Agent Builder
shareAI-lab/learn-claude-code
Design and build AI agents for any domain. An agent skill from shareAI-lab/learn-claude-code.
Two-mode review loop — single reviewer per epic, three reviewers for full branch.
$ npx skills add ntorga/agent-starter-kit --skill review-loop -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install ntorga/agent-starter-kit 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/ntorga/agent-starter-kit.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/review-loop .claude/skills/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 "review-loop" agent skill from https://github.com/ntorga/agent-starter-kit/tree/main/skills/review-loop into .claude/skills/review-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "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/ntorga/agent-starter-kit/tree/main/skills/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 ntorga/agent-starter-kit --skill review-loop -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install ntorga/agent-starter-kit review-loop --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ntorga/agent-starter-kit.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/review-loop .agents/skills/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 "review-loop" agent skill from https://github.com/ntorga/agent-starter-kit/tree/main/skills/review-loop into .agents/skills/review-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "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 ntorga/agent-starter-kit --skill review-loop -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install ntorga/agent-starter-kit review-loop --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ntorga/agent-starter-kit.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/review-loop .cursor/skills/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 "review-loop" agent skill from https://github.com/ntorga/agent-starter-kit/tree/main/skills/review-loop into .cursor/skills/review-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "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/ntorga/agent-starter-kit.git --path skills/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 ntorga/agent-starter-kit --skill review-loop -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install ntorga/agent-starter-kit review-loop --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ntorga/agent-starter-kit.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/review-loop .gemini/skills/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 "review-loop" agent skill from https://github.com/ntorga/agent-starter-kit/tree/main/skills/review-loop into .gemini/skills/review-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "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 ntorga/agent-starter-kit 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 ntorga/agent-starter-kit --skill review-loop -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/ntorga/agent-starter-kit.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/review-loop .github/skills/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 "review-loop" agent skill from https://github.com/ntorga/agent-starter-kit/tree/main/skills/review-loop into .github/skills/review-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "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 ntorga/agent-starter-kit --skill 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 ntorga/agent-starter-kit review-loop --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ntorga/agent-starter-kit.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/review-loop .opencode/skills/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 "review-loop" agent skill from https://github.com/ntorga/agent-starter-kit/tree/main/skills/review-loop into .opencode/skills/review-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "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.
review-loopTwo-mode review loop — single reviewer per epic, three reviewers for full branch.
Review Loop is an agent skill from ntorga/agent-starter-kit. Two-mode review loop — single reviewer per epic, three reviewers for full branch.
Its SKILL.md is about 1.3k 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 AI & LLM Engineering. The repository describes itself as: The scaffold for your multi-model, personalized Natural Language AI Harness (NLAH) . The licence is MIT.
8 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 851e942. It shows what the files ask for, not the result of running them.
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.
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Review Loop loads about 1.3k tokens when it runs. Until then it costs about 23 tokens; SKILL.md has 671 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.
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.
The full file from ntorga/agent-starter-kit at commit 851e942, republished under its MIT licence (© ntorga). 671 words, ~1,333 tokens.
.claude/skills/review-loop/SKILL.md (or your agent's skills folder).This skill defines how the Maestro reviews sub-agent work before it reaches the user. Two modes serve different needs. Incremental reviews (per epic) use one reviewer. Full branch reviews (at feature completion) dispatch three reviewers for full coverage.
Determine mode.
impl.md are marked ✓ and the review covers the entire branch's accumulated changes. Triggered by skills/plan-management/SKILL.md → Tracking Progress.Identify scope. Determine the changed files. Use the command matching the current mode:
git diff HEAD --name-only; git ls-files --others --exclude-standardgit diff "$(git merge-base HEAD main)" --name-only; git ls-files --others --exclude-standardIf no files changed, skip the review loop.
Dispatch. Dispatch the reviewer (personas/reviewer.md) (follows: skills/dispatch/SKILL.md).
Incremental mode — single dispatch. Reviewer runs all three lenses.
Full branch mode — three dispatches with focused <task>:
skills/code-coherence-review/SKILL.md).skills/code-quality-review/SKILL.md).skills/code-sec-review/SKILL.md).For plans and non-code work, use a single dispatch regardless of mode.
The <task> for every reviewer dispatch must include:
<task> or acceptance criteria.Merge findings. When all dispatched reviewers return:
For single-dispatch reviews (incremental mode), use its findings directly.
Verify findings. Before acting on any reviewer output, spot-check each blocker and warning against the codebase. Reviewers can hallucinate — flag false positives (invented violations, misread paths, fabricated rules) and discard them. Only confirmed findings proceed. When confirmed hallucinations appear, classify the cause before re-dispatching:
After verifying reported findings, spot-check for missing findings. Pick the first 3 paths in the changed code that involve error handling, authentication, authorization, data mutation, or external I/O, and verify the reviewers addressed them. A reviewer that returns zero findings on complex changes is suspect. A clean bill from a skimmed review is a false pass.
