SQL Optimization
github/awesome-copilot
Universal SQL performance optimization assistant for comprehensive query tuning, indexing strategies, and database performance analysis across all SQL databases (MySQL, PostgreSQL, SQL Server…
Predict thermodynamically optimal solid-state inorganic synthesis pathways and tabulates basic reactions.
MITAuto-check passed
Install Mat Reaction Network
$ npx skills add learningmatter-mit/AtomisticSkills --skill mat-reaction-network -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install learningmatter-mit/AtomisticSkills mat-reaction-network --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/learningmatter-mit/AtomisticSkills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/mat-reaction-network .claude/skills/mat-reaction-network && 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 "mat-reaction-network" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/mat-reaction-network into .claude/skills/mat-reaction-network/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mat-reaction-network", 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/learningmatter-mit/AtomisticSkills/tree/main/skills/mat-reaction-networkType 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 learningmatter-mit/AtomisticSkills --skill mat-reaction-network -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install learningmatter-mit/AtomisticSkills mat-reaction-network --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/learningmatter-mit/AtomisticSkills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/mat-reaction-network .agents/skills/mat-reaction-network && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "mat-reaction-network" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/mat-reaction-network into .agents/skills/mat-reaction-network/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mat-reaction-network", 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 learningmatter-mit/AtomisticSkills --skill mat-reaction-network -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install learningmatter-mit/AtomisticSkills mat-reaction-network --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/learningmatter-mit/AtomisticSkills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/mat-reaction-network .cursor/skills/mat-reaction-network && 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 "mat-reaction-network" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/mat-reaction-network into .cursor/skills/mat-reaction-network/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mat-reaction-network", 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/learningmatter-mit/AtomisticSkills.git --path skills/mat-reaction-network--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 learningmatter-mit/AtomisticSkills --skill mat-reaction-network -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install learningmatter-mit/AtomisticSkills mat-reaction-network --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/learningmatter-mit/AtomisticSkills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/mat-reaction-network .gemini/skills/mat-reaction-network && 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 "mat-reaction-network" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/mat-reaction-network into .gemini/skills/mat-reaction-network/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mat-reaction-network", 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 learningmatter-mit/AtomisticSkills mat-reaction-networkInstalls 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 learningmatter-mit/AtomisticSkills --skill mat-reaction-network -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/learningmatter-mit/AtomisticSkills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/mat-reaction-network .github/skills/mat-reaction-network && 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 "mat-reaction-network" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/mat-reaction-network into .github/skills/mat-reaction-network/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mat-reaction-network", 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 learningmatter-mit/AtomisticSkills --skill mat-reaction-network -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install learningmatter-mit/AtomisticSkills mat-reaction-network --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/learningmatter-mit/AtomisticSkills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/mat-reaction-network .opencode/skills/mat-reaction-network && 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 "mat-reaction-network" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/mat-reaction-network into .opencode/skills/mat-reaction-network/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mat-reaction-network", 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
mat-reaction-network- GitHub stars
- 175
- Token cost
- ~833 tokens
- SKILL.md length
- 289 words
- Files
- 12 (incl. scripts)
- Skills in repo
- 129
- Repo updated
- First seen
- Licence
- MIT
At a glance
Predict thermodynamically optimal solid-state inorganic synthesis pathways and tabulates basic reactions.
- Works in 2 steps: Reaction Enumeration → Pathfinding and Solving Syntheses
- SKILL.md covers Goal, Instructions, Examples and Constraints, plus 1 more section
- Runs Shell and Python scripts from its folder
What it does
Mat Reaction Network is an agent skill from learningmatter-mit/AtomisticSkills. Predict thermodynamically optimal solid-state inorganic synthesis pathways and tabulates basic reactions.
Its SKILL.md is about 830 tokens, which your agent loads only when the skill is triggered. The skill folder holds 15 other files, including scripts (for example `examples/1_predict_liznpo4/README.md`, `examples/1_predict_liznpo4/pair_a_output.json` and `examples/1_predict_liznpo4/pair_b_output.json`).
