A guide for viewing and operating macOS applications such as VS Code, Terminal, Finder, Safari, Chrome, and messaging apps. It describes how to inspect windows and perform clear user-requested actions.

Use it to identify the active app, read its interface, activate an app, type, press keys, click menus, or take a screenshot when needed. It also handles unknown app names and reports whether an action succeeded.

It reduces ambiguity when controlling an app and adds a confirmation step after an action.

app_control — Skill by blockcell-labs

Install

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.

agentmods

npx agentmods add skills/blockcell-labs/blockcell/app_control

Any agent

npx skills add blockcell-labs/blockcell --skill app_control

Clone the repo

git clone --depth 1 https://github.com/blockcell-labs/blockcell

Made for: Claude Code, Codex.

Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 416 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. Scan, not verified.

Origin original No closer match found in the catalogue.

Token cost

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	$0.00000	$0.00416
Opus 5	$0.00000	$0.00208
Sonnet 5	$0.00000	$0.00083
Haiku 4.5	$0.00000	$0.00042

Measured 2d ago against content hash cb8ed9bd53f3, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

app_control 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.

skills/app_control/SKILL.md · 33 lines

What it actually says

App Control

Shared {#shared}

适合查看或操作 macOS 应用，例如 Windsurf、VS Code、Terminal、Finder、Safari、Chrome、微信、飞书。
常用名称映射：
- Windsurf -> Windsurf
- VS Code / vscode -> Code
- 终端 -> Terminal
- 访达 -> Finder
- Chrome -> Google Chrome
- 飞书 -> Lark
如果用户没有明确应用名，但问题明显是在问当前前台应用，可先获取前台应用再继续。

Prompt {#prompt}

只有在“目标应用不明确”或“要执行的动作不明确”时才澄清。
查看应用当前状态时，优先策略：
1. 如果未给应用名且明显在问当前界面，先用 app_control 获取 frontmost app。
2. 优先用 read_ui 获取界面结构，默认从较浅层开始。
3. 只有在用户明确要截图，或需要给用户留存视觉证据时，才补 screenshot。
执行动作时，优先策略：
1. 必要时先 activate
2. 再执行 press_key、type、click_menu 等单个明确动作
3. 执行后用 read_ui 或 screenshot 做一次确认
如果应用名解析失败，先用 list_apps 判断是否在运行，再告知用户。
输出要求：
- 说明目标应用
- 说明执行的动作或读到的当前状态
- 说明结果是否成功
- 如果还差一步才能完成，给出下一步建议
不要连续触发多次不必要的界面操作，不要输出 AppleScript 或内部控制细节。

Files

What ships with it

4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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 · 33 lines · 0 tokens per session scan A cb8ed9bd53f3

Subscribe to this mod's changes

app_control is a skill published in the GitHub repository blockcell-labs/blockcell (263 stars, last pushed 18d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 416 tokens. 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.

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

brainstorming

You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

obra/superpowers · 37 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

agent-host-chat-contributions

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.

microsoft/vscode · 56 tokens

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.

microsoft/vscode · 62 tokens