Hierarchically decompose high-level scientific workflows (from literature or user-proposed) into executable sequences of existing SKILLs and MCP tools for the research plan.
Install the "general-workflow-planner" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/general-workflow-planner into .claude/skills/general-workflow-planner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "general-workflow-planner", 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.
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 learningmatter-mit/AtomisticSkills --skill general-workflow-planner -a codex
Project install goes to .agents/skills/; add -g for ~/.codex/skills/.
Install the "general-workflow-planner" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/general-workflow-planner into .agents/skills/general-workflow-planner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "general-workflow-planner", 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 learningmatter-mit/AtomisticSkills --skill general-workflow-planner -a cursor
Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.
Install the "general-workflow-planner" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/general-workflow-planner into .cursor/skills/general-workflow-planner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "general-workflow-planner", 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.
--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 learningmatter-mit/AtomisticSkills --skill general-workflow-planner -a gemini-cli
Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.
Install the "general-workflow-planner" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/general-workflow-planner into .gemini/skills/general-workflow-planner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "general-workflow-planner", 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.
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 learningmatter-mit/AtomisticSkills --skill general-workflow-planner -a github-copilot
Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.
Install the "general-workflow-planner" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/general-workflow-planner into .github/skills/general-workflow-planner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "general-workflow-planner", 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 learningmatter-mit/AtomisticSkills --skill general-workflow-planner -a opencode
OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
Install the "general-workflow-planner" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/general-workflow-planner into .opencode/skills/general-workflow-planner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "general-workflow-planner", 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
general-workflow-planner
GitHub stars
175
Token cost
~936 tokens
SKILL.md length
421 words
Files
2
Skills in repo
129
Repo updated
First seen
Licence
MIT
At a glance
Hierarchically decompose high-level scientific workflows (from literature or user-proposed) into executable sequences of existing SKILLs and MCP tools for the research plan.
Works in 5 steps: Objective Parsing → Skill Registry Mapping → Dependency Construction → …
Tasks that involve MCP servers
SKILL.md covers Goal, Prerequisites, Instructions and Examples, plus 2 more sections
Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
General Workflow Planner is an agent skill from learningmatter-mit/AtomisticSkills. Hierarchically decompose high-level scientific workflows (from literature or user-proposed) into executable sequences of existing SKILLs and MCP tools for the research plan.
Its SKILL.md is about 940 tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files (for example `examples/sse-discovery/README.md`).
It sits in Agent Workflows, covering MCP servers. It works with Model Context Protocol. The repository describes itself as: Integrating AtomisticSkills into Agentic IDEs (Cursor, Claude Code, Codex, Google Antigravity, Hermes Agent, etc). The licence is MIT.
When your agent uses it
Tasks that involve MCP servers
Example prompts
“/general-workflow-planner”
Requirements
Python 3
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
1Objective Parsing
2Skill Registry Mapping
3Dependency Construction
4Feasibility Analysis
5Detailed Action Plan Generation
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
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
Links to these hosts (documentation or services it may open):
github.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
General Workflow Planner loads about 936 tokens when it runs. Until then it costs about 50 tokens; SKILL.md has 421 words of instructions outside code blocks.
Always· name and description, kept in context so the agent knows when to use it
~50
When it runs· the whole SKILL.md, loaded when a task matches
~936
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.
Download SKILL.mdSave it as .claude/skills/general-workflow-planner/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
general-workflow-planner
description
Hierarchically decompose high-level scientific workflows (from literature or user-proposed) into executable sequences of existing SKILLs and MCP tools for the research plan.
metadata.category
general
metadata.venv
mlip
General Workflow Planner
<!-- mcp-tools-note -->
[!NOTE]
Steps written server.tool are MCP tool calls: mace.run_md is the run_md
tool of the mace server (mcp__mace__run_md, or
mcp__plugin_atomistic-skills_mace__run_md when installed as a plugin).
Without a connected server, run the same tools from the shell. Tools named in
one command share a process, so a model loaded by load_model stays loaded:
To decompose high-level scientific workflows (either sourced from literature or proposed directly by the user) into a concrete, executable sequence. This skill parses the objective and outputs a chronological "Detailed Action Plan" that feeds directly into the research_plan.md artifact, in accordance with .agents/rules/research-standards.md. Do not overcomplicate the output; it should be a straightforward list of steps.
Prerequisites
A high-level scientific workflow proposed by the user or derived from literature review.
Access to the skills/ registry and available MCP tools.
Instructions
Objective Parsing
Analyze the high-level workflow to determine the key scientific steps (e.g., Structure Generation $\rightarrow$ Relaxation $\rightarrow$ Stability $\rightarrow$ Dynamics).