The repository describes itself as: Integrating AtomisticSkills into Agentic IDEs (Cursor, Claude Code, Codex, Google Antigravity, Hermes Agent, etc). The licence is MIT.
Example prompts
- “/mat-reaction-network”
Requirements
- Python 3
- A Bash shell
Workflow steps
2 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 7f2d86d. 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
Ships 2 files in scripts/ (Shell and Python), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
doi.orggithub.com
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
Mat Reaction Network loads about 833 tokens when it runs. Until then it costs about 32 tokens; SKILL.md has 289 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.
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); the scripts in this folder are not scanned.
SKILL.md
The full file from learningmatter-mit/AtomisticSkills at commit 7f2d86d, republished under its MIT licence (© learningmatter-mit). 289 words, ~833 tokens.
Download SKILL.mdSave it as
.claude/skills/mat-reaction-network/SKILL.md (or your agent's skills folder). This skill also uses 11 other files; get the full folder from GitHub.- name
- mat-reaction-network
- description
- Predict thermodynamically optimal solid-state inorganic synthesis pathways and tabulates basic reactions.
- metadata.category
- materials
- metadata.venv
- cpu
Material Reaction Network Prediction
Goal
To predict the optimal sequence of thermodynamically favorable chemical reactions (pathways) needed to synthesize a target generic solid-state material from a set of starting precursors. This skill enumerates large, competitive reaction networks and solves for minimum-energy paths using the materialsproject/reaction-network code and Materials Project API thermodynamics data.
Instructions
1. Reaction Enumeration
Explore the landscape of competing reactions within a specific chemical system by explicitly generating balanced equations.
${CLAUDE_SKILL_DIR}/../../venv/run cpu python ${CLAUDE_SKILL_DIR}/scripts/enumerate_reactions.py --chemsys Ba-Ti-O --enumerator-type basic_open --open-phases O2 --temperature 1000 --limit 10--chemsys: The chemical system to restrict search to.--enumerator-type: The algorithm used to propose reactions (basic,basic_open,minimize_gibbs,minimize_grand_potential).--open-phases: (Specific tobasic_open) allow materials to be freely consumed or produced from an infinite reservoir (like environmental O2).--temperature: Synthesis temperature (Kelvin), affects Gibbs adjustments.--limit: Maximum number of elementary reactions to print.
2. Pathfinding and Solving Syntheses
To resolve a complete list of step-by-step reactions that convert specific starting precursors into a target compound, use the pathway solver script.
${CLAUDE_SKILL_DIR}/../../venv/run cpu python ${CLAUDE_SKILL_DIR}/scripts/find_pathways.py --target BaTiO3 --precursors BaO TiO2 --temperature 1000 --k-paths 5--target: The desired final functional material.--precursors: One or more starting materials (e.g., oxides or carbonates).--byproducts: Optional allowed volatile byproducts (e.g.,CO2,H2O) escaping into the atmosphere.--k-paths: Number of different candidate elementary pathways to yield.
Examples
Finding pathways to synthesize Yttrium Manganite from carbonates and chlorides:
${CLAUDE_SKILL_DIR}/../../venv/run cpu python ${CLAUDE_SKILL_DIR}/scripts/find_pathways.py \
--target YMnO3 \
--precursors YCl3 Mn2O3 Li2CO3 \
--byproducts LiCl CO2 \
--temperature 923 \
--k-paths 5Constraints
- Environments: The scripts require the
cpuenvironment wherereaction-networkandmp-apiare installed. Each execution MUST specify this environment. - Network Extent: Highly constrained chemical systems (e.g., >5 elements) without sensible stability filtering (
--stability-tol) can generate massive reaction networks taking >10 minutes and >16GB memory to solve. - Open Phases: Synthesis in air or controlled atmospheres must be modeled appropriately by declaring oxygen/nitrogen as open phases.
References
- McDermott, M. J., et al. "A graph-based approach to predicting solid-state synthesis pathways". Nature Communications (2021). DOI
Author: Bowen Deng Contact: GitHub @learningmatter-mit
© learningmatter-mit, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 11 other files (scripts) in skills/mat-reaction-network of learningmatter-mit/AtomisticSkills.
