New: 98,000+ skills indexed from GitHub repos with 100+ stars · every skill safety-checkedBrowse top skillsTop skills
Esc to closeBrowse all skills
Submit a skillBrowse skills
Submit a skillBrowse skills

Agent skill

Mattergen Structure Generation

by Tai609 in Tai609/NebulaMat

Generate auditable candidate crystal structures with the project's pinned MatterGen runtime, including request construction, model/conditioning selection, GPU-cost bounds, workspace-safe output…

Custom licenceAuto-check passedResearch & Science

Install Mattergen Structure Generation

skills CLI
$ npx skills add Tai609/NebulaMat --skill mattergen-structure-generation -a claude-code

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

GitHub CLI
$ gh skill install Tai609/NebulaMat mattergen-structure-generation --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/Tai609/NebulaMat.git skills-src && mkdir -p .claude/skills && cp -r skills-src/runtime/skills-bundle/mattergen-structure-generation .claude/skills/mattergen-structure-generation && 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
mattergen-structure-generation
GitHub stars
100
Token cost
~1.9k tokens
SKILL.md length
895 words
Files
3 (incl. references)
Skills in repo
15
Repo updated
First seen
Licence
Custom licence

At a glance

Generate auditable candidate crystal structures with the project's pinned MatterGen runtime, including request construction, model/conditioning selection, GPU-cost bounds, workspace-safe output…

  • Works in 8 steps: Classify the request. Distinguish… → Complete and review parameters. Read… → Create a workspace-local request. Write… → …
  • A user asks to generate
  • SKILL.md covers Workflow, Parameter Rules, Selection Guide and Failure Handling
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Mattergen Structure Generation is an agent skill from Tai609/NebulaMat. Generate auditable candidate crystal structures with the project's pinned MatterGen runtime, including request construction, model/conditioning selection, GPU-cost bounds, workspace-safe output, dry-run preflight, CIF/hash checks, and manifest-backed standardization. Use whenever a user asks to generate, sample, design, or propose crystal/material structures with MatterGen or asks for a new inorganic crystal structure.

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `agents/openai.yaml` and `references/parameter-policy.md`).

It sits in Research & Science, covering Physical and earth sciences. The repository describes itself as: NebulaMat scientific materials research workbench.

When your agent uses it

  • A user asks to generate
  • Propose crystal/material structures with MatterGen
  • Asks for a new inorganic crystal structure

Example prompts

  • “/mattergen-structure-generation”

Workflow steps

8 steps, taken from the first numbered list in SKILL.md.

  1. Classify the request. Distinguish candidate bulk generation, exact-formula crystal structure prediction (CSP), and surface/adsorption…
  2. Complete and review parameters. Read parameter policy. Ask for missing chemistry, model, sample count, or output intent, or use the…
  3. Create a workspace-local request. Write a unique materials/design//mattergen/request.json in the active session workspace. Use schema…
  4. Run preflight first. Use the runner named by NEBULAMAT_MATTERGEN_RUNNER
  5. Check the runtime before sampling. If the desktop-managed environment is not ready, follow the project AGENTS.md read-only WSL2 probe…
  6. Execute the same request. Remove --dry-run only after preflight and environment checks pass. Do not overwrite a non-empty output…
  7. Audit the result. Read mattergen-run.json and verify status=completed, upstream revision, model, requested sample count, artifact count…
  8. Pass on standardized structures only. Raw MatterGen CIFs are provenance/candidate inputs and must not go directly to MatterSim, UMA, or…

What it can do on your machine

Read from SKILL.md and the folder at commit c906ed5. 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.

Context cost

Mattergen Structure Generation loads about 1.9k tokens when it runs, and up to ~2.9k if it reads all its reference files. Until then it costs about 113 tokens; SKILL.md has 895 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~113
When it runs · the whole SKILL.md, loaded when a task matches
~1.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.9k

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

Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 895 words (~1,853 tokens).

