backward-traceability

Q: How do I install backward-traceability?

Run npx skills add https://github.com/lingzhi227/agent-research-skills --skill backward-traceability in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/backward-traceability/ (personal) or .claude/skills/backward-traceability/ (project).

by lingzhi227Docs & Writing

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.

Installs: 2.1K
Last 24h: +9
Trending rank: #9055
Security: Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/lingzhi227/agent-research-skills --skill backward-traceability

01
Install
Run the command in your project. The CLI asks which agents to install for.
02
Describe the task
Ask your agent for something this skill covers. It loads backward-traceability automatically when relevant.
03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

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 \hypertarget in 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

FAQ

What does the backward-traceability skill do?

How do I install backward-traceability?

Run npx skills add https://github.com/lingzhi227/agent-research-skills --skill backward-traceability in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/backward-traceability/ (personal) or .claude/skills/backward-traceability/ (project).

Which AI agents can use backward-traceability?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is backward-traceability safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains backward-traceability?

It is published by lingzhi227 in lingzhi227/agent-research-skills. It has 2,147 recorded installs.