- SKILL.md
- examples/1_predict_liznpo4/README.md
- examples/1_predict_liznpo4/pair_a_output.json
- examples/1_predict_liznpo4/pair_b_output.json
- examples/1_predict_liznpo4/pair_c_output.json
- examples/1_predict_liznpo4/run.sh
- examples/2_predict_libabo3/README.md
- examples/2_predict_libabo3/predicted_output.json
- examples/2_predict_libabo3/run.sh
- examples/2_predict_libabo3/traditional_output.json
- scripts/enumerate_reactions.py
- scripts/find_pathways.py
Open the folder on GitHubat commit 7f2d86d
Compare with similar skills
Mat Reaction Network 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 |
|---|---|---|---|---|---|---|
| Mat Reaction Network this skilllearningmatter-mit/AtomisticSkills | 175 | — | ~833 | Automated safety check: Pass | MIT | |
| SQL Optimizationgithub/awesome-copilot | 40k | 2 repos | ~2.3k | Automated safety check: Pass | MIT | |
| Agent Performance Optimizerruvnet/ruflo | 74k | 2 repos | ~3.6k | Automated safety check: Pass | MIT | |
| Database Optimizerdavila7/claude-code-templates | 32k | 7 repos | ~2.5k | Automated safety check: Pass | MIT | |
| Prompt Optimizeraffaan-m/ECC | 274k | 2 repos | ~2.4k | Automated safety check: Pass | MIT | |
| Cost Optimizeruvnet/ruflo | 74k | — | ~997 | Automated safety check: Notes | MIT |
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Questions about Mat Reaction Network
What does Mat Reaction Network do?
Predict thermodynamically optimal solid-state inorganic synthesis pathways and tabulates basic reactions. Mat Reaction Network is an agent skill from learningmatter-mit/AtomisticSkills. Predict thermodynamically optimal solid-state inorganic synthesis pathways and tabulates basic reactions.
How do I install Mat Reaction Network in Claude Code?
Run `npx skills add learningmatter-mit/AtomisticSkills --skill mat-reaction-network -a claude-code`. Or copy the skill folder (skills/mat-reaction-network in learningmatter-mit/AtomisticSkills) into .claude/skills/mat-reaction-network in your project. Claude Code loads it when a task matches its description.
How do I install Mat Reaction Network in Codex?
Run `npx skills add learningmatter-mit/AtomisticSkills --skill mat-reaction-network -a codex`. Or copy the skill folder (skills/mat-reaction-network in learningmatter-mit/AtomisticSkills) into .agents/skills/mat-reaction-network in your project. Codex loads it when a task matches its description.
Can I use Mat Reaction Network 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 learningmatter-mit/AtomisticSkills --skill mat-reaction-network -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/mat-reaction-network, .gemini/skills/mat-reaction-network, .github/skills/mat-reaction-network and .opencode/skills/mat-reaction-network in your project.
What does Mat Reaction Network need to run?
Going by SKILL.md and its folder, Mat Reaction Network needs a shell and Python for the scripts in its folder. Our summary lists: Python 3; A Bash shell.
Does Mat Reaction Network access the network?
SKILL.md names 2 domains. As links in the text: doi.org and github.com. This is read from the text; nothing was executed.
Is Mat Reaction Network 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Mat Reaction Network use?
Mat Reaction Network 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 Mat Reaction Network use?
About 833 tokens (SKILL.md is roughly 3.3k 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 Mat Reaction Network?
Skills that share tags, products or a category with Mat Reaction Network: SQL Optimization (github/awesome-copilot, 40k stars), Agent Performance Optimizer (ruvnet/ruflo, 74k stars), Database Optimizer (davila7/claude-code-templates, 32k stars) and Prompt Optimizer (affaan-m/ECC, 274k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Mat Reaction Network?
learningmatter-mit (a GitHub organization) maintains it in learningmatter-mit/AtomisticSkills, which has 175 GitHub stars. The repository holds 129 skills in this directory. The repository was last updated on October 6, 2026.
Source: learningmatter-mit/AtomisticSkills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.