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Agent skill

Auto Review Loop

by CurryTang in CurryTang/Amadeus

Autonomous multi-round research review loop. An agent skill from CurryTang/Amadeus.

No licenceAuto-check: notesAgent Workflows

Install Auto Review Loop

skills CLI
$ npx skills add CurryTang/Amadeus --skill auto-review-loop -a claude-code

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

GitHub CLI
$ gh skill install CurryTang/Amadeus auto-review-loop --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/CurryTang/Amadeus.git skills-src && mkdir -p .claude/skills && cp -r skills-src/resource/integrations/aris/overlay/skills/auto-review-loop .claude/skills/auto-review-loop && 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
auto-review-loop
GitHub stars
176
Token cost
~4.3k tokens
SKILL.md length
1,145 words
Files
1
Skills in repo
13
Repo updated
First seen
Licence
None found

At a glance

Autonomous multi-round research review loop. An agent skill from CurryTang/Amadeus.

  • User says auto review loop
  • SKILL.md covers Context: $ARGUMENTS, Step 0: Environment Check, Mode Detection and A.1 Initialization, plus 8 more sections
  • Calls python3, curl and ssh; needs API_TOKEN and TODO_KEY
  • Review until it passes

What it does

Auto Review Loop is an agent skill from CurryTang/Amadeus. Autonomous multi-round research review loop. Supports two modes: (1) Plan-driven: takes an implementation plan file, executes TODO items respecting dependency DAG, uses Codex MCP to verify completion of each item. (2) Free-form: iterates review → fix → re-review until positive assessment. Use when user says 'auto review loop', 'review until it passes', or wants iterative improvement.

Its SKILL.md is about 4.3k 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 Agent Workflows, covering Planning and Quality gates. It works with Model Context Protocol. The repository describes itself as: Your personal AI research assistant that automatically reads, summarizes, organizes, and acts on academic papers.

When your agent uses it

  • User says auto review loop
  • Review until it passes
  • Wants iterative improvement

Example prompts

  • “auto review loop”
  • “review until it passes”
  • “/auto-review-loop”

Requirements

  • Python 3
  • A credential in API_TOKEN
  • A credential in TODO_KEY
  • Pre-approved tools (allowed-tools): Bash(*), Read, Grep, Glob, Write, Edit, Agent, Skill, mcp__codex__codex, mcp__codex__codex-reply

What it can do on your machine

Read from SKILL.md and the folder at commit 72f0e2f. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Bash(*)
    • Read
    • Grep
    • Glob
    • Write
    • Edit
    • Agent
    • Skill
    • mcp__codex__codex
    • mcp__codex__codex-reply

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • python3
    • curl
    • ssh

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

  • Network

    No URLs in SKILL.md. Its commands use curl and ssh, 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 these keys or tokens, usually read from environment variables:

    • API_TOKEN
    • TODO_KEY
    • DEP_KEY
    • NEXT_TODO_KEY

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

Context cost

Auto Review Loop loads about 4.3k tokens when it runs. Until then it costs about 101 tokens; SKILL.md has 1,145 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~101
When it runs · the whole SKILL.md, loaded when a task matches
~4.3k

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: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Bash(*), Read, Grep, Glob, Write, Edit, Agent, Skill, mcp__codex__codex, mcp__codex__codex-reply

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

Without a licence we can't republish the file, so here is its outline and opening line. It has 1,145 words (~4,294 tokens).

name
auto-review-loop
allowed-tools
Bash(*), Read, Grep, Glob, Write, Edit, Agent, Skill, mcp__codex__codex, mcp__codex__codex-reply
argument-hint
[topic-or-scope] [--plan path/to/plan.md]

Read the full SKILL.md on GitHub

Files

Just SKILL.md in resource/integrations/aris/overlay/skills/auto-review-loop of CurryTang/Amadeus.

Open the folder on GitHubat commit 72f0e2f

Compare with similar skills

Auto Review Loop 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.

Auto Review Loop compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Auto Review Loop this skillCurryTang/Amadeus176—~4.3kAutomated safety check: NotesNone
Codex with ChatGPT Planning LoopXiaoDuoYa/codex-with-chatgpt7.1k—~11kAutomated safety check: NotesMIT
Agentic Tool Integrationsamugit83/redamon3k—~1.3kAutomated safety check: PassMIT
Workflow Orchestrationvxcozy/workflow-orchestration116—~1kAutomated safety check: PassMIT
agtx Task Planningfynnfluegge/agtx1.7k—~439Automated safety check: PassApache-2.0
Discoveranombyte93/prd-taskmaster605—~2.4kAutomated safety check: PassMIT

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More from CurryTang/Amadeus

All 13 skills in this repo

  • Research Lit

    CurryTang/Amadeus

    Search and analyze research papers, find related work, summarize key ideas.

