resistor Calculator
sickn33/agentic-awesome-skills
Calculates and validates end-of-line (EOL, SEOL, DEOL, TEOL) resistor loops for intrusion alarm panels (Honeywell, DSC, Paradox, Bosch) with wire gauge drop and state tables.
VASP band structure calculation. An agent skill from Hello-QM/catgo-LRG.
$ npx skills add Hello-QM/catgo-LRG --skill vasp-band -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Hello-QM/catgo-LRG vasp-band --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/Hello-QM/catgo-LRG.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/vasp-band .claude/skills/vasp-band && 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 "vasp-band" agent skill from https://github.com/Hello-QM/catgo-LRG/tree/main/.claude/skills/vasp-band into .claude/skills/vasp-band/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vasp-band", 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/Hello-QM/catgo-LRG/tree/main/.claude/skills/vasp-bandType 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 Hello-QM/catgo-LRG --skill vasp-band -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Hello-QM/catgo-LRG vasp-band --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Hello-QM/catgo-LRG.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/vasp-band .agents/skills/vasp-band && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "vasp-band" agent skill from https://github.com/Hello-QM/catgo-LRG/tree/main/.claude/skills/vasp-band into .agents/skills/vasp-band/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vasp-band", 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 Hello-QM/catgo-LRG --skill vasp-band -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Hello-QM/catgo-LRG vasp-band --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Hello-QM/catgo-LRG.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/vasp-band .cursor/skills/vasp-band && 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 "vasp-band" agent skill from https://github.com/Hello-QM/catgo-LRG/tree/main/.claude/skills/vasp-band into .cursor/skills/vasp-band/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vasp-band", 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/Hello-QM/catgo-LRG.git --path .claude/skills/vasp-band--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 Hello-QM/catgo-LRG --skill vasp-band -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Hello-QM/catgo-LRG vasp-band --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Hello-QM/catgo-LRG.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/vasp-band .gemini/skills/vasp-band && 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 "vasp-band" agent skill from https://github.com/Hello-QM/catgo-LRG/tree/main/.claude/skills/vasp-band into .gemini/skills/vasp-band/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vasp-band", 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 Hello-QM/catgo-LRG vasp-bandInstalls 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 Hello-QM/catgo-LRG --skill vasp-band -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Hello-QM/catgo-LRG.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/vasp-band .github/skills/vasp-band && 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 "vasp-band" agent skill from https://github.com/Hello-QM/catgo-LRG/tree/main/.claude/skills/vasp-band into .github/skills/vasp-band/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vasp-band", 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 Hello-QM/catgo-LRG --skill vasp-band -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Hello-QM/catgo-LRG vasp-band --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Hello-QM/catgo-LRG.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/vasp-band .opencode/skills/vasp-band && 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 "vasp-band" agent skill from https://github.com/Hello-QM/catgo-LRG/tree/main/.claude/skills/vasp-band into .opencode/skills/vasp-band/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vasp-band", 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.
vasp-bandVASP band structure calculation. An agent skill from Hello-QM/catgo-LRG.
Vasp Band is an agent skill from Hello-QM/catgo-LRG. VASP band structure calculation. Two-step workflow with SCF charge density followed by non-SCF band calculation along high-symmetry k-path.
Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
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.
2 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit fd6291b. 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.
No scripts in the folder and no shell commands in SKILL.md (its code samples are python).
From 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.
Vasp Band loads about 1.7k tokens when it runs. Until then it costs about 37 tokens; SKILL.md has 320 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 Hello-QM/catgo-LRG at commit fd6291b, republished under its AGPL-3.0 licence (© Hello-QM). 320 words, ~1,657 tokens.
.claude/skills/vasp-band/SKILL.md (or your agent's skills folder).Compute electronic band structure along high-symmetry k-point paths. Requires a two-step process: self-consistent charge density, then non-SCF calculation along the k-path.
This separation is necessary because the high-symmetry k-path does not provide uniform Brillouin zone sampling needed for SCF convergence.
