AC openclaw-pyautogui
Cross-platform mouse/keyboard automation skill. Supports mouse control (move/click/drag/scroll), keyboard control (key press/hotkeys/type text), screen operations (screenshots/mouse position/screen size), image utilities (metadata/crop), screen overlay markers, drawing markers on images, image locating (template matching + OCR), and file cleanup to free disk space. Activate when the user needs UI automation, screenshots, coordinate verification, image analysis/annotation, on-screen element locating, or cleanup.
As a process C 57/100 · Has gaps — weak spots: inputs and preconditions, consistency, running it twice
How to improve
- 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: 12. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "description_zh"
Process rating: all ten parameters 57/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 3 mutating operations with no state check
- 40Consistency. Frontmatter name (openclaw-pyautogui) differs from the folder (pyautogui)
- 55Failures and branches. 1 branches
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70When it triggers. States when to use, but not when not to
- 70Execution cost. Instruction body is 4504 tokens
- 100Steps. 67 steps
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 14 top-level sections: this looks like several domains in one skill
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)
- -218 emoji in the instructions: noise for the model
- -41 reference files, but SKILL.md never points to them: the model will not open them
- +1No license
- +2Single-language instructions
- +3Description length 516: enough signal without eating the budget
- +4Structure: 60 headings
- +3Step-by-step instructions: 67 items
- +3Output format is stated explicitly
- +4Has examples (35 code blocks)
- +3All 6 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.