“Treat MatterGen as a candidate-structure generator, not as evidence of stability, synthesizability, or experimental performance. Every generation request must use the project runner and retain the request, run manifest, raw CIFs, standardized structures, and SHA-256 hashes. Do not call the…”

— opening of SKILL.md by Tai609, Custom licence
name
mattergen-structure-generation

Read the full SKILL.md on GitHub

Files

SKILL.md and 2 other files (references) in runtime/skills-bundle/mattergen-structure-generation of Tai609/NebulaMat.

  • SKILL.md
  • agents/openai.yaml
  • references/parameter-policy.md

Open the folder on GitHubat commit c906ed5

Compare with similar skills

Mattergen Structure Generation 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.

Mattergen Structure Generation compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Mattergen Structure Generation this skillTai609/NebulaMat100—~1.9kAutomated safety check: PassCustom licence
AstropyzLanqing/codex-claude-academic-skills4.7k13 repos~2.9kAutomated safety check: PassBSD-3-Clause
PymatgenzLanqing/codex-claude-academic-skills4.7k11 repos~5kAutomated safety check: PassMIT
Cantera Ignition DelayK-Dense-AI/scientific-agent-skills48k1 repos~2.2kAutomated safety check: PassMIT
Weathertrpc-group/trpc-agent-go1.9k8 repos~591Automated safety check: PassApache-2.0
Pymol VisualizationChatMol/ChatMol373—~1.2kAutomated safety check: PassMIT

Similar skills

  • Astropy

    zLanqing/codex-claude-academic-skills

    Comprehensive Python library for astronomy and astrophysics.

    4.7k GitHub starsUsed in 13 repos~2.9k tokens
    Research & ScienceAuto-check passed

  • Pymatgen

    zLanqing/codex-claude-academic-skills

    Materials science toolkit. An agent skill from zLanqing/codex-claude-academic-skills.

    4.7k GitHub starsUsed in 11 repos~5k tokens
    Research & ScienceAuto-check passed

  • Cantera Ignition Delay

    K-Dense-AI/scientific-agent-skills

    Runs Cantera constant-volume or constant-pressure ignition simulations and reports temperature-based ignition delay with mechanism provenance and checks.

    48k GitHub starsUsed in 1 repo~2.2k tokens
    Research & ScienceAuto-check passed

  • Weather

    trpc-group/trpc-agent-go

    Get current weather and forecasts via wttr.in or Open-Meteo.

    1.9k GitHub starsUsed in 8 repos~591 tokens
    Research & ScienceAuto-check passed

  • Pymol Visualization

    ChatMol/ChatMol

    Generate publication-quality molecular visualization images using PyMOL.

    373 GitHub stars~1.2k tokensUpdated 6 mo ago
    Research & ScienceAuto-check passed

  • Review

    Muuuun/luxas

    Write domain-authentic review articles that synthesize rather than stack.

    1.2k GitHub stars~2.1k tokensUpdated 1 mo ago
    Research & ScienceAuto-check passed

More from Tai609/NebulaMat

All 15 skills in this repo

  • Image OCR

    Tai609/NebulaMat

    Read and transcribe the text visible inside an image file (PNG/JPG/JPEG/WebP/BMP/GIF) using the built-in Windows Media.Ocr OCR engine, with NO external credential or network required.

    100 GitHub stars~1.1k tokensUpdated 1 mo ago
    Auto-check passed

  • Nature Figure

    Tai609/NebulaMat

    Create, revise, audit, and export submission-grade scientific figures for Nature-family and other high-impact venues in Python (matplotlib/seaborn) or R (ggplot2/patchwork/ComplexHeatmap), including…

    100 GitHub stars~1.9k tokensUpdated 1 mo ago
    Auto-check passed

  • Aris Proof Orchestrator

    Tai609/NebulaMat

    Manage a stateful, run-directory-based proof project with Codex: continuation across runs, run-local source bookkeeping, manual GPT Pro handoff packages when a local attempt stalls, and an optional…