from catgo.workflow import Workflow
from catgo.workflow.builtins import geo_opt, single_point
wf = Workflow("TiO2 band structure")
struct = wf.add_task("structure_input", structure=structure_json)
# Step 1: Optimize (skip if already relaxed)
opt = wf.add_task(geo_opt, structure=struct.output.structure,
ISIF=3, system_name="relax")
# Step 2: SCF single point to generate CHGCAR
scf = wf.add_task(single_point, structure=opt.output.structure,
LCHARG=True, # Write CHGCAR
EDIFF=1e-6, # Tight convergence
system_name="SCF")
# Step 3: Non-SCF band calculation
band = wf.add_task(single_point, structure=opt.output.structure,
ICHARG=11, # Read CHGCAR, do not update
LORBIT=11, # Projected band character
LCHARG=False,
LWAVE=False,
kpath_mode="auto", # Auto-detect high-symmetry path
kpath_density=40, # Points per segment
system_name="bands")
wf.submit()catgo_workflow_engine(action="create", params={"name": "Band structure"})
# Input structure
catgo_workflow_engine(action="add_task", params={
"workflow_id": "wf_xxx",
"task_type": "structure_input",
"structure": "<json>"
})
# SCF single point
catgo_workflow_engine(action="add_task", params={
"workflow_id": "wf_xxx",
"task_type": "single_point",
"software": "vasp",
"structure": "{{t_001.output.structure}}",
"LCHARG": true,
"EDIFF": 1e-6,
"system_name": "SCF"
})
# Non-SCF band calculation
catgo_workflow_engine(action="add_task", params={
"workflow_id": "wf_xxx",
"task_type": "single_point",
"software": "vasp",
"structure": "{{t_001.output.structure}}",
"ICHARG": 11,
"LORBIT": 11,
"kpath_mode": "auto",
"kpath_density": 40,
"system_name": "bands"
})
catgo_workflow_engine(action="submit", params={"workflow_id": "wf_xxx"})Set kpath_mode="auto" to let the engine detect the Bravais lattice and generate the standard k-path. This works for most crystal systems.
For custom paths, specify k-points explicitly:
band = wf.add_task(single_point, structure=opt.output.structure,
ICHARG=11,
kpath_mode="manual",
kpath_points={
"G": [0.0, 0.0, 0.0],
"X": [0.5, 0.0, 0.0],
"M": [0.5, 0.5, 0.0],
"G2": [0.0, 0.0, 0.0],
"R": [0.5, 0.5, 0.5],
},
kpath_segments=["G-X", "X-M", "M-G2", "G2-R"],
kpath_density=40,
system_name="bands")| System | Path | Example |
|---|---|---|
| FCC | G-X-W-K-G-L-U-W-L-K | Cu, Al, Pt |
| BCC | G-H-N-G-P-H | Fe, W, Cr |
| HCP | G-M-K-G-A-L-H-A | Ti, Ru, Co |
| Tetragonal | G-X-M-G-Z-R-A-Z | TiO2 rutile |
| Simple cubic | G-X-M-G-R-X | SrTiO3 |
| Parameter | Value | Purpose |
|---|---|---|
| ICHARG | 11 | Read CHGCAR, non-self-consistent |
| LORBIT | 11 | Atom- and orbital-projected bands |
| NBANDS | auto | Number of bands (increase for unoccupied states) |
| LCHARG | False | Do not overwrite CHGCAR from SCF step |
| LWAVE | False | Do not write WAVECAR (saves disk) |
| kpath_density | 40 | K-points per segment (more = smoother bands) |
For magnetic systems:
scf = wf.add_task(single_point, structure=s,
LCHARG=True, ISPIN=2,
MAGMOM="2*5.0 4*0.6",
system_name="SCF_spin")
band = wf.add_task(single_point, structure=s,
ICHARG=11, ISPIN=2, LORBIT=11,
kpath_mode="auto", kpath_density=40,
system_name="bands_spin")HSE06 band structure is expensive but more accurate for band gaps:
scf = wf.add_task(single_point, structure=s,
LCHARG=True, LHFCALC=True, HFSCREEN=0.2,
AEXX=0.25, ALGO="Damped", TIME=0.4,
system_name="SCF_HSE")
band = wf.add_task(single_point, structure=s,
ICHARG=11, LHFCALC=True, HFSCREEN=0.2,
AEXX=0.25, ALGO="Damped", TIME=0.4,
kpath_mode="auto", kpath_density=20,
system_name="bands_HSE")Note: HSE band calculations are 10-100x more expensive than PBE. Use a lower kpath_density (20) and fewer NBANDS.
Run both from the same SCF calculation:
scf = wf.add_task(single_point, structure=opt.output.structure,
LCHARG=True, EDIFF=1e-6, system_name="SCF")
# DOS branch
dos_sp = wf.add_task(single_point, structure=opt.output.structure,
ISMEAR=-5, NEDOS=3001, LORBIT=11,
system_name="DOS")
# Band branch
band = wf.add_task(single_point, structure=opt.output.structure,
ICHARG=11, LORBIT=11,
kpath_mode="auto", kpath_density=40,
system_name="bands")| Problem | Fix |
|---|---|
| Bands look wrong / discontinuous | CHGCAR from SCF may be on different k-mesh. Ensure SCF used uniform mesh |
| Band gap too small (PBE) | Expected — PBE underestimates gaps. Use HSE06 for accurate gaps |
| Missing unoccupied bands | Increase NBANDS (default may cut off conduction bands) |
| ICHARG=11 error | CHGCAR must exist from SCF step. Check SCF completed with LCHARG=True |
| Very slow HSE | Normal — reduce kpath_density, reduce NBANDS, use more nodes |
© Hello-QM, AGPL-3.0. 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 .claude/skills/vasp-band of Hello-QM/catgo-LRG.
