Codex with ChatGPT Planning Loop
XiaoDuoYa/codex-with-chatgpt
Uses ChatGPT in the browser as the planning and review brain for a Codex session, with Codex keeping all execution and ChatGPT reading the workspace through a bridge.
Peer Review Ralph Loop — combines Cavekit kits with a Ralph Loop and true cross-model peer review using Codex (OpenAI).
Install Peer Review Loop
$ npx skills add hashgraph-online/awesome-codex-plugins --skill peer-review-loop -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins peer-review-loop --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/JuliusBrussee/blueprint/skills/peer-review-loop .claude/skills/peer-review-loop && rm -rf skills-srcUse ~/.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/
Install the "peer-review-loop" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/JuliusBrussee/blueprint/skills/peer-review-loop into .claude/skills/peer-review-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "peer-review-loop", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/JuliusBrussee/blueprint/skills/peer-review-loopType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add hashgraph-online/awesome-codex-plugins --skill peer-review-loop -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins peer-review-loop --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .agents/skills && cp -r skills-src/plugins/JuliusBrussee/blueprint/skills/peer-review-loop .agents/skills/peer-review-loop && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "peer-review-loop" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/JuliusBrussee/blueprint/skills/peer-review-loop into .agents/skills/peer-review-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "peer-review-loop", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add hashgraph-online/awesome-codex-plugins --skill peer-review-loop -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins peer-review-loop --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/plugins/JuliusBrussee/blueprint/skills/peer-review-loop .cursor/skills/peer-review-loop && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "peer-review-loop" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/JuliusBrussee/blueprint/skills/peer-review-loop into .cursor/skills/peer-review-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "peer-review-loop", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/hashgraph-online/awesome-codex-plugins.git --path plugins/JuliusBrussee/blueprint/skills/peer-review-loop--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add hashgraph-online/awesome-codex-plugins --skill peer-review-loop -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins peer-review-loop --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/plugins/JuliusBrussee/blueprint/skills/peer-review-loop .gemini/skills/peer-review-loop && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "peer-review-loop" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/JuliusBrussee/blueprint/skills/peer-review-loop into .gemini/skills/peer-review-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "peer-review-loop", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install hashgraph-online/awesome-codex-plugins peer-review-loopInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add hashgraph-online/awesome-codex-plugins --skill peer-review-loop -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .github/skills && cp -r skills-src/plugins/JuliusBrussee/blueprint/skills/peer-review-loop .github/skills/peer-review-loop && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "peer-review-loop" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/JuliusBrussee/blueprint/skills/peer-review-loop into .github/skills/peer-review-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "peer-review-loop", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add hashgraph-online/awesome-codex-plugins --skill peer-review-loop -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins peer-review-loop --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/plugins/JuliusBrussee/blueprint/skills/peer-review-loop .opencode/skills/peer-review-loop && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "peer-review-loop" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/JuliusBrussee/blueprint/skills/peer-review-loop into .opencode/skills/peer-review-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "peer-review-loop", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
peer-review-loop- GitHub stars
- 1.2k
- Token cost
- ~2.3k tokens
- SKILL.md length
- 739 words
- Files
- 1
- Skills in repo
- 686
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Peer Review Ralph Loop — combines Cavekit kits with a Ralph Loop and true cross-model peer review using Codex (OpenAI).
- Works in 2 steps: Codex CLI delegation (primary) — Uses… → MCP server (legacy fallback) —…
- Tasks that involve Peer review
- SKILL.md covers Why This Works, Architecture, Quick Start and What the Command Does, plus 8 more sections
- Calls npm and codex
What it does
Peer Review Loop is an agent skill from hashgraph-online/awesome-codex-plugins. Peer Review Ralph Loop — combines Cavekit kits with a Ralph Loop and true cross-model peer review using Codex (OpenAI). Claude builds from specs; Codex reviews adversarially. Primary path: Codex CLI delegation via codex-review.sh (fast, no MCP overhead). Legacy fallback: Codex as MCP server when CLI delegation is unavailable. Covers setup, iteration patterns, convergence detection, and completion criteria. Triggers: "peer review loop", "ralph loop with codex", "cavekit ralph", "peer review build loop"…
Its SKILL.md is about 2.3k 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 Peer review, Autonomous loops and MCP servers. It works with Model Context Protocol and OpenAI. The repository describes itself as: A curated list of awesome OpenAI Codex / ChatGPT plugins, skills, and resources. The 1 Codex Marketplace. See live plugins at: https://hol.org/plugins/best-codex-plugins. The licence is Apache-2.0.
