Agent skill

Reviewer Handoff

by ntorga in ntorga/agent-starter-kit

Structured review summary format with verdict logic and coverage scoring.

MITAuto-check passedAI & LLM Engineering

Install Reviewer Handoff

skills CLI
$ npx skills add ntorga/agent-starter-kit --skill reviewer-handoff -a claude-code

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

GitHub CLI
$ gh skill install ntorga/agent-starter-kit reviewer-handoff --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/ntorga/agent-starter-kit.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/reviewer-handoff .claude/skills/reviewer-handoff && 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
reviewer-handoff
GitHub stars
146
Token cost
~393 tokens
SKILL.md length
151 words
Files
1
Skills in repo
21
Repo updated
First seen
Licence
MIT

At a glance

Structured review summary format with verdict logic and coverage scoring.

  • Works in 3 steps: Assemble the handoff using the template… → Determine the verdict. → Append planned commits on failure. When…
  • AI & LLM Engineering work in your project
  • SKILL.md covers Purpose, Procedure and Guardrails
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Reviewer Handoff is an agent skill from ntorga/agent-starter-kit. Structured review summary format with verdict logic and coverage scoring.

Its SKILL.md is about 390 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.

When your agent uses it

  • AI & LLM Engineering work in your project

Example prompts

  • “/reviewer-handoff”

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. Assemble the handoff using the template below. The progress file path is required — it contains all findings.
  2. Determine the verdict.
  3. Append planned commits on failure. When the verdict is fail and the type is code, add a "Planned Commits" section after the summary. Write…

What it can do on your machine

Read from SKILL.md and the folder at commit 851e942. 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

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

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

  • Network

    No URLs in SKILL.md.

    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

Reviewer Handoff loads about 393 tokens when it runs. Until then it costs about 23 tokens; SKILL.md has 151 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~23
When it runs · the whole SKILL.md, loaded when a task matches
~393

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 ntorga/agent-starter-kit at commit 851e942, republished under its MIT licence (© ntorga). 151 words, ~393 tokens.

Download SKILL.mdSave it as .claude/skills/reviewer-handoff/SKILL.md (or your agent's skills folder).
name
reviewer-handoff
description
Structured review summary format with verdict logic and coverage scoring.
usedBy
reviewer
version
0.2.0
lastUpdated
2026-09-12

Purpose

This skill defines the output format for review handoffs — the structured summary a Reviewer delivers after inspecting work. The progress file (.memory/reviews/review-<type>-<timestamp>.md) contains the full findings trail. The handoff adds the verdict and planned commits on failure.

Procedure

  1. Assemble the handoff using the template below. The progress file path is required — it contains all findings.
markdown
## Review Summary

**Verdict:** <pass | partial-pass | fail>
**Type:** <code | architecture | documentation | configuration | other>
**Progress file:** <path to review progress file>

## SHIELD Self-Review Scorecard
[Complete the scorecard from `skills/reviewer-self-review/SKILL.md`]
  1. Determine the verdict.

    • pass — zero blockers and all review phases completed.
    • partial-pass — zero blockers but a review phase was skipped (e.g., external tool unavailable).
    • fail — one or more blockers.
  2. Append planned commits on failure. When the verdict is fail and the type is code, add a "Planned Commits" section after the summary. Write conventional-commit messages (follows: rules/git.md) for each requested fix. This gives the next step ready-made commit messages once the fixes land.

Guardrails

  • Never omit the Progress file reference — it contains the full analysis trail and is required on every review.

© ntorga, 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 skills/reviewer-handoff of ntorga/agent-starter-kit.

Open the folder on GitHubat commit 851e942

Compare with similar skills

Reviewer Handoff 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.

Reviewer Handoff compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Reviewer Handoff this skillntorga/agent-starter-kit146—~393Automated safety check: PassMIT
AI Research Reproductionlllllllama/RigorPilot-Skills4971 repos~1.8kAutomated safety check: PassMIT
Onnxtxtonnx/onnx22k—~1.3kAutomated safety check: PassApache-2.0
Add Publication DocsRLinf/RLinf5.5k—~1.1kAutomated safety check: PassApache-2.0
Create Simple Promptpnp/copilot-prompts893—~2.6kAutomated safety check: PassMIT
Google Agents CLI Adk Codepifferologo/cloud-agents-cli1291 repos~768Automated safety check: PassApache-2.0

Similar skills

  • AI Research Reproduction

    lllllllama/RigorPilot-Skills

    Rigor Reproduce compatible skill slug for README-first deep learning repository reproduction.

    497 GitHub starsUsed in 1 repo~1.8k tokens
    AI & LLM EngineeringAuto-check passed
  • Onnxtxt

    onnx/onnx

    Read or write ONNX text format ("onnxtxt"). An agent skill from onnx/onnx.

