Resume a paused experiment. An agent skill from alirezarezvani/claude-skills.

MITAuto-check passedBusiness, Finance & HR

Install Ar Resume

skills CLI
$ npx skills add alirezarezvani/claude-skills --skill ar-resume -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install alirezarezvani/claude-skills ar-resume --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/alirezarezvani/claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/engineering/autoresearch-agent/skills/ar-resume .claude/skills/ar-resume && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
ar-resume
GitHub stars
28k
Token cost
~529 tokens
SKILL.md length
82 words
Files
1
Skills in repo
342
Repo updated
First seen
Licence
MIT

At a glance

Resume a paused experiment. An agent skill from alirezarezvani/claude-skills.

  • Works in 4 steps: List experiments if needed → Load full context → Report current state → …
  • The user runs /ar:ar-resume
  • SKILL.md covers Usage and What It Does
  • Calls git and python

What it does

Ar Resume is an agent skill from alirezarezvani/claude-skills. Resume a paused experiment. Checkout the experiment branch, read results history, continue iterating. Use when the user runs /ar:ar-resume or asks to pick up a previously started autoresearch experiment.

Its SKILL.md is about 530 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Business, Finance & HR, covering Autonomous loops. The repository describes itself as: 380 Claude Code skills & agent skills & plugins (30+ Agents, 70+ custom commands, 380+ skills, customizable references, scripts)for Claude Code, Codex, Gemini CLI, Cursor, and 8… The licence is MIT.

When your agent uses it

  • The user runs /ar:ar-resume
  • Asks to pick up a previously started autoresearch experiment

Example prompts

  • “/ar-resume”

Requirements

  • Python 3

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. List experiments if needed
  2. Load full context
  3. Report current state
  4. Ask next action

What it can do on your machine

Read from SKILL.md and the folder at commit 19392f7. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • git
    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Ar Resume loads about 529 tokens when it runs. Until then it costs about 53 tokens; SKILL.md has 82 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~53
When it runs · the whole SKILL.md, loaded when a task matches
~529

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from alirezarezvani/claude-skills at commit 19392f7, republished under its MIT licence (© alirezarezvani). 82 words, ~529 tokens.

Download SKILL.mdSave it as .claude/skills/ar-resume/SKILL.md (or your agent's skills folder).
name
ar-resume
description
Resume a paused experiment. Checkout the experiment branch, read results history, continue iterating. Use when the user runs /ar:ar-resume or asks to pick up a previously started autoresearch experiment.
command
/ar:ar-resume

/ar:ar-resume — Resume Experiment

Resume a paused or context-limited experiment. Reads all history and continues where you left off.

Usage

/ar:ar-resume                                  # List experiments, let user pick
/ar:ar-resume engineering/api-speed            # Resume specific experiment

What It Does

Step 1: List experiments if needed

If no experiment specified:

bash
python {skill_path}/scripts/setup_experiment.py --list

Show status for each (active/paused/done based on results.tsv age). Let user pick.

Step 2: Load full context
bash
# Checkout the experiment branch
git checkout autoresearch/{domain}/{name}

# Read config
cat .autoresearch/{domain}/{name}/config.cfg

# Read strategy
cat .autoresearch/{domain}/{name}/program.md

# Read full results history
cat .autoresearch/{domain}/{name}/results.tsv

# Read recent git log for the branch
git log --oneline -20
Step 3: Report current state

Summarize for the user:

Resuming: engineering/api-speed
  Target: src/api/search.py
  Metric: p50_ms (lower is better)
  Experiments: 23 total — 8 kept, 12 discarded, 3 crashed
  Best: 185ms (-42% from baseline of 320ms)
  Last experiment: "added response caching" → KEEP (185ms)

  Recent patterns:
  - Caching changes: 3 kept, 1 discarded (consistently helpful)
  - Algorithm changes: 2 discarded, 1 crashed (high risk, low reward so far)
  - I/O optimization: 2 kept (promising direction)
Step 4: Ask next action
How would you like to continue?
  1. Single iteration (/ar:run)  — I'll make one change and evaluate
  2. Start a loop (/ar:loop)     — Autonomous with scheduled interval
  3. Just show me the results    — I'll review and decide

If the user picks loop, hand off to /ar:loop with the experiment pre-selected. If single, hand off to /ar:run.

© alirezarezvani, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in engineering/autoresearch-agent/skills/ar-resume of alirezarezvani/claude-skills.

Open the folder on GitHubat commit 19392f7

Compare with similar skills

Ar Resume next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Ar Resume compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Ar Resume this skillalirezarezvani/claude-skills28k—~529Automated safety check: PassMIT
ClawlaunchLeoYeAI/openclaw-master-skills2.2k—~5.9kAutomated safety check: PassMIT
Vc Autoresearchwithkynam/vibecode-pro-max-kit1.1k—~3.7kAutomated safety check: PassMIT
Manussanjay3290/ai-skills432—~1.7kAutomated safety check: PassApache-2.0
Polymarket Quant TraderLeoYeAI/openclaw-master-skills2.2k—~4.7kAutomated safety check: NotesMIT
Context ManagerMark393295827/third-brain-v7-skills141—~1.5kAutomated safety check: PassMIT

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Questions about Ar Resume

What does Ar Resume do?

Resume a paused experiment. An agent skill from alirezarezvani/claude-skills. Ar Resume is an agent skill from alirezarezvani/claude-skills. Resume a paused experiment.

When should I use Ar Resume?

Ar Resume fits situations like: the user runs /ar:ar-resume; asks to pick up a previously started autoresearch experiment.

How do I install Ar Resume in Claude Code?

Run `npx skills add alirezarezvani/claude-skills --skill ar-resume -a claude-code`. Or copy the skill folder (engineering/autoresearch-agent/skills/ar-resume in alirezarezvani/claude-skills) into .claude/skills/ar-resume in your project. Claude Code loads it when a task matches its description.

How do I install Ar Resume in Codex?

Run `npx skills add alirezarezvani/claude-skills --skill ar-resume -a codex`. Or copy the skill folder (engineering/autoresearch-agent/skills/ar-resume in alirezarezvani/claude-skills) into .agents/skills/ar-resume in your project. Codex loads it when a task matches its description.

Can I use Ar Resume in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add alirezarezvani/claude-skills --skill ar-resume -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ar-resume, .gemini/skills/ar-resume, .github/skills/ar-resume and .opencode/skills/ar-resume in your project.

What does Ar Resume need to run?

Going by SKILL.md and its folder, Ar Resume needs the command-line tools its instructions call (git and python). Our summary lists: Python 3.

Does Ar Resume access the network?

SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Ar Resume safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Ar Resume use?

Ar Resume is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Ar Resume use?

About 529 tokens (SKILL.md is roughly 2.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Ar Resume?

Skills that share tags, products or a category with Ar Resume: Clawlaunch (LeoYeAI/openclaw-master-skills, 2.2k stars), Vc Autoresearch (withkynam/vibecode-pro-max-kit, 1.1k stars), Manus (sanjay3290/ai-skills, 432 stars) and Polymarket Quant Trader (LeoYeAI/openclaw-master-skills, 2.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Ar Resume?

alirezarezvani (a GitHub user) maintains it in alirezarezvani/claude-skills, which has 27,938 GitHub stars. The repository holds 342 skills in this directory. The repository was last updated on August 30, 2026.

Source: alirezarezvani/claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.