backward-traceability
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.
How do I install this agent skill?
npx skills add https://github.com/lingzhi227/agent-research-skills --skill backward-traceabilityIs this agent skill safe to install?
- Gen Agent Trust Hubwarn
The skill facilitates data traceability in LaTeX documents using a Python script for verification. However, the documentation provides code patterns that use the eval() function for dynamic formula evaluation, which introduces a potential dynamic execution risk. Additionally, the skill's ingestion of external LaTeX files presents a minor indirect prompt injection surface.
- Socketpass
No alerts
- Snykpass
Risk: LOW · No issues
- Runlayerpass
2/3 files flagged
What does this agent skill do?
Backward Traceability
Make every number in the final PDF hyperlink back to the exact code line that produced it.
Input
$0— Paper project directory containing code and LaTeX files
References
- Traceability patterns and LaTeX commands:
~/.claude/skills/backward-traceability/references/traceability-patterns.md
Scripts
Scan hypertarget/hyperlink references
python ~/.claude/skills/backward-traceability/scripts/ref_numeric_values.py \
--scan paper/main.tex --output report.json
Reports: all hypertargets, hyperlinks, orphan references, unreferenced numeric values.
Verify cross-reference integrity
python ~/.claude/skills/backward-traceability/scripts/ref_numeric_values.py \
--verify paper/main.tex --code-output results.txt
Cross-checks values between paper text and code output. Reports mismatches.
Workflow
Step 1: Tag Code Outputs
For every numeric value produced by experiment code, add hypertarget tags:
# In experiment code output:
print(f"\\hypertarget{{R1a}}{{45.3}}") # Mean accuracy
print(f"\\hypertarget{{R1b}}{{2.1}}") # Std deviation
Label format: {prefix}{line_number}{letter} where letter = a, b, c... for multiple values on same line.
Step 2: Reference in Paper Text
Use \hyperlink to create clickable references in the paper:
Our method achieves \hyperlink{R1a}{45.3}\% accuracy
($\pm$\hyperlink{R1b}{2.1}).
Step 3: Use \num for Computed Values
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"}\%.
Step 4: Generate Appendix Code Listing
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}
Step 5: Verify Traceability
- Every number in the paper text must have a corresponding
\hypertargetin the code - Every
\num{}formula must evaluate correctly - Click-test: every hyperlink in the PDF must jump to the correct code line
LaTeX Setup
Required packages:
\usepackage{hyperref}
\usepackage{listings}
Rules
- Every numeric result in the paper MUST trace to code output
- Never manually type numbers — always reference tagged outputs
- Use
\num{}for any derived/computed values - Code listing in appendix must match actual executed code
- Verify all hyperlinks resolve correctly after compilation
Related Skills
- Upstream: experiment-code, data-analysis
- Downstream: paper-compilation
- See also: paper-assembly
How can the creator link this skill?
Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.
<a href="https://skillzs.dev/skills/lingzhi227/agent-research-skills/backward-traceability">View backward-traceability on skillZs</a>