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skill

ar-status — Claude Code skill: autoresearch experiment dashboard

Shows results, active loops and progress across autoresearch experiments. Useful once you have enough runs that keeping track in your head stops working.

Install into Claude Code · Plugin marketplace All methods and platforms ↓
/plugin marketplace add alirezarezvani/claude-skills
/plugin install autoresearch-agent@claude-code-skills
Open on GitHub

What ar-status does

The skill prints a summary per experiment: run count, how many results were kept, best value, change and status. It calls log_results.py with --dashboard to build that table. Next to each experiment it reads .autoresearch/{domain}/{name}/loop.json and, when the file is there, adds a line about the active loop with interval, cron ID and start date.

You can narrow the view. --domain engineering lists experiments from one area, while a name like engineering/api-speed gives the detail for a single run. Exports go through --format markdown or --format csv plus --output {file}.

Everything runs on Python, since the logic lives in scripts/log_results.py. No interpreter, no output. Data comes from the .autoresearch directory, so in a project with no experiments the dashboard stays empty.

What it helps with

  • see which experiments are still running and which are done
  • compare the best result against the starting point
  • check whether a loop is scheduled and how often it fires
  • export the summary to CSV for a spreadsheet
  • review every experiment in one domain at once

Example prompts for the agent

  • /ar:ar-status
  • /ar:ar-status engineering/api-speed
  • /ar:ar-status --domain engineering --format markdown

How to install ar-status

1Plugin marketplace

/plugin marketplace add alirezarezvani/claude-skills
/plugin install autoresearch-agent@claude-code-skills

This installs the whole autoresearch-agent plugin with all its skills

2Skills CLI (Vercel)

npx skills add alirezarezvani/claude-skills --skill ar-status -a claude-code

3Manually: put the files in place

~/.claude/skills/ar-status/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/ar-status/

Step by step, with commands for each platform: How to install skills in Claude Code: five ways

Questions about ar-status

How do I install ar-status in Claude?

From the marketplace: run /plugin marketplace add alirezarezvani/claude-skills first, then /plugin install autoresearch-agent@claude-code-skills.

What does ar-status do?

It renders an autoresearch dashboard: runs, kept results, best value and status for each experiment, plus the state of any active loop.

What does ar-status need to work?

Python to run scripts/log_results.py, and an .autoresearch directory holding the experiment data. Without them the dashboard comes back empty.

Source text

SKILL.md · MIT
---
name: "ar-status"
description: "Show experiment dashboard with results, active loops, and progress. Use when the user runs /ar:ar-status or asks how an autoresearch experiment is going."
metadata:
  command: /ar:ar-status
---

# /ar:ar-status — Experiment Dashboard

Show experiment results, active loops, and progress across all experiments.

## Usage

```
/ar:ar-status                                  # Full dashboard
/ar:ar-status engineering/api-speed            # Single experiment detail
/ar:ar-status --domain engineering             # All experiments in a domain
/ar:ar-status --format markdown                # Export as markdown
/ar: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     —
```

© Alireza Rezvani · MIT · alirezarezvani/claude-skills

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