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 skills add aiocean/claude-plugins --skill aio-review-deepgit clone --depth 1 https://github.com/aiocean/claude-pluginsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/aiocean/claude-plugins/aio-review-deep)<a href="https://agentmods.dev/skills/aiocean/claude-plugins/aio-review-deep"><img src="https://agentmods.dev/badge/skills/aiocean/claude-plugins/aio-review-deep.svg" alt="Measured on agentmods" height="20"></a>What 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 5.1 | $0.00068 | $0.04577 |
| Opus 5 | $0.00034 | $0.02289 |
| Sonnet 5 | $0.00014 | $0.00915 |
| Haiku 4.5 | $0.00007 | $0.00458 |
Grade A, and why
aio-review-deep 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 6d ago.
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 — 472 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Fleet Review — Parallel Multi-Agent Code Review
Dispatches a fleet of specialized review agents in parallel, each scrutinizing the diff through a different lens (security, architecture, quality, performance, tests). Uses GitNexus + CodeWiki for deep codebase understanding, then runs adversarial meta-review to synthesize findings. Heavier than aio-review-quick (quick pre-commit sanity check) — reach for this before merging high-impact changes.
Environment
- GitNexus: !
npx gitnexus status 2>/dev/null && echo "AVAILABLE" || echo "NOT INSTALLED" - CodeWiki: !
which codewiki 2>/dev/null || echo "NOT INSTALLED"
When to Use
- User requests "review code", "code review", "review this PR"
- Before merging a pull request
- After implementing a major feature
- User wants quality assessment grounded in codebase structure
Workflow
Phase 0: Detect Tools and Language/Domain
0.1 Tool Availability
Tools are pre-detected in the Environment section above. Adapt the review based on availability:
| Tool | Status | Impact on Review |
|---|---|---|
| GitNexus | Available | Hybrid search, symbol context, dependency tracking, blast radius via impact |
| GitNexus | Missing | Fall back to CodeWiki dependency graphs + manual grep for impact |
| CodeWiki | Available | Module clustering, metrics, dependency graphs |
| CodeWiki | Missing | Skip module mapping — use GitNexus context or file-path grouping |
Proceed with whatever tools are available. Both together give the richest review; either subset still works.
0.2 Detect Language/Domain and Invoke Specialist Skills
Scan the project and changed files to invoke domain-specific static analysis before the general review agents run. Each skill brings specialized linters and pattern checks that general agents cannot replicate.
# Language detection — invoke matching skills
if go.mod or *.go exists:
→ invoke /golang-mastery (go vet, golangci-lint, govulncheck, nilaway, deadcode, race detection)
if *.xcodeproj or Package.swift exists:
→ invoke /ios-mastery (SwiftUI patterns, iOS conventions, Liquid Glass compliance)
# Framework detection — scan changed files for imports
if changed files import "react" or "next":
→ invoke /react-minimal-effects (useEffect anti-patterns, React 19 hooks, React Compiler readiness)
if changed files import "xstate":
→ invoke /xstate (v5 strict patterns, setup().createMachine(), actor patterns)
# Domain detection — based on file paths
if changed files touch infra/, deploy/, monitoring/, or include logging/metrics/tracing code:
→ invoke /monitoring-observability (Golden Signals, OpenTelemetry, SLO compliance)
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.
- 6d ago First seen · 472 lines · 68 tokens per session scan A 45c195cd0e1c
aio-review-deep is a skill published in the GitHub repository aiocean/claude-plugins (4 stars, last pushed 4d ago), licensed MIT. It adds 68 tokens to every session and 4,577 once invoked, about $0.0003 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 2026-08-31.
Other skills, from other repositories
design-patterns
Detect, suggest, and evaluate GoF design patterns in TypeScript/JavaScript codebases. Use when refactoring code, applying singleton/factory/observer/strategy patterns, reviewing pattern quality, or finding stack-native alternatives for React, Angular, NestJS, and Vue.
pr-triage
4-phase PR backlog management with audit, deep code review, validated comments, and optional worktree setup. Use when triaging pull requests, catching up on pending code reviews, or managing a backlog of open PRs. Args: 'all' to review all, PR numbers to focus (e.g. '42 57'), 'en'/'fr' for language, no arg = audit…
audit-agents-skills
Audit Claude Code agents, skills, and commands for quality and production readiness. Use when evaluating skill quality, checking production readiness scores, or comparing agents against best-practice templates.
eval-skills
Audit all skills in the current project for frontmatter completeness, effort level appropriateness, allowed-tools scoping, and content quality. Produces a scored report with effort-level recommendations for each skill. Use when onboarding to a new project, reviewing skill quality before shipping, or adding effort…
review-pr
Perform a comprehensive code review of a pull request.
sonarqube
Analyze SonarCloud quality issues for a specific PR.