AC desktop-agent-ops
Execute cross-platform desktop tasks through a packaged desktop automation skill that guides the main agent to observe the screen, focus apps and windows, call helper scripts for screenshots and input actions, verify each step, clean up task context, and only escalate to multi-agent collaboration when tasks become clearly multi-window or multi-app. Use when the user wants desktop GUI control, native app operation, window focus, screenshots, click and type flows, or cross-platform desktop workflows on macOS, Windows, or Linux.
As a process C 62/100 · Has gaps — weak spots: result and completion, inputs and preconditions, progress reporting
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 · 1
✓ No critical or high findings
Medium and low: 1
-
low Dangerous commands
cmd-pipe-to-shell-known-hostscripts/first_run_setup.py:635Pipe-to-shell installer from a well-known host (still executes remote code) (string literal in code, not executed)steps.append("Install uv (curl -LsSf https://astral.sh/uv/install.sh | sh) then re-run")code literal
Files scanned: 40. 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 62/100
- 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
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 70Execution cost. Instruction body is 4319 tokens
- 85Steps. 53 steps, 1 vague phrases
- 100When it triggers. States when to use and when not to
- 100Failures and branches. 3 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Running it twice. Mutating operations check current state
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 12 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)
- +3Output format is not stated: the model decides each time
- -311 of 18 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 531: enough signal without eating the budget
- +4Structure: 37 headings
- +3Step-by-step instructions: 53 items
- +4Has examples (18 code blocks)
- +4Reference files are cited in the instructions (15 of 19)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.