Kimi Review

CommunityPopular

davidondrej

kimi-review

Launch an independent Kimi K3.1 Pro Max code review and return it verbatim, falling back across harnesses and routes until one works. Use only when the user explicitly invokes /kimi-review.

Overview

Publisher	davidondrej
Repository	`skills`
Skill name	`kimi-review`
Stars	4.2K
Forks	610
Bundled files	2
License	MIT
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
2 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by davidondrej on GitHub. Read the source before you install it.

Installation

Install the Kimi Review AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/davidondrej/skills/tree/main/skills/agent-orchestration/kimi-review
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/davidondrej/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/agent-orchestration/kimi-review .claude/skills/kimi-review

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Kimi Review in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Kimi Review on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Kimi Review is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Kimi Review

Always use Kimi K3.1 Pro at Max reasoning, orchestrated by Cloudroom. The model and effort never change. Only the harness or route may change, and only to get the review running.

Routes

Try these in order. Move to the next one only when the current one fails.

--provider pi --model vercel-ai-gateway/moonshotai/kimi-k3.1-pro --reasoning-level max
--provider acp-fx --model moonshotai/kimi-k3.1-pro --reasoning-level max (fx uses Vercel AI Gateway)
--provider acp-opencode --model vercel/moonshotai/kimi-k3.1-pro --reasoning-level max
--provider pi --model openrouter/moonshotai/kimi-k3.1-pro --reasoning-level max
--provider acp-opencode --model openrouter/moonshotai/kimi-k3.1-pro --reasoning-level max

Vercel comes first because it keeps no data and does not train on it. OpenRouter serves this model only through Moonshot itself. Vercel routes may incur usage costs.

Pi setup

Pi's built-in catalog lacks this model. Both Pi routes need the entries in references/pi-models.json, placed under providers.<provider>.models in ~/.pi/agent/models.json. If an entry is missing (common in fresh Cloud sandboxes), back up the file, merge the entry in, and confirm with pi --list-models | grep k3.1.

After a models.json edit, Cloudroom's Pi catalog can stay stale for about 5 idle minutes. A stale catalog makes the spawn fail instantly, at no cost. Wait 5 minutes without querying Pi models, then retry once.

Run

Read /room-cli and follow its launch checks. Reuse the current environment, including uncommitted work, and use --parent-self.

A route fails when the spawn errors, room-cli thread show reports a different model or effort, or the first turn errors (gateway errors, auth errors, an empty balance). Stop and archive the failed thread, note its error, and try the next route.

Report a blocker only after every route has failed, with each route's error.

Review brief

Give neutral context: scope, paths, intended behavior, and diff/base revision. Ask for a thorough senior-developer review, including related code and tests, without steering toward suspected bugs, solutions, or verdicts. Review only; do not change files. Request a concise plain-English report of serious or critical issues, fixes, and production merge readiness. Distinguish verified findings from uncertainty and identify validation gaps.

Include this sentence in the brief, word for word: "During your final answer, Rate each issue you find from 1 to 10 on how often it would happen, and 1-10 on how bad it would be"

Result

Use room-cli thread wait and room-cli thread output. Verify this review actually completed; idle status, timeouts, gateway errors, and queued retries are not completion. If a route dies mid-review, start the next route with the same brief.

Return the completed reviewer's full final response verbatim, followed by one line naming the route used.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

agents/openai.yaml1 KB
references/pi-models.json1 KB

Frequently asked questions

What does the Kimi Review AI skill do?

Launch an independent Kimi K3.1 Pro Max code review and return it verbatim, falling back across harnesses and routes until one works. Use only when the user explicitly invokes /kimi-review.

Why use Kimi Review on TypingMind?

Because you install it once and use it with any model. Kimi Review is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Kimi Review in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/davidondrej/skills/tree/main/skills/agent-orchestration/kimi-review. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Kimi Review?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Kimi Review?

As many as you like. As long as a model supports skills, you can use Kimi Review with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Kimi Review AI skill free?

Yes. It is published on GitHub by davidondrej under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Kimi Review

Routes

Pi setup

Run

Review brief

Result

Bundled files

Frequently asked questions

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