SKILLEMALL.ai
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AC record

macOS CLI tool for recording audio (microphone), screen (video/screenshot), and camera (video/photo) from the terminal. Use when the user or an AI agent needs to: (1) record microphone audio, (2) capture screen video or screenshot, (3) capture camera video or photo, (4) list available devices/displays/cameras, or any task involving audio/video/image capture on macOS via the command line. Trigger on keywords like: record, microphone, screen capture, screenshot, screen recording, camera, webcam, photo, audio capture.

modbender/skill-library-mcp Agent Skills author: modbender MIT 4 files body ≈ 999 tokens Open the sourcegithub.com↗ analyzed 3 d ago

macOS CLI tool for recording audio (microphone), screen (video/screenshot), and camera (video/photo) from the terminal.

As a process C 55/100 · Has gaps — weak spots: result and completion, inputs and preconditions, progress reporting

IntegrationMedia and videoAI and agentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw 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) Goose OpenCode
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
88
Run on models
none yet
Process rating
C
55/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
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: 4. 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 55/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 85Steps. 6 steps, 1 vague phrases
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 999 tokens
    • 100Running it twice. No mutating operations

    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)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 520: enough signal without eating the budget
    • +4Structure: 16 headings
    • +3Step-by-step instructions: 6 items
    • +4Has examples (9 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.