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Research
Skill

/atomic-decomposition

Decompose research ideas into atomic, self-contained concepts with bidirectional math-code mapping. For each concept, extract the math formula from papers and find code implementations. Use for complex system papers requiring formal grounding.

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agent-research-skills
26531 skills1 command
Install
$ npx -y skills add lingzhi227/agent-research-skills --skill atomic-decomposition --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/atomic-decomposition

Context preview

The summary Claude sees to decide when to auto-load this skill.

Decompose research ideas into atomic, self-contained concepts with bidirectional math-code mapping. For each concept, extract the math formula from papers and find code implementations. Use for complex system papers requiring formal grounding.

SKILL.md

atomic-decomposition.SKILL.md
name: atomic-decomposition
description: Decompose research ideas into atomic, self-contained concepts with bidirectional math-code mapping. For each concept, extract the math formula from papers and find code implementations. Use for complex system papers requiring formal grounding.
argument-hint: [idea-or-paper]

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 code
  • Must be traceable to specific papers

Step 2: For Each Atomic Definition

A. Paper Survey (Math Formula)

  • Search papers for the mathematical formulation
  • Extract the exact LaTeX formula
  • Note assumptions and constraints
  • Record reference papers

B. Code Survey (Implementation)

  • Search codebases for implementations
  • Extract the corresponding code
  • Note implementation details and variations
  • Record reference repositories

C. Create Knowledge Entry

{
  "definition": "Kernelized Gumbel-Softmax Operator",
  "math_formula": "Z = \\text{softmax}((\\log \\pi + g) / \\tau), g \\sim \\text{Gumbel}(0,1)",
  "code_implementation": "def gumbel_softmax(logits, tau=1.0): ...",
  "reference_papers": ["Paper Title 1"],
  "reference_codebases": ["github_user/repo_name"],
  "assumptions": ["Differentiable relaxation of discrete sampling"],
  "connections": ["Used in Component X of the proposed method"]
}

Step 3: Compile Knowledge Base

  • Merge all atomic definitions into a structured knowledge base
  • Verify consistency: every math formula has a code implementation
  • Verify completeness: every code module traces to a formal definition
  • Identify any gaps (formulas without code, or code without theory)

Rules

  • Each atomic definition must be specific enough to trace to concrete formulas and code
  • Do not skip or combine definitions — analyze each separately
  • If unsure about atomicity, err on the side of breaking down further
  • Document breakdown reasoning before analysis
  • Every mathematical concept in the paper must have verified code
  • Every code module must trace back to a formal mathematical definition

Related Skills

  • Upstream: [research-planning](../research-planning/), [idea-generation](../idea-generation/)
  • Downstream: [experiment-code](../experiment-code/), [algorithm-design](../algorithm-design/)
  • See also: [math-reasoning](../math-reasoning/)
Read more
Ships withagent-research-skills

31 skills for Claude Code covering the full academic research paper lifecycle — from literature search to slide generation — plus GitHub repository analysis for research topics. Extracted from 17 GitHub repos studying LLM-agent-driven research automation.

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