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/moasq/ios-dev-agent/listsnpx skills add moasq/ios-dev-agent --skill listsgit clone --depth 1 https://github.com/moasq/ios-dev-agentWhat 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 | $0.00028 | $0.00569 |
| Opus 5 | $0.00014 | $0.00284 |
| Sonnet 5 | $0.00006 | $0.00114 |
| Haiku 4.5 | $0.00003 | $0.00057 |
Grade A, and why
lists 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 2d 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 — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
List Patterns
Use this guide when implementing or modifying list-based UI.
ForEach Identity (CRITICAL)
Always provide stable identity. Never use .indices for dynamic content:
// CORRECT — stable identity via Identifiable
ForEach(users) { user in
UserRow(user: user)
}
// CORRECT — stable identity via keypath
ForEach(users, id: \.userId) { user in
UserRow(user: user)
}
// WRONG — indices create static content, crashes on removal
ForEach(users.indices, id: \.self) { index in
UserRow(user: users[index])
}
Constant View Count per Element
// CORRECT — consistent view count
ForEach(items) { item in
ItemRow(item: item)
}
// WRONG — variable view count breaks identity
ForEach(items) { item in
if item.isSpecial {
SpecialRow(item: item)
DetailRow(item: item)
} else {
RegularRow(item: item)
}
}
Avoid Inline Filtering
// WRONG — unstable identity
ForEach(items.filter { $0.isEnabled }) { item in ... }
// CORRECT — prefilter via computed property
var enabledItems: [Item] {
items.filter { $0.isEnabled }
}
ForEach(enabledItems) { item in ... }
No AnyView in Rows
// WRONG — hides identity
AnyView(item.isSpecial ? SpecialRow(item: item) : RegularRow(item: item))
// CORRECT — unified row view with internal branching
struct ItemRow: View {
let item: Item
var body: some View {
if item.isSpecial { SpecialRow(item: item) }
else { RegularRow(item: item) }
}
}
Enumerated Sequences
Always convert to array:
ForEach(Array(items.enumerated()), id: \.offset) { index, item in
Text("\(index): \(item)")
}
Pull-to-Refresh
List(items) { item in
ItemRow(item: item)
}
.refreshable { await loadItems() }
Custom List Styling
List(items) { item in
ItemRow(item: item)
.listRowInsets(EdgeInsets(top: 8, leading: 16, bottom: 8, trailing: 16))
.listRowSeparator(.hidden)
}
.listStyle(.plain)
.scrollContentBackground(.hidden)
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.
- 2d ago First seen · 100 lines · 28 tokens per session scan A 7027d6373ec2
lists is a skill published in the GitHub repository moasq/ios-dev-agent (4 stars, last pushed 3mo ago), licensed MIT. It adds 28 tokens to every session and 569 once invoked, about $0.0001 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.
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Build and review cross-cutting agent-host chat behavior through lifecycle contributions. Use when adding turn lifecycle side effects, prompt or context injection, restored-history transformation, protocol-action observation, or when reviewing changes that add code to AgentSideEffects or AgentService.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.