When your agent uses it
- Tasks that involve Peer review
- Tasks that involve Autonomous loops
- Tasks that involve MCP servers
Example prompts
- “peer review loop”
- “ralph loop with codex”
- “cavekit ralph”
- “/peer-review-loop”
Requirements
- Node.js
Workflow steps
2 steps, taken from the first numbered list in SKILL.md.
- Codex CLI delegation (primary) — Uses scripts/codex-review.sh which
- MCP server (legacy fallback) — Configures Codex as an MCP server in
What it can do on your machine
Read from SKILL.md and the folder at commit 78497e5. 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:
npmcodex
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use npm, 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
Peer Review Loop loads about 2.3k tokens when it runs. Until then it costs about 148 tokens; SKILL.md has 739 words of instructions outside code blocks.
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 hashgraph-online/awesome-codex-plugins at commit 78497e5, republished under its Apache-2.0 licence (© hashgraph-online). 739 words, ~2,314 tokens.
Download SKILL.mdSave it as
.claude/skills/peer-review-loop/SKILL.md (or your agent's skills folder).- name
- peer-review-loop
- description
- Peer Review Ralph Loop — combines Cavekit kits with a Ralph Loop and true cross-model peer review using Codex (OpenAI). Claude builds from specs; Codex reviews adversarially. Primary path: Codex CLI delegation via codex-review.sh (fast, no MCP overhead). Legacy fallback: Codex as MCP server when CLI delegation is unavailable. Covers setup, iteration patterns, convergence detection, and completion criteria. Triggers: "peer review loop", "ralph loop with codex", "cavekit ralph", "peer review build loop", "cross-model loop", "codex peer reviewer", "cavekit to ralph loop"
Peer Review Loop — Cavekit + Ralph Loop + Codex Peer reviewer
Run a Cavekit cavekit through a Ralph Loop where Claude builds and Codex adversarially reviews. This is the most rigorous automated quality process available: every few iterations, a completely different model (different training data, different biases, different blind spots) challenges your implementation.
Why This Works
| Factor | Single-Model Loop | Peer Review Loop |
|---|---|---|
| Blind spots | Same model, same blind spots every iteration | Two models catch different classes of issues |
| Cavekit drift | Builder may silently deviate from cavekit | Peer reviewer checks cavekit compliance explicitly |
| Quality floor | Converges to "good enough for one model" | Converges to "survives cross-examination" |
| Dead ends | May retry failed approaches | Peer reviewer flags repeated patterns |
Architecture
┌─────────────────────────────────────────────────────┐
│ Ralph Loop │
│ (Stop hook feeds same prompt each iteration) │
│ │
│ ┌──────────┐ ┌──────────────┐ ┌────────────┐ │
│ │ Claude │───▶│ Build from │───▶│ Commit │ │
│ │ (Build) │ │ cavekit + │ │ changes │ │
│ └──────────┘ └──────────────┘ └──────┬─────┘ │
│ ▲ │ │
│ │ ▼ │
│ ┌──────────┐ ┌──────────────┐ ┌────────────┐ │
│ │ Fix │◀──│ Parse │◀──│ Codex CLI │ │
│ │ findings │ │ findings │ │ (Review) │ │
│ └──────────┘ └──────────────┘ └────────────┘ │
│ │
│ Completion: all cavekit requirements met + │
│ no CRITICAL/HIGH findings │
└─────────────────────────────────────────────────────┘Review Invocation: Codex CLI (primary) vs MCP (legacy)
The peer review loop supports two invocation paths:
Codex CLI delegation (primary) — Uses
scripts/codex-review.shwhich callscodexdirectly in--approval-mode full-autowith a structured review prompt. Faster, no MCP server overhead, findings are parsed and appended tocontext/impl/impl-review-findings.mdautomatically.MCP server (legacy fallback) — Configures Codex as an MCP server in
.mcp.json. Claude calls the MCP tool on review iterations. Used only when Codex CLI delegation is unavailable (e.g., older Codex versions).
The build script (setup-build.sh) auto-detects which path to use: if
codex-review.sh is present and codex CLI is available, it uses CLI
delegation. Otherwise it falls back to MCP configuration.
