setup

alirezarezvani/claude-skills · .gemini/skills/setup/SKILL.md

Set up a new autoresearch experiment interactively. Collects domain, target file, eval command, metric, direction, and evaluator. Use when the user runs /ar:setup or asks to start optimizing a file with the autoresearch loop.

No license★ 25441⑂ 3598commit 19392f7

Install skillView source on GitHub

What this skill does

/ar:setup — Create New Experiment

Set up a new autoresearch experiment with all required configuration.

Usage

/ar:setup                                    # Interactive mode
/ar:setup engineering api-speed src/api.py "pytest bench.py" p50_ms lower
/ar:setup --list                             # Show existing experiments
/ar:setup --list-evaluators                  # Show available evaluators

What It Does

If arguments provided

Pass them directly to the setup script:

python {skill_path}/scripts/setup_experiment.py \
  --domain {domain} --name {name} \
  --target {target} --eval "{eval_cmd}" \
  --metric {metric} --direction {direction} \
  [--evaluator {evaluator}] [--scope {scope}]

If no arguments (interactive mode)

Collect each parameter one at a time:

Domain — Ask: "What domain? (engineering, marketing, content, prompts, custom)"
Name — Ask: "Experiment name? (e.g., api-speed, blog-titles)"
Target file — Ask: "Which file to optimize?" Verify it exists.
Eval command — Ask: "How to measure it? (e.g., pytest bench.py, python evaluate.py)"
Metric — Ask: "What metric does the eval output? (e.g., p50_ms, ctr_score)"
Direction — Ask: "Is lower or higher better?"
Evaluator (optional) — Show built-in evaluators. Ask: "Use a built-in evaluator, or your own?"
Scope — Ask: "Store in project (.autoresearch/) or user (~/.autoresearch/)?"

Then run setup_experiment.py with the collected parameters.

Listing

# Show existing experiments
python {skill_path}/scripts/setup_experiment.py --list

# Show available evaluators
python {skill_path}/scripts/setup_experiment.py --list-evaluators

Built-in Evaluators

| Name | Metric | Use Case | |------|--------|----------| | benchmark_speed | p50_ms (lower) | Function/API execution time | | benchmark_size | size_bytes (lower) | File, bundle, Docker image size | | test_pass_rate | pass_rate (higher) | Test suite pass percentage | | build_speed | build_seconds (lower) | Build/compile/Docker build time | | memory_usage | peak_mb (lower) | Peak memory during execution | | llm_judge_content | ctr_score (higher) | Headlines, titles, descriptions | | llm_judge_prompt | quality_score (higher) | System prompts, agent instructions | | llm_judge_copy | engagement_score (higher) | Social posts, ad copy, emails |

After Setup

Report to the user:

Experiment path and branch name
Whether the eval command worked and the baseline metric
Suggest: "Run /ar:run {domain}/{name} to start iterating, or /ar:loop {domain}/{name} for autonomous mode."

Installation

Copy a source-pinned command for your client. You run it yourself.

Destination: .claude/skills/setup · pinned to the source commit

# Run from your project root
git clone https://github.com/alirezarezvani/claude-skills.git .skillboard-tmp
git -C .skillboard-tmp checkout 19392f7a08264ed00486a251f5b2098321771f94
mkdir -p ".claude/skills"
cp -r ".skillboard-tmp/.gemini/skills/setup" ".claude/skills/"
rm -rf .skillboard-tmp

Review the source before running. This copies files into your project; it is not a one-click install and does not verify runtime safety.

New here? Step-by-step setup – from installing the agent to using the skill

Operating systemAgentI already use Claude Code

1
Install Git
Install Git with your package manager (Debian/Ubuntu shown; use dnf/pacman on others). Official download.
```
sudo apt update && sudo apt install -y git
```
2
Install Claude Code
Requires Node.js 18+. Install the CLI globally: Official docs. (command-line tool)
```
npm install -g @anthropic-ai/claude-code
```

Get the skill, pinned to its exact version

Open a terminal and run these steps (they clone the source, check out the exact commit, and copy the skill into place):

# Run from your project root
git clone https://github.com/alirezarezvani/claude-skills.git .skillboard-tmp
git -C .skillboard-tmp checkout 19392f7a08264ed00486a251f5b2098321771f94
mkdir -p ".claude/skills"
cp -r ".skillboard-tmp/.gemini/skills/setup" ".claude/skills/"
rm -rf .skillboard-tmp

Destination: .claude/skills/setup

4
Use it in Claude Code
Open Claude Code in your project. It reads skills from the folder above, so setup is now available. Always review the source before using it – static checks cannot prove runtime safety.

