Skill-Details
status
Narrow experiment-loop component.
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SKILL.md
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---
name: "status"
description: "Show experiment dashboard with results, active loops, and progress. Use when the user runs /ar:status or asks how an autoresearch experiment is going."
command: /ar:status
---
# /ar:status — Experiment Dashboard
Show experiment results, active loops, and progress across all experiments.
## Usage
```
/ar:status # Full dashboard
/ar:status engineering/api-speed # Single experiment detail
/ar:status --domain engineering # All experiments in a domain
/ar:status --format markdown # Export as markdown
/ar:status --format csv --output results.csv # Export as CSV
```
## What It Does
### Single experiment
```bash
python {skill_path}/scripts/log_results.py --experiment {domain}/{name}
```
Also check for active loop:
```bash
cat .autoresearch/{domain}/{name}/loop.json 2>/dev/null
```
If loop.json exists, show:
```
Active loop: every {interval} (cron ID: {id}, started: {date})
```
### Domain view
```bash
python {skill_path}/scripts/log_results.py --domain {domain}
```
### Full dashboard
```bash
python {skill_path}/scripts/log_results.py --dashboard
```
For each experiment, also check for loop.json and show loop status.
### Export
```bash
# CSV
python {skill_path}/scripts/log_results.py --dashboard --format csv --output {file}
# Markdown
python {skill_path}/scripts/log_results.py --dashboard --format markdown --output {file}
```
## Output Example
```
DOMAIN EXPERIMENT RUNS KEPT BEST CHANGE STATUS LOOP
engineering api-speed 47 14 185ms -76.9% active every 1h
engineering bundle-size 23 8 412KB -58.3% paused —
marketing medium-ctr 31 11 8.4/10 +68.0% active daily
prompts support-tone 15 6 82/100 +46.4% done —
```
Vollständige Quelle auf GitHub lesen (öffnet externe Seite)