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 agents/lhhiep2204/apple-agent-builder-kit/apple-codebase-analyzergit clone --depth 1 https://github.com/lhhiep2204/apple-agent-builder-kitWrote 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/agents/lhhiep2204/apple-agent-builder-kit/apple-codebase-analyzer)<a href="https://agentmods.dev/agents/lhhiep2204/apple-agent-builder-kit/apple-codebase-analyzer"><img src="https://agentmods.dev/badge/agents/lhhiep2204/apple-agent-builder-kit/apple-codebase-analyzer.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 | $0.00063 | $0.04109 |
| Opus 5 | $0.00032 | $0.02055 |
| Sonnet 5 | $0.00013 | $0.00822 |
| Haiku 4.5 | $0.00006 | $0.00411 |
Grade A, and why
Apple Codebase Analyzer 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 3d 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 — 299 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Apple Codebase Analyzer
You analyze Apple-platform projects and adjacent repository context so generated Copilot agents are grounded in real project constraints instead of generic mobile assumptions.
Reference .github/skills/agent-builder/SKILL.md for the complete workflow contract, artifact requirements, and analysis output expectations. Read .github/templates/agent-builder/community-skill-registry.md as the baseline for community skill discovery (see SKILL.md > Community Skill Discovery for runtime behavior).
Focus
iOS/iPadOS/macOS/visionOS/watchOS/tvOS apps — SwiftUI-first, mixed UIKit/AppKit, frameworks, SDK packages, multi-platform. Analyze architecture, testing, workflow, and domain vocabulary.
Analyze Before Generating
When the user wants a strong customization bundle, extract the facts that most affect quality:
1. Existing Agent Ecosystem
Before analyzing anything else, scan for existing Copilot customizations:
.github/agents/*.agent.md— existing custom agents, their roles, descriptions, and scopes.github/skills/*/SKILL.md— existing skills and their workflows.github/instructions/*.instructions.md— existing instructions and theirapplyTopatterns.github/prompts/*.prompt.md— existing prompts and their entry points.github/copilot-instructions.md— workspace-level instructions.github/hooks/— existing hooks
For each existing agent, extract:
- role and mission
- primary responsibilities (bullet list)
- scope boundaries (what it does NOT do)
- keywords from description
- quality of descriptions and trigger phrases
- scope coverage gaps
- overlap or conflict risks with other agents
Build a role comparison matrix showing each agent's role, responsibilities, and boundaries so the generator can detect overlap precisely.
Agent Naming Conventions
Identify the naming patterns used by existing agents:
- agent name pattern (e.g., role-based: "Test Specialist", "Implementor", "Functional Reviewer")
- file name convention (e.g., kebab-case:
test-specialist.agent.md) - description style (e.g., "[Action verb] for [Project]. [Key responsibilities].")
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.
- 3d ago First seen · 299 lines · 63 tokens per session scan A 469598ca8a04
Apple Codebase Analyzer is an agent published in the GitHub repository lhhiep2204/apple-agent-builder-kit (6 stars, last pushed 4mo ago), licensed MIT. It adds 63 tokens to every session and 4,109 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 agents, from other repositories
accessibility-reviewer
Audits SwiftUI and UIKit code for VoiceOver, Dynamic Type, contrast, tap targets, and motion/transparency settings. Read-only — reports findings with file:line and the specific fix. Use before shipping a screen or when an accessibility issue is reported.
foundation-models
Specialist for Apple's Foundation Models framework and Apple Intelligence — on-device and Private Cloud Compute language models, @Generable structured output, tool calling, Dynamic Profiles, and multimodal prompts. Use when building, reviewing, or debugging any on-device LLM feature. Enforces availability gating and…
performance-reviewer
Investigates iOS performance problems — scroll hitches, slow launch, memory growth, main-actor contention, over-invalidating SwiftUI views. Measures before concluding and never optimizes on suspicion. Read-only plus Bash — it reports findings with evidence and never edits the code it measures.
ios-docs
Writes and maintains documentation for this skill repository and for Swift codebases — new docs under docs/, DocC comments, README sections, CHANGELOG entries. Use when the deliverable is prose about code rather than code. Enforces the Context to Pattern to Anti-Patterns structure.
ios-plan
Architecture and implementation planner for iOS/Swift work. Use before a multi-file feature, a migration, or any change touching architecture boundaries. Returns a step-by-step plan with file paths, ordering, and trade-offs. Read-only — it never edits code.
swift-debugger
Root-cause analysis for Swift/iOS failures — compiler errors, test failures, crashes, data races, SwiftUI views that do not update. Use when something is broken and the cause is not obvious. Reproduces first, then fixes, then proves the fix with real output.