    176 GitHub starsUsed in 5 repos~963 tokens
    Auto-check: notes

  • Repo Sync Updater

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    Synchronize a local or WSL clone with its upstream branch and verify backend runtime prerequisites for this project.

    176 GitHub stars~564 tokensUpdated 6 mo ago
    Auto-check passed

  • Sync Workspace

    CurryTang/Amadeus

    Sync local and remote project files bidirectionally. An agent skill from CurryTang/Amadeus.

    176 GitHub stars~1.2k tokensUpdated 6 mo ago
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  • Todo To Node

    CurryTang/Amadeus

    Convert a project TODO item into a ResearchOps tree node via LLM.

    176 GitHub stars~691 tokensUpdated 6 mo ago
    Auto-check passed

  • GPU Status

    CurryTang/Amadeus

    Show GPU availability across all SSH servers listed in this project's CLAUDE.md.

    176 GitHub stars~862 tokensUpdated 6 mo ago
    Auto-check: warnings

  • Project Todo Manager

    CurryTang/Amadeus

    Manage project-management TODO workflows in ResearchOps. An agent skill from CurryTang/Amadeus.

    176 GitHub stars~465 tokensUpdated 6 mo ago
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Works with

Categories

Questions about Auto Review Loop

What does Auto Review Loop do?

Autonomous multi-round research review loop. An agent skill from CurryTang/Amadeus. Auto Review Loop is an agent skill from CurryTang/Amadeus. Autonomous multi-round research review loop.

When should I use Auto Review Loop?

Auto Review Loop fits situations like: user says auto review loop; review until it passes; wants iterative improvement.

How do I install Auto Review Loop in Claude Code?

Run `npx skills add CurryTang/Amadeus --skill auto-review-loop -a claude-code`. Or copy the skill folder (resource/integrations/aris/overlay/skills/auto-review-loop in CurryTang/Amadeus) into .claude/skills/auto-review-loop in your project. Claude Code loads it when a task matches its description.

How do I install Auto Review Loop in Codex?

Run `npx skills add CurryTang/Amadeus --skill auto-review-loop -a codex`. Or copy the skill folder (resource/integrations/aris/overlay/skills/auto-review-loop in CurryTang/Amadeus) into .agents/skills/auto-review-loop in your project. Codex loads it when a task matches its description.

Can I use Auto Review Loop 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 CurryTang/Amadeus --skill auto-review-loop -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/auto-review-loop, .gemini/skills/auto-review-loop, .github/skills/auto-review-loop and .opencode/skills/auto-review-loop in your project.

What does Auto Review Loop need to run?

Going by SKILL.md and its folder, Auto Review Loop needs the command-line tools its instructions call (python3, curl and ssh) and credentials named API_TOKEN, TODO_KEY, DEP_KEY and NEXT_TODO_KEY. Our summary lists: Python 3; A credential in API_TOKEN; A credential in TODO_KEY. Its frontmatter pre-approves these tools: Bash(*), Read, Grep, Glob, Write, Edit, Agent, Skill, mcp__codex__codex, mcp__codex__codex-reply.

Does Auto Review Loop access the network?

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

Is Auto Review Loop safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Auto Review Loop use?

No licence was found for Auto Review Loop or its repository. Without one, default copyright applies: ask the author before reusing or redistributing it.

How many tokens does Auto Review Loop use?

About 4.3k tokens (SKILL.md is roughly 17k 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 Auto Review Loop?

Skills that share tags, products or a category with Auto Review Loop: Codex with ChatGPT Planning Loop (XiaoDuoYa/codex-with-chatgpt, 7.1k stars), Agentic Tool Integration (samugit83/redamon, 3k stars), Workflow Orchestration (vxcozy/workflow-orchestration, 116 stars) and agtx Task Planning (fynnfluegge/agtx, 1.7k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Auto Review Loop?

CurryTang (a GitHub user) maintains it in CurryTang/Amadeus, which has 176 GitHub stars. The repository holds 13 skills in this directory. The repository was last updated on March 25, 2026.

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