atomic-decomposition
The atomic-decomposition skill breaks research ideas into atomic concepts by mapping mathematical formulas to code implementations. It requires users to provide a research idea or paper description as input.
Is atomic-decomposition safe to install?
Safe to install: our audit of atomic-decomposition's source files found 0 shell commands, 0 external URLs, file reads and writes (low risk). Every command and URL listed appears verbatim in the skill's source. The skill reads local files at ~/.claude/skills/atomic-decomposition/references/decomposition-prompts.md to execute its workflow.
How we audit skills: our security review methodology.
Who is this skill for?
Researchers and developers working on complex systems who need to ground theoretical concepts in verifiable code.
What can you do with it?
- Decomposing research papers into self-contained mathematical and code-based definitions.
- Verifying the consistency between mathematical formulas and their corresponding code implementations.
- Identifying gaps between theoretical research and practical code modules.
How good is this skill?
Quality score: 4/10. The skill provides a clear, structured workflow for research decomposition. It lacks external network dependencies, making it safe for local execution.
What does the skill file contain?
# Atomic Decomposition Decompose research ideas into atomic concepts with math formula <-> code implementation mapping. ## Input - `$0` — Research idea, paper, or method description ## References - Decomposition prompts and workflow: `~/.claude/skills/atomic-decomposition/references/decomposition-prompts.md` ## Workflow (from AI-Researcher Survey Agent) ### Step 1: Break Down into Atomic Definitions Analyze the research idea and decompose into atomic, self-contained concepts: - Each atom should be a single concept - Must have clear mathematical foundations - Must be implementable in cod...
Frequently asked questions
What input does the skill require?
The skill requires a research idea, paper, or method description as an argument.
How does the skill verify research concepts?
It mandates that every mathematical concept must have a verified code implementation and every code module must trace back to a formal mathematical definition.
What is the output format for a knowledge entry?
The skill produces a JSON object containing the definition, LaTeX math formula, code implementation, reference papers, reference codebases, assumptions, and connections.
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