engineering/autoresearch-agent/skills/status/SKILL.md
Show experiment dashboard with results, active loops, and progress. Use when the user runs /ar:status or asks how an autoresearch experiment is going.
npx skillsauth add alirezarezvani/claude-skills statusInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Show experiment results, active loops, and progress across all experiments.
/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
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})
python {skill_path}/scripts/log_results.py --domain {domain}
python {skill_path}/scripts/log_results.py --dashboard
For each experiment, also check for loop.json and show loop status.
# 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}
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 —
data-ai
Use when you want to understand what Claude contributed vs what you drove in a session. Triggers on: /collab-proof, session retrospective, ai contribution analysis, collaboration evidence, what did claude do.
data-ai
Personal coach that teaches users to become Claude power users. Use this skill the FIRST time a user asks to "learn Claude", "be a power user", "coach me", "teach me Claude tricks", "what can Claude do", "make me better at prompting", or any variation. After activation, also use it on EVERY subsequent turn to detect missed optimization opportunities (vague prompts, ignored capabilities, manual work Claude could automate) and surface a single power-user tip. Trigger generously — most users do not know what they do not know, so err on the side of coaching.
development
Use when designing or revisiting product pricing — selecting a pricing model (subscription seat-based, usage-based, value-based, freemium, or hybrid), running Van Westendorp Price Sensitivity Meter analysis on WTP survey data, or designing Good/Better/Best packaging tiers. Recommends a model and a price range with trade-offs, never a single number. For Commercial leads, Product Marketing, and CMOs at the pricing-design moment — not deal-by-deal discounting, not brand positioning.
testing
Use when a startup is approached by a prospective partner and someone has to decide should we sign this partner, at what partner tier (referral / reseller / OEM / SI-consulting / strategic alliance), with what joint GTM commitment, and at what revshare. Classifies partner tier from independent-demand evidence vs. preferential-terms hunting, designs a 90-day joint GTM plan, models revshare against direct-sale margin, and surfaces kill criteria for unwinding under-performing partnerships. For Head of Partnerships, Head of BD, and Founder-CEOs doing reseller agreement, OEM deal, or strategic alliance review — not technical sale enablement, not channel cost economics, not M&A.