    100 GitHub stars~5k tokensUpdated 1 mo ago
    Auto-check passed

  • Electrochemical Adsorption Model Construction

    Tai609/NebulaMat

    Build provenance-controlled facet-specific electrochemical adsorption model cohorts from MatterGen candidates after MatterSim relaxation, including slab terminations, adsorption sites and…

    100 GitHub stars~2.7k tokensUpdated 1 mo ago
    Auto-check passed

  • Mattersim Relaxation Screening

    Tai609/NebulaMat

    Run governed MatterSim-v1.0.0-5M energy, force, stress, and optional ASE FIRE relaxation for workspace-local standardized structures.

    100 GitHub stars~1.6k tokensUpdated 1 mo ago
    Auto-check passed

  • Nature Academic Search

    Tai609/NebulaMat

    Multi-source literature search, citation verification, strict independent other-citation audits, article-level citation metric tables, influential citer profiling with citation-context extraction…

    100 GitHub stars~1.2k tokensUpdated 1 mo ago
    Auto-check passed

Categories

Questions about Mattergen Structure Generation

What does Mattergen Structure Generation do?

Generate auditable candidate crystal structures with the project's pinned MatterGen runtime, including request construction, model/conditioning selection, GPU-cost bounds, workspace-safe output…. Mattergen Structure Generation is an agent skill from Tai609/NebulaMat. Generate auditable candidate crystal structures with the project's pinned MatterGen runtime, including request construction, model/conditioning selection, GPU-cost bounds, workspace-safe output, dry-run preflight, CIF/hash checks, and manifest-backed standardization.

When should I use Mattergen Structure Generation?

Mattergen Structure Generation fits situations like: A user asks to generate; propose crystal/material structures with MatterGen; asks for a new inorganic crystal structure.

How do I install Mattergen Structure Generation in Claude Code?

Run `npx skills add Tai609/NebulaMat --skill mattergen-structure-generation -a claude-code`. Or copy the skill folder (runtime/skills-bundle/mattergen-structure-generation in Tai609/NebulaMat) into .claude/skills/mattergen-structure-generation in your project. Claude Code loads it when a task matches its description.

How do I install Mattergen Structure Generation in Codex?

Run `npx skills add Tai609/NebulaMat --skill mattergen-structure-generation -a codex`. Or copy the skill folder (runtime/skills-bundle/mattergen-structure-generation in Tai609/NebulaMat) into .agents/skills/mattergen-structure-generation in your project. Codex loads it when a task matches its description.

Can I use Mattergen Structure Generation 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 Tai609/NebulaMat --skill mattergen-structure-generation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/mattergen-structure-generation, .gemini/skills/mattergen-structure-generation, .github/skills/mattergen-structure-generation and .opencode/skills/mattergen-structure-generation in your project.

What does Mattergen Structure Generation need to run?

SKILL.md names no scripts, command-line tools or credentials: Mattergen Structure Generation is instructions for the agent only.

Does Mattergen Structure Generation 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 Mattergen Structure Generation 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 Mattergen Structure Generation use?

Mattergen Structure Generation has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.

How many tokens does Mattergen Structure Generation use?

About 1.9k tokens (SKILL.md is roughly 7.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1k tokens, read only when the agent opens those files.

What are the alternatives to Mattergen Structure Generation?

Skills that share tags, products or a category with Mattergen Structure Generation: Astropy (zLanqing/codex-claude-academic-skills, 4.7k stars), Pymatgen (zLanqing/codex-claude-academic-skills, 4.7k stars), Cantera Ignition Delay (K-Dense-AI/scientific-agent-skills, 48k stars) and Weather (trpc-group/trpc-agent-go, 1.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Mattergen Structure Generation?

Tai609 (a GitHub user) maintains it in Tai609/NebulaMat, which has 100 GitHub stars. The repository holds 15 skills in this directory. The repository was last updated on September 6, 2026.

Source: Tai609/NebulaMat on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.