Quick Start
# Basic: implement a cavekit with peer review
/ck:peer-review-loop context/kits/cavekit-auth.md
# With options
/ck:peer-review-loop context/kits/cavekit-api.md --max-iterations 20 --codex-model gpt-5.4-mini
# Review-only mode (review existing code, don't build new)
/ck:peer-review-loop context/kits/cavekit-api.md --review-only
# Review every iteration instead of every 2nd
/ck:peer-review-loop context/kits/cavekit-auth.md --review-interval 1What the Command Does
- Validates the cavekit file exists and Codex CLI is installed
- Configures Codex as an MCP server in
.mcp.json(if not already configured) - Builds a Ralph Loop prompt that embeds:
- The cavekit path and related plan/impl files
- Instructions to alternate between build and review iterations
- The peer review prompt template for Codex
- Completion criteria tied to cavekit acceptance criteria
- Starts the Ralph Loop via the stop hook mechanism
Codex Review Invocation
Primary: Codex CLI via codex-review.sh
When codex CLI is available, the loop delegates review to scripts/codex-review.sh
which exposes the bp_codex_review function. This runs Codex in full-auto mode with
a structured adversarial review prompt, parses findings into a standardized table, and
appends them to context/impl/impl-review-findings.md.
# What the build loop runs on review iterations:
source scripts/codex-review.sh
bp_codex_review --base mainThe CLI path is faster (no MCP server startup), produces structured findings with severity levels (P0-P3), and handles fallback gracefully if Codex is unavailable.
Legacy fallback: Codex MCP Server
When Codex CLI delegation is not available, the command configures Codex as an MCP server automatically:
{
"mcpServers": {
"codex-reviewer": {
"command": "codex",
"args": ["mcp-server", "-c", "model=\"gpt-5.4\""]
}
}
}Claude calls this MCP server on review iterations to get peer review feedback. The MCP server exposes Codex as a tool that accepts prompts and returns responses — Claude sends the cavekit + code diff, Codex returns findings.
Changing the Codex Model
Use --codex-model to specify which OpenAI model Codex should use:
/ck:peer-review-loop cavekit.md --codex-model gpt-5.4-mini # faster, cheaper
/ck:peer-review-loop cavekit.md --codex-model gpt-5.4 # default, most capableShow full SKILL.md (295 more words)Show less
Iteration Pattern
Iteration 1: BUILD — Read cavekit, implement first requirement
Iteration 2: REVIEW — Call Codex CLI (or MCP fallback), get findings, fix CRITICAL/HIGH
Iteration 3: BUILD — Continue implementing, address remaining findings
Iteration 4: REVIEW — Call Codex CLI (or MCP fallback) again, new findings on new code
...
Iteration N: BUILD — All requirements met, all findings fixed
→ outputs <promise>SPEC COMPLETE</promise>The review interval is configurable. Default is every 2nd iteration.
Use --review-interval 1 for maximum rigor (review every iteration).
Peer Review Findings File
Review findings are tracked in context/peer-review-findings.md:
# Peer Review Findings
## Latest Review: Iteration 4 — 2026-03-14T10:30:00Z
### Reviewer: Codex (gpt-5.4)
| # | Severity | File | Issue | Status |
|---|----------|------|-------|--------|
| 1 | CRITICAL | src/auth.ts:L42 | Missing input validation on token | FIXED |
| 2 | HIGH | src/auth.ts:L67 | Race condition in session refresh | FIXED |
| 3 | MEDIUM | src/auth.ts:L15 | Unused import | NEW |
| 4 | LOW | src/auth.ts:L3 | Comment typo | WONTFIX |
## History
### Iteration 2
| # | Severity | File | Issue | Status |
|---|----------|------|-------|--------|
| 1 | CRITICAL | src/auth.ts:L20 | SQL injection in login query | FIXED |Completion Criteria
The loop exits when the completion promise is output. The prompt instructs Claude to ONLY output it when ALL of these are true:
- All cavekit requirements (R-numbers) have been implemented
- All acceptance criteria pass
- No CRITICAL or HIGH peer review findings remain unfixed
- Build passes
- Tests pass
- At least one review iteration completed with no new CRITICAL/HIGH findings
Modes
Build + Review (default)
Alternates between implementing cavekit requirements and calling Codex for review. Use for greenfield implementation from a cavekit.
Review Only (--review-only)
Skips building. Each iteration calls Codex to review existing code against the cavekit, then fixes issues found. Use when code already exists and you want peer review QA.