Security & Audits

Scanner static-checks@0.1.0 · commit 19392f7a0826. Static checks cannot prove runtime safety – review the source and the exact diff before installing. How checks work.

mediumEncoded or obfuscated payload
Uses encoding/eval patterns that can hide executable content.
Evidence: [redacted]· fingerprint 1bbd174404efbce9

setup

alirezarezvani/claude-skills · .gemini/skills/setup/SKILL.md

No license★ 25441⑂ 3598commit 19392f7

Install skillView source on GitHub

What this skill does

/ar:setup — Create New Experiment

Set up a new autoresearch experiment with all required configuration.

Usage

/ar:setup                                    # Interactive mode
/ar:setup engineering api-speed src/api.py "pytest bench.py" p50_ms lower
/ar:setup --list                             # Show existing experiments
/ar:setup --list-evaluators                  # Show available evaluators

What It Does

If arguments provided

Pass them directly to the setup script:

python {skill_path}/scripts/setup_experiment.py \
  --domain {domain} --name {name} \
  --target {target} --eval "{eval_cmd}" \
  --metric {metric} --direction {direction} \
  [--evaluator {evaluator}] [--scope {scope}]

If no arguments (interactive mode)

Collect each parameter one at a time:

Domain — Ask: "What domain? (engineering, marketing, content, prompts, custom)"
Name — Ask: "Experiment name? (e.g., api-speed, blog-titles)"
Target file — Ask: "Which file to optimize?" Verify it exists.
Eval command — Ask: "How to measure it? (e.g., pytest bench.py, python evaluate.py)"
Metric — Ask: "What metric does the eval output? (e.g., p50_ms, ctr_score)"
Direction — Ask: "Is lower or higher better?"
Evaluator (optional) — Show built-in evaluators. Ask: "Use a built-in evaluator, or your own?"
Scope — Ask: "Store in project (.autoresearch/) or user (~/.autoresearch/)?"

Then run setup_experiment.py with the collected parameters.

Listing

# Show existing experiments
python {skill_path}/scripts/setup_experiment.py --list

# Show available evaluators
python {skill_path}/scripts/setup_experiment.py --list-evaluators

Built-in Evaluators

After Setup

Report to the user:

Experiment path and branch name
Whether the eval command worked and the baseline metric
Suggest: "Run /ar:run {domain}/{name} to start iterating, or /ar:loop {domain}/{name} for autonomous mode."

Installation

Copy a source-pinned command for your client. You run it yourself.

Destination: .claude/skills/setup · pinned to the source commit

# Run from your project root
git clone https://github.com/alirezarezvani/claude-skills.git .skillboard-tmp
git -C .skillboard-tmp checkout 19392f7a08264ed00486a251f5b2098321771f94
mkdir -p ".claude/skills"
cp -r ".skillboard-tmp/.gemini/skills/setup" ".claude/skills/"
rm -rf .skillboard-tmp

Review the source before running. This copies files into your project; it is not a one-click install and does not verify runtime safety.

New here? Step-by-step setup – from installing the agent to using the skill

Operating systemAgentI already use Claude Code

1
Install Git
Install Git with your package manager (Debian/Ubuntu shown; use dnf/pacman on others). Official download.
```
sudo apt update && sudo apt install -y git
```
2
Install Claude Code
Requires Node.js 18+. Install the CLI globally: Official docs. (command-line tool)
```
npm install -g @anthropic-ai/claude-code
```

Get the skill, pinned to its exact version

Open a terminal and run these steps (they clone the source, check out the exact commit, and copy the skill into place):

# Run from your project root
git clone https://github.com/alirezarezvani/claude-skills.git .skillboard-tmp
git -C .skillboard-tmp checkout 19392f7a08264ed00486a251f5b2098321771f94
mkdir -p ".claude/skills"
cp -r ".skillboard-tmp/.gemini/skills/setup" ".claude/skills/"
rm -rf .skillboard-tmp

Destination: .claude/skills/setup

4
Use it in Claude Code
Open Claude Code in your project. It reads skills from the folder above, so setup is now available. Always review the source before using it – static checks cannot prove runtime safety.

Security & Audits

Scanner static-checks@0.1.0 · commit 19392f7a0826. Static checks cannot prove runtime safety – review the source and the exact diff before installing. How checks work.

mediumEncoded or obfuscated payload
Uses encoding/eval patterns that can hide executable content.
Evidence: [redacted]· fingerprint 1bbd174404efbce9

setup

What this skill does

/ar:setup — Create New Experiment

Usage

What It Does

If arguments provided

If no arguments (interactive mode)

Listing

Built-in Evaluators

After Setup

Installation

Install Git

Install Claude Code

Get the skill, pinned to its exact version

Use it in Claude Code

Security & Audits

setup

What this skill does

/ar:setup — Create New Experiment

Usage

What It Does

If arguments provided

If no arguments (interactive mode)

Listing

Built-in Evaluators

After Setup

Installation

Install Git

Install Claude Code

Get the skill, pinned to its exact version

Use it in Claude Code

Security & Audits