    22k GitHub stars~1.3k tokensUpdated today
    AI & LLM EngineeringAuto-check passed
  • Adds a new publication page to the RLinf Sphinx docs (EN + ZH) and wires it into the Publications index/toctree.

    5.5k GitHub stars~1.1k tokensUpdated yesterday
    AI & LLM EngineeringAuto-check passed
  • Create Simple Prompt

    pnp/copilot-prompts

    This skill should be used when the user asks to "create a new prompt sample", "add a new prompt sample", "scaffold a new prompt sample", "create a prompt contribution", "add a prompt", or needs to…

    893 GitHub stars~2.6k tokensUpdated 4 days ago
    AI & LLM EngineeringAuto-check passed
  • Google Agents CLI Adk Code

    pifferologo/cloud-agents-cli

    This skill should be used when the user wants to "write agent code", "build an agent with ADK", "add a tool", "create a callback", "define an agent", "use state management", or needs ADK (Agent…

    129 GitHub starsUsed in 1 repo~768 tokens
    AI & LLM EngineeringAuto-check passed
  • Llmobs Testing

    DataDog/dd-trace-js

    Official

    A skill your agent uses when writing, modifying, or debugging tests for an LLMObs plugin in dd-trace-js.

    837 GitHub stars~2k tokensUpdated today
    AI & LLM EngineeringAuto-check passed

More from ntorga/agent-starter-kit

All 21 skills in this repo
  • Agent Decision

    ntorga/agent-starter-kit

    Deterministic self-evaluation rubric for decision escalations — scored every run using the FRAME framework.

    146 GitHub stars~1.7k tokensUpdated 27 days ago
    Auto-check passed
  • Agent Memory

    ntorga/agent-starter-kit

    Long-term and session memory across sessions. An agent skill from ntorga/agent-starter-kit.

    146 GitHub stars~2.7k tokensUpdated 27 days ago
    Auto-check passed
  • Architect Design Tree

    ntorga/agent-starter-kit

    Builds the design tree for the grill — decisions mapped as nodes with dependencies, recommendations, and impact, pruned by path.

    146 GitHub stars~1.2k tokensUpdated 27 days ago
    Auto-check passed
  • Architect Impl Grounding

    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.

    146 GitHub stars~944 tokensUpdated 27 days ago
    Auto-check passed
  • Boot

    ntorga/agent-starter-kit

    Session startup — gitignore, auto-update, memory, rules, context, CLI config, and greet.

    146 GitHub stars~937 tokensUpdated 27 days ago
    Auto-check passed
  • Browser Inspect

    ntorga/agent-starter-kit

    Browser inspection and interaction for verifying rendered web UI during development.

    146 GitHub stars~2k tokensUpdated 27 days ago
    Auto-check passed

Questions about Reviewer Handoff

What does Reviewer Handoff do?

Structured review summary format with verdict logic and coverage scoring. Reviewer Handoff is an agent skill from ntorga/agent-starter-kit. Structured review summary format with verdict logic and coverage scoring.

When should I use Reviewer Handoff?

Reviewer Handoff fits situations like: AI & LLM Engineering work in your project.

How do I install Reviewer Handoff in Claude Code?

Run `npx skills add ntorga/agent-starter-kit --skill reviewer-handoff -a claude-code`. Or copy the skill folder (skills/reviewer-handoff in ntorga/agent-starter-kit) into .claude/skills/reviewer-handoff in your project. Claude Code loads it when a task matches its description.

How do I install Reviewer Handoff in Codex?

Run `npx skills add ntorga/agent-starter-kit --skill reviewer-handoff -a codex`. Or copy the skill folder (skills/reviewer-handoff in ntorga/agent-starter-kit) into .agents/skills/reviewer-handoff in your project. Codex loads it when a task matches its description.

Can I use Reviewer Handoff 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 ntorga/agent-starter-kit --skill reviewer-handoff -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/reviewer-handoff, .gemini/skills/reviewer-handoff, .github/skills/reviewer-handoff and .opencode/skills/reviewer-handoff in your project.

What does Reviewer Handoff need to run?

SKILL.md names no scripts, command-line tools or credentials: Reviewer Handoff is instructions for the agent only.

Does Reviewer Handoff access the network?

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.

Is Reviewer Handoff 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 Reviewer Handoff use?

Reviewer Handoff 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 Reviewer Handoff use?

About 393 tokens (SKILL.md is roughly 1.6k 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 Reviewer Handoff?

Skills that share tags, products or a category with Reviewer Handoff: AI Research Reproduction (lllllllama/RigorPilot-Skills, 497 stars), Onnxtxt (onnx/onnx, 22k stars), Add Publication Docs (RLinf/RLinf, 5.5k stars) and Create Simple Prompt (pnp/copilot-prompts, 893 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Reviewer Handoff?

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.