algorithm-design
Design algorithms with LaTeX pseudocode and UML diagrams. Generate algorithmic environments,…
Make every number in the final PDF traceable to the exact code line that produced it. Uses \hypertarget/\hyperlink LaTeX commands and \num{formula} evaluated at compile time. Use for reproducibility and data integrity verification.
$ npx -y skills add lingzhi227/agent-research-skills --skill backward-traceability --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/backward-traceabilityContext preview
The summary Claude sees to decide when to auto-load this skill.
Make every number in the final PDF traceable to the exact code line that produced it. Uses \hypertarget/\hyperlink LaTeX commands and \num{formula} evaluated at compile time. Use for reproducibility and data integrity verification.
name: backward-traceability
description: Make every number in the final PDF traceable to the exact code line that produced it. Uses \hypertarget/\hyperlink LaTeX commands and \num{formula} evaluated at compile time. Use for reproducibility and data integrity verification.
argument-hint: [paper-directory]Make every number in the final PDF hyperlink back to the exact code line that produced it.
python ~/.claude/skills/backward-traceability/scripts/ref_numeric_values.py \ --scan paper/main.tex --output report.json
Reports: all hypertargets, hyperlinks, orphan references, unreferenced numeric values.
python ~/.claude/skills/backward-traceability/scripts/ref_numeric_values.py \ --verify paper/main.tex --code-output results.txt
Cross-checks values between paper text and code output. Reports mismatches.
For every numeric value produced by experiment code, add hypertarget tags:
# In experiment code output:
print(f"\\hypertarget{{R1a}}{{45.3}}") # Mean accuracy
print(f"\\hypertarget{{R1b}}{{2.1}}") # Std deviationLabel format: `{prefix}{line_number}{letter}` where letter = a, b, c... for multiple values on same line.
Use `\hyperlink` to create clickable references in the paper:
Our method achieves \hyperlink{R1a}{45.3}\% accuracy
($\pm$\hyperlink{R1b}{2.1}).For values derived from other values, use `\num{}` for compile-time evaluation:
% \num{formula, "explanation"} → evaluated at compile time
The improvement is \num{45.3 - 38.7, "accuracy gain"}\%.Create an appendix with the full code listing, with `\hypertarget` anchors at relevant lines:
\section*{Appendix: Code Listing}
\begin{lstlisting}[escapechar=@]
@\hypertarget{code1}{}@result = model.evaluate(test_data)
@\hypertarget{code2}{}@accuracy = result['accuracy']
\end{lstlisting}Required packages:
\usepackage{hyperref}
\usepackage{listings}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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