Learn-skills.dev 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.
git clone https://github.com/NeverSight/learn-skills.dev
T=$(mktemp -d) && git clone --depth=1 https://github.com/NeverSight/learn-skills.dev "$T" && mkdir -p ~/.claude/skills && cp -r "$T/data/skills-md/a-green-hand-jack/ml-research-skills/project-sync" ~/.claude/skills/neversight-learn-skills-dev-project-sync && rm -rf "$T"
data/skills-md/a-green-hand-jack/ml-research-skills/project-sync/SKILL.mdProject 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 "$(git rev-parse --show-toplevel)/../"
Determine:
— the code repo root$CODE_ROOT
— the paper repo root (sibling directory)$PAPER_ROOT
If both
paper/ and code/ are not siblings under a common parent, ask the user:
"Where is the paper repo? Please provide its path."
Step 2 — Gather New Results
Ask the user in a single message:
- Date: What date are these experiments? (default: today's date, YYYY-MM-DD)
- Short title: A brief label for this experiment batch (e.g. "Baseline on CIFAR-10", "Ablation: remove attention layer")
- Setup: What method variant / config / dataset was used?
- Results: What are the key numbers? (paste metrics, accuracy, loss, etc.)
- Observation: What do the results mean? What worked, what didn't?
- Next: What follow-up experiment is planned?
Optionally, also check if there are existing result files to pull from:
# Recent files in experiments/ or outputs/ ls -lt "$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