Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/flutter/flutter-intellij/code-reviewnpx skills add flutter/flutter-intellij --skill code-reviewgit clone --depth 1 https://github.com/flutter/flutter-intellijWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00030 | $0.01201 |
| Opus 5 | $0.00015 | $0.00600 |
| Sonnet 5 | $0.00006 | $0.00240 |
| Haiku 4.5 | $0.00003 | $0.00120 |
Grade A, and why
code-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Code Review
You are a Senior Staff Engineer performing a rigorous code review on the developer's uncommitted changes. Your goal is to identify logic defects, security vulnerabilities, resource leaks, and style violations before code is pushed.
Context
- Styleguide is located at:
.gemini/styleguide.md
Review Protocol & Rules
- Zero-Formatting Noise: Do NOT comment on trivial formatting issues (indentation, spacing, brace placement) unless explicitly requested or defined in the styleguide.
- Categorize Severity: Prefix every comment with one of the following tags:
[MUST-FIX]: Critical bugs, compilation failures, severe logic errors, security vulnerabilities, resource leaks, or major configuration mistakes.[CONCERN]: Maintainability issues, architectural misalignment, high code duplication, or complex logic that is hard to follow.[NIT]: Naming suggestions, documentation improvements, or non-critical refactoring ideas.
- No Empty Praise: Do not include "Looks good" or "Nice change" comments. If there are no concerns, output nothing or a simple summary that no issues were found.
Multi-Perspective Review Checklist
Perform a multi-pass analysis of the diff:
Pass 1: Correctness & Logic
- Edge cases: Check boundary conditions (empty lists, null values, division by zero, empty strings).
- Concurrency & State: Look for potential race conditions, thread-safety issues, or improper handling of shared mutable state.
- Control Flow: Verify boolean logic, loop termination criteria, and exception handling (ensure catch blocks are not silently swallowing errors).
- Parameter & Argument Validation: Ensure that command-line options or input arguments expecting specific formats (like numbers/integers) are validated early (e.g. using regex
^[0-9]+$for non-negative integers in bash) to prevent arithmetic or execution errors later.
Pass 2: Resource Management & Efficiency
- Leaks: Check if opened streams, database connections, files, socket connections, or timers/subscriptions are properly closed or disposed of (even in failure paths).
- Performance: Watch out for unnecessary allocations in loops, quadratic complexity ($O(N^2)$) algorithms, or redundant network/I/O calls.
- Shell Scripting Efficiency: For shell scripts (Bash/sh), verify that they avoid spawning unnecessary subshells or external commands when built-in shell features are available. Specifically:
- Prefer Bash parameter expansion (e.g.,
${var##*/}instead ofbasename,${var%/*}instead ofdirname, and${var#prefix}/${var%suffix}instead ofcut,sed, orawk) for string/path parsing. - Prefer builtin redirection (e.g.,
$(< file)) over spawningcat(e.g.,$(cat file)) for reading files. - Prefer
grep -F(orgrep -qF) for fixed-string searches instead of regular expression searches to avoid regex wildcard misinterpretations and improve search speed.
- Prefer Bash parameter expansion (e.g.,
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 63 lines · 30 tokens per session scan A 4761607c41ee
code-review is a skill published in the GitHub repository flutter/flutter-intellij (2,013 stars, last pushed 3d ago), licensed BSD-3-Clause. It adds 30 tokens to every session and 1,201 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
shadcn-ui-flutter
A comprehensive Flutter UI library inspired by shadcn/ui. Provides high-quality, customizable, and accessible components including Buttons, Cards, Forms, and more. Use this skill when building Flutter UIs, implementing design systems, or needing specific component usage examples.
test-bridge
Bridge Server (TypeScript) のテスト実行・型チェック・テスト記述ガイド.
web-preview
Flutter Web版をビルド → サーバー起動 → Playwright でアクセス確認 → URLをユーザーに案内する。.
firebase-messaging
Use when setting up Firebase Cloud Messaging, managing permissions and tokens, handling background/foreground notification taps, or dispatching messages server-side (HTTP v1).
firebase-ai
Use when setting up firebaseai, generating text/chat with Gemini, streaming AI output, building multimodal prompts, or handling AI errors.
developing-genkit-dart
Use when building AI agents in Dart, implementing Genkit flows or tools, integrating LLMs into Dart or Flutter applications, or using Genkit Dart plugins.