project-sync

Sync experiment results from the code repo into the paper's daily experiments log (daily_experiments.tex). Use when you have new experiment results to record, want to update the paper with latest numbers, or log experimental findings from an ML research project.

Safety Notice

This listing is imported from skills.sh public index metadata. Review upstream SKILL.md and repository scripts before running.

Copy this and send it to your AI assistant to learn

Install skill "project-sync" with this command: npx skills add a-green-hand-jack/ml-research-skills/a-green-hand-jack-ml-research-skills-project-sync

Project Sync Workflow

Use this workflow when you have new experiment results in the code repo and want to record them in the paper's daily_experiments.tex.

This is a manual, human-triggered workflow — run it whenever you want to checkpoint results into the paper.


Step 1 — Locate the Project

// turbo Auto-detect the project structure. Run:

# Find the git root of the current repo
git rev-parse --show-toplevel 2>/dev/null

# Check if we're in code/ or paper/ and find sibling
ls "$(git rev-parse --show-toplevel)/../"

Determine:

  • $CODE_ROOT — the code repo root
  • $PAPER_ROOT — the paper repo root (sibling directory)

If both paper/ and code/ are not siblings under a common parent, ask the user:

"Where is the paper repo? Please provide its path."


Step 2 — Gather New Results

Ask the user in a single message:

  1. Date: What date are these experiments? (default: today's date, YYYY-MM-DD)
  2. Short title: A brief label for this experiment batch (e.g. "Baseline on CIFAR-10", "Ablation: remove attention layer")
  3. Setup: What method variant / config / dataset was used?
  4. Results: What are the key numbers? (paste metrics, accuracy, loss, etc.)
  5. Observation: What do the results mean? What worked, what didn't?
  6. Next: What follow-up experiment is planned?

Optionally, also check if there are existing result files to pull from:

# Recent files in experiments/ or outputs/
ls -lt "$CODE_ROOT/experiments/" 2>/dev/null | head -10
ls -lt "$CODE_ROOT/outputs/logs/" 2>/dev/null | head -10

If relevant log files exist, read them and pre-fill the answers for the user to confirm.


Step 3 — Preview the Entry

Compose and display the LaTeX entry for the user to review:

\subsection*{<DATE> — <SHORT TITLE>}
\textbf{Setup:} <setup>\\
\textbf{Result:} <results>\\
\textbf{Observation:} <observation>\\
\textbf{Next:} <next>

Ask: "Does this look correct? Should I add it to the paper?"

Wait for confirmation.


Step 4 — Insert into daily_experiments.tex

// turbo Read the current contents of $PAPER_ROOT/sections/daily_experiments.tex.

Insert the new entry at the top (below the comment header), so the log is in reverse chronological order (newest first).

After inserting, show the user the updated top of the file to confirm it looks right.


Step 5 — Commit to Paper Repo (optional)

Ask: "要把这条实验记录提交到 paper repo 的 Git 吗?(Y/n)"

If yes:

git -C "$PAPER_ROOT" add sections/daily_experiments.tex
git -C "$PAPER_ROOT" commit -m "exp: add <DATE> — <SHORT TITLE>"

If no, inform the user the file is saved and can be committed later.


Step 6 — Confirm

Report:

Experiment logged:
  Date:   <DATE>
  Title:  <SHORT TITLE>
  File:   <PAPER_ROOT>/sections/daily_experiments.tex

To view all logged experiments:
  cat <PAPER_ROOT>/sections/daily_experiments.tex

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

Related Skills

Related by shared tags or category signals.

Coding

init-python-project

No summary provided by upstream source.

Repository SourceNeeds Review
Research

add-git-tag

No summary provided by upstream source.

Repository SourceNeeds Review
Research

update-docs

No summary provided by upstream source.

Repository SourceNeeds Review
Research

project-init

No summary provided by upstream source.

Repository SourceNeeds Review