SKILLEMALL.ai

CD verify-cua-driver

Verify the Cua Driver daemon and CLI/MCP desktop tools against real fixture apps after driver changes, using Linux diagnostics, AX-first actions, side-effect checks, and retained evidence.

The skillemall take

Claims to verify Cua Driver daemon and CLI/MCP tools after code changes with Linux diagnostics and side-effect checks. Actually a folder with 10 files and 2 scripts, code quality 66%, process score 43%. No critical errors found, but broken_references signal missing files. No model runs, no sandbox tests. Targets 10 platforms yet never ran on any. Skip it—an integration tool meant to catch bugs shouldn't ship with dangling references and unverified paths.

trycua/cua Agent Skills author: trycua 10 files · 2 scripts body ≈ 2 545 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Verify the Cua Driver daemon and CLI/MCP desktop tools against real fixture apps after driver changes, using Linux diagnostics, AX-first actions, side-effect…

As a process D 43/100 · Unfinished process — References files that are not bundled: scripts/ci/linux/run-rust-e2e-wayland.sh, scripts/ci/linux/run-rust-e2e.sh

IntegrationGitHubAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
C
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
66
Run on models
none yet
Process rating
D
43/100
Unfinished process
References files that are not bundled: scripts/ci/linux/run-rust-e2e-wayland.sh, scripts/ci/linux/run-rust-e2e.sh
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. The text references files that are not there: add them or drop the references.
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: 10. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning missing-ref reference to a missing file: scripts/ci/linux/run-rust-e2e-wayland.sh
  • warning missing-ref reference to a missing file: scripts/ci/linux/run-rust-e2e.sh

Process rating: all ten parameters 43/100

Will not run. References files that are not bundled: scripts/ci/linux/run-rust-e2e-wayland.sh, scripts/ci/linux/run-rust-e2e.sh
  • 0Tools and files. 2 referenced file(s) missing: scripts/ci/linux/run-rust-e2e-wayland.sh, scripts/ci/linux/run-rust-e2e.sh
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 3 mutating operations with no state check
  • 50When it triggers. No condition that starts the skill
  • 50Failures and branches. 0 branches, has a failure section
  • 100Steps. 9 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2545 tokens
  • 100Progress reporting. Reports progress
  • high The skill tells the model to perform an irreversible action with no human approval

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 188: enough signal without eating the budget
  • +4Structure: 9 headings
  • +3Step-by-step instructions: 9 items
  • +4Has examples (5 code blocks)
  • +3All 2 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.