Open the folder on GitHubat commit fd6291b
Vasp Band 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 |
|---|---|---|---|---|---|---|
| Vasp Band this skillHello-QM/catgo-LRG | 205 | — | ~1.7k | Automated safety check: Pass | AGPL-3.0 | |
| Eol Resistor Calculatorsickn33/agentic-awesome-skills | 47k | 1 repos | ~3.5k | Automated safety check: Pass | MIT | |
| Bandjinzhezenggroup/computational-chemistry-agent-skills | 148 | — | ~411 | Automated safety check: Pass | LGPL-3.0-or-later | |
| Metric Calculatorjeremylongshore/tons-of-skills-marketplace | 2.8k | — | ~563 | Automated safety check: Pass | MIT | |
| Retention Calculatorjeremylongshore/tons-of-skills-marketplace | 2.8k | — | ~573 | Automated safety check: Pass | MIT | |
| Throughput Calculatorjeremylongshore/tons-of-skills-marketplace | 2.8k | — | ~577 | Automated safety check: Pass | MIT |
sickn33/agentic-awesome-skills
Calculates and validates end-of-line (EOL, SEOL, DEOL, TEOL) resistor loops for intrusion alarm panels (Honeywell, DSC, Paradox, Bosch) with wire gauge drop and state tables.
jinzhezenggroup/computational-chemistry-agent-skills
Prepare VASP band-structure workflow inputs from existing SCF context and user-specified band-path settings.
jeremylongshore/tons-of-skills-marketplace
Configure and manage - Calculate metric calculator operations.
jeremylongshore/tons-of-skills-marketplace
Configure and manage - Calculate retention calculator operations.
jeremylongshore/tons-of-skills-marketplace
Calculate throughput calculator operations. An agent skill from jeremylongshore/tons-of-skills-marketplace.
Code-and-Sorts/awesome-copilot-agents
Performs arbitrary-precision arithmetic calculations including addition, subtraction, multiplication, division, and exponents.
Hello-QM/catgo-LRG
Drive a file-first, agent-in-the-loop computational campaign via a folder + markdown tree (no DB).
Hello-QM/catgo-LRG
Compute adsorption/reaction Gibbs free energies, free-energy diagrams, and electrochemical overpotentials (HER/ORR/OER/CO2RR/NRR) with VASP.
Hello-QM/catgo-LRG
Generate and manage ABINIT DFT calculations. An agent skill from Hello-QM/catgo-LRG.
Hello-QM/catgo-LRG
A skill your agent uses when the user asks to place an adsorbate molecule on a surface, find adsorption sites, or set up a surface+adsorbate model for DFT.
Hello-QM/catgo-LRG
A skill your agent uses when the user asks for adsorption energy, binding energy, or wants to compare how strongly a molecule binds to a surface.
Hello-QM/catgo-LRG
A skill your agent uses when the user asks to analyze computational results: Gibbs free energy, OER/HER/CO2RR overpotentials, adsorption energy, convergence tests, DOS/d-band analysis, or Bader…
VASP band structure calculation. An agent skill from Hello-QM/catgo-LRG. Vasp Band is an agent skill from Hello-QM/catgo-LRG. VASP band structure calculation.
Run `npx skills add Hello-QM/catgo-LRG --skill vasp-band -a claude-code`. Or copy the skill folder (.claude/skills/vasp-band in Hello-QM/catgo-LRG) into .claude/skills/vasp-band in your project. Claude Code loads it when a task matches its description.
Run `npx skills add Hello-QM/catgo-LRG --skill vasp-band -a codex`. Or copy the skill folder (.claude/skills/vasp-band in Hello-QM/catgo-LRG) into .agents/skills/vasp-band 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 Hello-QM/catgo-LRG --skill vasp-band -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/vasp-band, .gemini/skills/vasp-band, .github/skills/vasp-band and .opencode/skills/vasp-band in your project.
SKILL.md names no scripts, command-line tools or credentials: Vasp Band is instructions for the agent only. 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. Review the folder before installing.
Vasp Band 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.
About 1.7k tokens (SKILL.md is roughly 6.6k 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 Vasp Band: Eol Resistor Calculator (sickn33/agentic-awesome-skills, 47k stars), Band (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.
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.