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Diagnose and fix macOS TCC permission dialogs and silent denials — Screen Recording, Microphone, Camera, Accessibility, Automation (Apple Events), Full Disk Access, Files & Folders, and the "X would like to access data from other apps" prompt. Use whenever an app or background job is blocked by a macOS privacy permission, a permission dialog reappears after clicking Allow, a LaunchAgent/`uv run` job keeps prompting, System Settings shows a bare version number or wrong name, a granted permission silently stops working after an update, or you need to find WHO is really requesting a permission. Covers reading TCC.db as the ground-truth source, attribution (display name ≠ responsible process), per-binary-path grants, the `uv`-in-launchd Full-Disk-Access trap, `tccutil reset`, and SIP limits. 中文触发：权限弹窗、授权、TCC、完全磁盘访问、Full Disk Access、录屏/麦克风/摄像头/辅助功能/自动化权限被拒、访问其他应用的数据、弹窗一直弹、授权了没用、升级后失效、System Settings 里显示版本号。

daymade/claude-code-skills Agent Skills author: daymade MIT 3 files body ≈ 1 172 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Diagnose and fix macOS TCC permission dialogs and silent denials — Screen Recording, Microphone, Camera, Accessibility, Automation (Apple Events), Full Disk…

As a process C 54/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

AnalyzerAI and agentstype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
B
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
85
Run on models
none yet
Process rating
C
54/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 0

    ✓ No critical or high findings

    Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 54/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 60Tools and files. Uses tools (bash, node) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 5 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1172 tokens
    • 100Running it twice. No mutating operations
    • 100Progress reporting. Reports progress

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Description length 915: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +4Structure: 5 headings
    • +3Step-by-step instructions: 5 items
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.