Monitor running experiments, check progress, collect results. Use when user says \"check results\", \"is it done\", \"monitor\", or wants experiment output.
Scanned 9/3/2026
Install to Claude Code
npx -y skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill monitor-experiment --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Monitor Experiment?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/brycewang-stanford-monitor-experiment-auto-empirical-research-skills)More formats (shields.io, HTML) on the badges page.
---
name: "monitor-experiment"
description: "Monitor running experiments, check progress, collect results. Use when user says \"check results\", \"is it done\", \"monitor\", or wants experiment output."
---
# Monitor Experiment Results
Monitor: $ARGUMENTS
## Workflow
### Step 1: Check What's Running
```bash
ssh <server> "screen -ls"
```
### Step 2: Collect Output from Each Screen
For each screen session, capture the last N lines:
```bash
ssh <server> "screen -S <name> -X hardcopy /tmp/screen_<name>.txt && tail -50 /tmp/screen_<name>.txt"
```
If hardcopy fails, check for log files or tee output.
### Step 3: Check for JSON Result Files
```bash
ssh <server> "ls -lt <results_dir>/*.json 2>/dev/null | head -20"
```
If JSON results exist, fetch and parse them:
```bash
ssh <server> "cat <results_dir>/<latest>.json"
```
### Step 4: Summarize Results
Present results in a comparison table:
```
| Experiment | Metric | Delta vs Baseline | Status |
|-----------|--------|-------------------|--------|
| Baseline | X.XX | — | done |
| Method A | X.XX | +Y.Y | done |
```
### Step 5: Interpret
- Compare against known baselines
- Flag unexpected results (negative delta, NaN, divergence)
- Suggest next steps based on findings
### Step 6: Feishu Notification (if configured)
After results are collected, check `~/.codex/feishu.json`:
- Send `experiment_done` notification: results summary table, delta vs baseline
- If config absent or mode `"off"`: skip entirely (no-op)
## Key Rules
- Always show raw numbers before interpretation
- Compare against the correct baseline (same config)
- Note if experiments are still running (check progress bars, iteration counts)
- If results look wrong, check training logs for errors before concluding
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!