lingzhi227/agent-research-skills

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.

All-time #7970 Trending #9245 First seen Feb 20, 2026
8-week activity · all time api

Installation

$ npx skills add lingzhi227/agent-research-skills --skill atomic-decomposition

Similar popular skills

Related neighbors and high-traction skills in the same topics — useful to compare before installing.

Also in this package

Other skills from lingzhi227/agent-research-skills · top by installs.

npx skills add lingzhi227/agent-research-skills

Browse all from lingzhi227/agent-research-skills

More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 317
Default branch main
Open issues 3
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

Declared agents claude-code

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 2,851 B
  • docs SUMMARY.md 268 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 1,400 installs

SKILL.md

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/)