BC tui-tests
Use when writing, fixing, or reviewing tests that render OpenTUI (testRender, createTestRenderer, createAppFixture) in packages/tui or packages/cli. Covers frame waits (waitForFrame, waitFor, waitForVisualIdle, flush), started vs non-started renderers, injected clocks, mock keyboard and mouse input, terminal sizes, cleanup and shared paths, and the 30s budget. Also use when a TUI test fails with "Timed out waiting for frame predicate after N passes", or when a tui test file is slow. For cli subprocess and service tests, use the unit-tests skill.
This skill targets OpenTUI test writing: helps draft and fix tests using testRender, createTestRenderer, createAppFixture. Covers frame waits (waitForFrame, waitFor, waitForVisualIdle, flush), started vs non-started renderers, injected clocks, keyboard and mouse mocking, terminal sizes, cleanup and shared paths. Triggers on "Timed out waiting for frame predicate after N passes" errors.
Code passed checks at grade B: quality 84, process 54. No critical or high findings, linter clean. Description spans 3549 tokens of instruction—enough to handle the framework. One file, no scripts. Supports all major platforms (Claude, Cursor, Copilot, others).
Install if you write TUI tests in those packages and hit frame timeouts. For other scenarios—won't help.
Covers frame waits (waitForFrame, waitFor, waitForVisualIdle, flush), started vs non-started renderers, injected clocks, mock keyboard and mouse input…
As a process C 54/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
The same skill appears in 1 more place: opencode
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: 1. 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
- 30Running it twice. 14 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
- 100Steps. 41 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3549 tokens
- 100Progress reporting. Reports progress
- low The response is described with custom markup (3 tags): a typed call is more reliable
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 551: enough signal without eating the budget
- +4Structure: 8 headings
- +3Step-by-step instructions: 41 items
- +4Has examples (0 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.