Skill Registry Mapping
Scan the repository's capabilities. Map each conceptual step to existing project tools by searching the skills/ directory and available MCP tools (e.g., mace.run_md, matgl.relax_structure).
Dependency Construction
Map the dependencies between the identified SKILLs and MCP tools:
Identify data dependencies: The output of Step A must act as the input for Step B (e.g., the mat-db-mp skill outputs a .cif, which serves as the input for the mace.relax_structure MCP tool).
Identify parallelization opportunities if applicable.
Feasibility Analysis
Verify that there is a continuous line of data flowing from the initial state to the target objective using only existing tools.
If missing steps exist, flag them explicitly so the user knows where custom scripting or new skills are required.
Detailed Action Plan Generation
Output a concrete, chronological list of steps required to execute the workflow. List the proposed hyperparameters for each SKILL and MCP tool (e.g., temperature, steps, supercell_min_length). This list is directly inserted into the Detailed Action Plan section of research_plan.md.
Show full SKILL.md (77 more words)Show less
Examples
For an example of decomposing a high-level goal into a Detailed Action Plan using existing skills and MCP tools, see the Solid-State Electrolyte Discovery example.
Constraints
Skill Hallucination: NEVER invent or hallucinate skill names. Every step must map to a verifiable directory inside skills/ or a documented MCP tool.
Simplicity: Do not overcomplicate the output. Produce a linear or simple branching Action Plan suited for research_plan.md.
General Workflow Planner 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.
General Workflow Planner compared with similar skills
Skill
Stars
Used in
Tokens
Auto-check
Licence
Repo updated
General Workflow Planner this skilllearningmatter-mit/AtomisticSkills
Walks through building MCP servers in Python or TypeScript that expose tools, resources and prompts to Claude, with templates, registration and testing.
Explains how to bundle Model Context Protocol servers in a Claude Code plugin, covering config files, stdio, SSE, HTTP and WebSocket server types, and authentication.
Explains how to configure the Crush coding agent with crushrc or crush.json, covering providers, models, LSPs, MCP servers, hooks, permissions and config precedence.
Routes large command, file, API and browser output through context-mode tools so only the needed result enters the agent's context, instead of dumping it via Bash.
Define a docking search box (center coordinates + box dimensions in Angstroms) from a co-crystal ligand, binding-site residues, or a saved JSON specification.
Hierarchically decompose high-level scientific workflows (from literature or user-proposed) into executable sequences of existing SKILLs and MCP tools for the research plan. General Workflow Planner is an agent skill from learningmatter-mit/AtomisticSkills. Hierarchically decompose high-level scientific workflows (from literature or user-proposed) into executable sequences of existing SKILLs and MCP tools for the research plan.
When should I use General Workflow Planner?
General Workflow Planner fits situations like: tasks that involve MCP servers.
How do I install General Workflow Planner in Claude Code?
Run `npx skills add learningmatter-mit/AtomisticSkills --skill general-workflow-planner -a claude-code`. Or copy the skill folder (skills/general-workflow-planner in learningmatter-mit/AtomisticSkills) into .claude/skills/general-workflow-planner in your project. Claude Code loads it when a task matches its description.
How do I install General Workflow Planner in Codex?
Run `npx skills add learningmatter-mit/AtomisticSkills --skill general-workflow-planner -a codex`. Or copy the skill folder (skills/general-workflow-planner in learningmatter-mit/AtomisticSkills) into .agents/skills/general-workflow-planner in your project. Codex loads it when a task matches its description.
Can I use General Workflow Planner 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 general-workflow-planner -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/general-workflow-planner, .gemini/skills/general-workflow-planner, .github/skills/general-workflow-planner and .opencode/skills/general-workflow-planner in your project.
What does General Workflow Planner need to run?
SKILL.md names no scripts, command-line tools or credentials: General Workflow Planner is instructions for the agent only. Our summary lists: Python 3.
Does General Workflow Planner access the network?
SKILL.md names 1 domain. As links in the text: github.com. This is read from the text; nothing was executed.
Is General Workflow Planner 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 General Workflow Planner use?
General Workflow Planner 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 General Workflow Planner use?
About 936 tokens (SKILL.md is roughly 3.7k 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 General Workflow Planner?
Skills that share tags, products or a category with General Workflow Planner: MCP Server Builder (anthropics/skills, 180k stars), MCP Server Builder (shareAI-lab/learn-claude-code, 78k stars), MCP Integration for Plugins (anthropics/claude-plugins-official, 37k stars) and Fastmcp Client CLI (PrefectHQ/fastmcp, 28k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains General Workflow Planner?
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.
