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/ar:ar-status — Experiment Dashboard

Show experiment dashboard with results, active loops, and progress.

How to use it

Claude Code
  1. Run the line below. It pulls the whole folder into ~/.claude/skills/ar-status, including the files SKILL.md points to.
  2. Describe your job in plain words. Claude Code follows the skill from there.
Claude Code — installs the whole folder, not just SKILL.md
npx degit alirezarezvani/claude-skills/engineering/autoresearch-agent/skills/ar-status#main ~/.claude/skills/ar-status

For one project only, change the path to .claude/skills/ar-status. This skill also uses loop.json — copying SKILL.md alone won't be enough. See the folder on GitHub.

Claude (web or desktop app)
  1. On this page open ⋯ → Download .md.
  2. Save it as SKILL.md in a folder, zip the folder, then Customize → Skills → + → Create skill → Upload a skill.
  3. Pick the file and Save. Claude shows the name and description and runs a security scan.
  4. Check the skill is switched on.
  5. Start a new chat and describe your job in plain words. The AI follows the skill from there.
ChatGPT or another app
  1. ChatGPT: make a Project and paste it into Instructions.
  2. Neither? Paste it at the top of a new chat — it works for that chat.
Not working?
  • Check which app you pasted it into — the steps above name the right one.
  • Some skills need the paid tier of Claude or ChatGPT.
Step-by-step guide with screenshots · Ask in the forum

Paste into Claude, ChatGPT or Cursor.

Source of /ar:ar-status — Experiment Dashboard

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namedescriptioncommand
ar-statusShow experiment dashboard with results, active loops, and progress. Use when the user runs /ar:ar-status or asks how an autoresearch experiment is going./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
python {skill_path}/scripts/log_results.py --experiment {domain}/{name}

Also check for active loop:

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
python {skill_path}/scripts/log_results.py --domain {domain}
Full dashboard
python {skill_path}/scripts/log_results.py --dashboard

For each experiment, also check for loop.json and show loop status.

Export
# 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     —
1---
2name: "ar-status"
3description: "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."
4command: /ar:ar-status
5---
6 
7# /ar:ar-status — Experiment Dashboard
8 
9Show experiment results, active loops, and progress across all experiments.
10 
11## Usage
12 
13```
14/ar:ar-status # Full dashboard
15/ar:ar-status engineering/api-speed # Single experiment detail
16/ar:ar-status --domain engineering # All experiments in a domain
17/ar:ar-status --format markdown # Export as markdown
18/ar:ar-status --format csv --output results.csv # Export as CSV
19```
20 
21## What It Does
22 
23### Single experiment
24 
25```bash
26python {skill_path}/scripts/log_results.py --experiment {domain}/{name}
27```
28 
29Also check for active loop:
30```bash
31cat .autoresearch/{domain}/{name}/loop.json 2>/dev/null
32```
33 
34If loop.json exists, show:
35```
36Active loop: every {interval} (cron ID: {id}, started: {date})
37```
38 
39### Domain view
40 
41```bash
42python {skill_path}/scripts/log_results.py --domain {domain}
43```
44 
45### Full dashboard
46 
47```bash
48python {skill_path}/scripts/log_results.py --dashboard
49```
50 
51For each experiment, also check for loop.json and show loop status.
52 
53### Export
54 
55```bash
56# CSV
57python {skill_path}/scripts/log_results.py --dashboard --format csv --output {file}
58 
59# Markdown
60python {skill_path}/scripts/log_results.py --dashboard --format markdown --output {file}
61```
62 
63## Output Example
64 
65```
66DOMAIN EXPERIMENT RUNS KEPT BEST CHANGE STATUS LOOP
67engineering api-speed 47 14 185ms -76.9% active every 1h
68engineering bundle-size 23 8 412KB -58.3% paused —
69marketing medium-ctr 31 11 8.4/10 +68.0% active daily
70prompts support-tone 15 6 82/100 +46.4% done —
71```
72 

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