Determine the verdict.
pass — zero confirmed blockers and all review steps completed.partial-pass — zero confirmed blockers but one or more review steps were skipped (e.g., external tool unavailable). Surface the gap to the user.fail — one or more confirmed blockers.Handle failure. If the verdict is fail:
personas/architect.md) (follows: skills/dispatch/SKILL.md) with the confirmed findings. If the failed artifact is code, re-dispatch the Coder (personas/coder.md) (follows: skills/dispatch/SKILL.md) with the findings (blockers, warnings, notes).pass or partial-pass. If the cycle exceeds 2 re-dispatches without reaching a passing verdict, yield to the user with the confirmed findings, conflicting verdicts, or ambiguous trade-offs that could not be resolved.Handle success. If the verdict is pass and the artifact is code from a plan, mark the epic as delivered in impl.md (follows: skills/plan-management/SKILL.md → Tracking Progress).
© ntorga, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in skills/review-loop of ntorga/agent-starter-kit.
Open the folder on GitHubat commit 851e942
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 |
|---|---|---|---|---|---|---|
| Review Loop this skillntorga/agent-starter-kit | 146 | — | ~1.3k | Automated safety check: Pass | MIT | |
| Agent BuildershareAI-lab/learn-claude-code | 78k | 6 repos | ~1.2k | Automated safety check: Pass | MIT | |
| Add Uint Supportpytorch/pytorch | 104k | 2 repos | ~2.3k | Automated safety check: Pass | Custom licence | |
| Peft Fine TuningOrchestra-Research/AI-Research-SKILLs | 13k | 9 repos | ~3.1k | Automated safety check: Pass | MIT | |
| Segment Anything Model GuideOrchestra-Research/AI-Research-SKILLs | 13k | 9 repos | ~3.3k | Automated safety check: Pass | MIT | |
| 1passwordtrpc-group/trpc-agent-go | 1.8k | 15 repos | ~656 | Automated safety check: Pass | Apache-2.0 |
shareAI-lab/learn-claude-code
Design and build AI agents for any domain. An agent skill from shareAI-lab/learn-claude-code.
pytorch/pytorch
Add unsigned integer (uint) type support to PyTorch operators by updating ATDISPATCH macros.
Orchestra-Research/AI-Research-SKILLs
Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods.
Orchestra-Research/AI-Research-SKILLs
Guide to using Meta's Segment Anything Model for zero-shot image segmentation with point, box or mask prompts, or automatic mask generation.
trpc-group/trpc-agent-go
Set up and use 1Password CLI (op). An agent skill from trpc-group/trpc-agent-go.
Orchestra-Research/AI-Research-SKILLs
Shows how to store documents and embeddings in Chroma, query them by similarity with metadata filters, and persist them to disk for RAG and semantic search projects.
ntorga/agent-starter-kit
Deterministic self-evaluation rubric for decision escalations — scored every run using the FRAME framework.
ntorga/agent-starter-kit
Long-term and session memory across sessions. An agent skill from ntorga/agent-starter-kit.
ntorga/agent-starter-kit
Builds the design tree for the grill — decisions mapped as nodes with dependencies, recommendations, and impact, pruned by path.
ntorga/agent-starter-kit
Grounds the grill's settled decisions in the codebase — annotates impl.md with file paths, signatures, reference files, test specs, and LOC; re-grounds the next epic after each landing.
ntorga/agent-starter-kit
Session startup — gitignore, auto-update, memory, rules, context, CLI config, and greet.
ntorga/agent-starter-kit
Browser inspection and interaction for verifying rendered web UI during development.
Categories
Two-mode review loop — single reviewer per epic, three reviewers for full branch. Review Loop is an agent skill from ntorga/agent-starter-kit. Two-mode review loop — single reviewer per epic, three reviewers for full branch.
Review Loop fits situations like: AI & LLM Engineering work in your project.
Run `npx skills add ntorga/agent-starter-kit --skill review-loop -a claude-code`. Or copy the skill folder (skills/review-loop in ntorga/agent-starter-kit) into .claude/skills/review-loop in your project. Claude Code loads it when a task matches its description.
Run `npx skills add ntorga/agent-starter-kit --skill review-loop -a codex`. Or copy the skill folder (skills/review-loop in ntorga/agent-starter-kit) into .agents/skills/review-loop in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ntorga/agent-starter-kit --skill 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/review-loop, .gemini/skills/review-loop, .github/skills/review-loop and .opencode/skills/review-loop in your project.
SKILL.md names no scripts, command-line tools or credentials: Review Loop is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
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.
Review Loop is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.3k tokens (SKILL.md is roughly 5.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Review Loop: Agent Builder (shareAI-lab/learn-claude-code, 78k stars), Add Uint Support (pytorch/pytorch, 104k stars), Peft Fine Tuning (Orchestra-Research/AI-Research-SKILLs, 13k stars) and Segment Anything Model Guide (Orchestra-Research/AI-Research-SKILLs, 13k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
ntorga (a GitHub user) maintains it in ntorga/agent-starter-kit, which has 146 GitHub stars. The repository holds 21 skills in this directory. The repository was last updated on September 12, 2026.
Source: ntorga/agent-starter-kit on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.