Prerequisites
- Codex CLI installed:
npm install -g @openai/codex - OpenAI API key configured: Codex needs authentication (via
codex loginor env var) - Cavekit context directory: Cavekit file must exist at the given path
- Ralph Loop plugin: The ralph-loop plugin must be installed (provides the stop hook)
Convergence Signals
The peer review loop has converged when:
- Codex's findings drop to zero or only LOW/MEDIUM severity
- Code diffs between iterations are minimal
- All cavekit requirements confirmed as met by both Claude and Codex
If the loop hits max iterations without converging:
- Check
context/peer-review-findings.mdfor persistent issues - Consider whether the cavekit needs clarification
- Run
/ck:reviseto trace issues back to kits
Cross-References
- peer-review — The underlying peer review patterns and prompt templates
- convergence-monitoring — How to detect convergence vs ceiling
- validation-first — Validation gates that run on every build iteration
- impl-tracking — How implementation progress is tracked across iterations
- Ralph Loop — The underlying Ralph Loop mechanism
© hashgraph-online, Apache-2.0. 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 plugins/JuliusBrussee/blueprint/skills/peer-review-loop of hashgraph-online/awesome-codex-plugins.
Open the folder on GitHubat commit 78497e5
Compare with similar skills
Peer 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Peer Review Loop this skillhashgraph-online/awesome-codex-plugins | 1.2k | — | ~2.3k | Automated safety check: Pass | Apache-2.0 | |
| Codex with ChatGPT Planning LoopXiaoDuoYa/codex-with-chatgpt | 7.1k | — | ~11k | Automated safety check: Notes | MIT | |
| Cao MCP Appsawslabs/cli-agent-orchestrator | 1.4k | — | ~1.9k | Automated safety check: Pass | Apache-2.0 | |
| Chatgpt AppsHaohao-end/openagent | 807 | 1 repos | ~4.9k | Automated safety check: Pass | Apache-2.0 | |
| Chatgpt App Builderalpic-ai/skybridge | 2.1k | — | ~1k | Automated safety check: Pass | MIT | |
| Agent QA Authoringvostride/agent-qa | 902 | — | ~569 | Automated safety check: Pass | Custom licence |
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Questions about Peer Review Loop
What does Peer Review Loop do?
Peer Review Ralph Loop — combines Cavekit kits with a Ralph Loop and true cross-model peer review using Codex (OpenAI). Peer Review Loop is an agent skill from hashgraph-online/awesome-codex-plugins. Peer Review Ralph Loop — combines Cavekit kits with a Ralph Loop and true cross-model peer review using Codex (OpenAI).
When should I use Peer Review Loop?
Peer Review Loop fits situations like: tasks that involve Peer review; tasks that involve Autonomous loops; tasks that involve MCP servers.
How do I install Peer Review Loop in Claude Code?
Run `npx skills add hashgraph-online/awesome-codex-plugins --skill peer-review-loop -a claude-code`. Or copy the skill folder (plugins/JuliusBrussee/blueprint/skills/peer-review-loop in hashgraph-online/awesome-codex-plugins) into .claude/skills/peer-review-loop in your project. Claude Code loads it when a task matches its description.
How do I install Peer Review Loop in Codex?
Run `npx skills add hashgraph-online/awesome-codex-plugins --skill peer-review-loop -a codex`. Or copy the skill folder (plugins/JuliusBrussee/blueprint/skills/peer-review-loop in hashgraph-online/awesome-codex-plugins) into .agents/skills/peer-review-loop in your project. Codex loads it when a task matches its description.
Can I use Peer 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 hashgraph-online/awesome-codex-plugins --skill peer-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/peer-review-loop, .gemini/skills/peer-review-loop, .github/skills/peer-review-loop and .opencode/skills/peer-review-loop in your project.
What does Peer Review Loop need to run?
Going by SKILL.md and its folder, Peer Review Loop needs the command-line tools its instructions call (npm and codex). Our summary lists: Node.js.
Does Peer Review Loop access the network?
SKILL.md contains no URLs. Its commands use npm, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is Peer Review Loop 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 Peer Review Loop use?
Peer Review Loop is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Peer Review Loop use?
About 2.3k tokens (SKILL.md is roughly 9.3k 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 Peer Review Loop?
Skills that share tags, products or a category with Peer Review Loop: Codex with ChatGPT Planning Loop (XiaoDuoYa/codex-with-chatgpt, 7.1k stars), Cao MCP Apps (awslabs/cli-agent-orchestrator, 1.4k stars), Chatgpt Apps (Haohao-end/openagent, 807 stars) and Chatgpt App Builder (alpic-ai/skybridge, 2.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Peer Review Loop?
hashgraph-online (a GitHub organization) maintains it in hashgraph-online/awesome-codex-plugins, which has 1,242 GitHub stars. The repository holds 686 skills in this directory. The repository was last updated on October 8, 2026.
Source: hashgraph-online/awesome-codex-plugins on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.