modelscope.cn

extract-algorithm

Parse and document algorithm pseudocode from research papers. Use when preparing for implementation.

Installation

$ npx skills add https://modelscope.cn

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 modelscope.cn · top by installs.

npx skills add https://modelscope.cn

Browse all from modelscope.cn

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

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 1,717 B

History

  1. First recorded snapshot · 0 installs

SKILL.md

Extract Algorithm

Identify, document, and translate algorithms from research papers into structured pseudocode for implementation planning.

When to Use

  • Converting paper algorithms to code
  • Understanding computational complexity
  • Planning implementation steps
  • Documenting algorithm variations

Quick Reference

# Extract text from PDF focusing on algorithms
pdftotext paper.pdf - | grep -A 20 -i "algorithm\|pseudocode" | head -50

# Convert pseudo-code to structured documentation
# Use cleaner formatting with numbered steps

Workflow

  1. Locate algorithm: Find algorithm description, pseudocode, or flowchart in paper
  2. Document steps: Extract numbered steps or pseudocode from paper
  3. Identify inputs/outputs: List parameters, preconditions, postconditions
  4. Note special cases: Document edge cases and conditional logic
  5. Translate to implementation plan: Convert to implementation checklist

Output Format

Algorithm documentation:

  • Algorithm name and source reference
  • Inputs (parameters, data types, constraints)
  • Outputs (return values, side effects)
  • Pseudocode or step-by-step description
  • Complexity analysis (time and space)
  • Special cases and error handling
  • Implementation notes and tips

References

  • See analyze-equations skill for mathematical formula extraction
  • See identify-architecture skill for understanding algorithm structure
  • See CLAUDE.md > Key Development Principles for implementation guidance