AC browseros
Use when a task requires interacting with a website beyond just reading it — clicking elements, filling forms, submitting data, navigating through multi-step flows, taking screenshots, or any workflow where the user needs a real browser with actions like click, type, scroll, or select. Also use for managing browser bookmarks, history, or tabs. Trigger whenever the user mentions browseros, browseros-cli, or BrowserOS. Do NOT use when simply fetching or reading page content would suffice — use curl, fetch, or WebFetch for that instead.
As a process C 55/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches
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: 3. 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
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 6 mutating operations with no state check
- 40Consistency. Frontmatter name (browseros) differs from the folder (browseros-agent)
- 100Tools and files. Tools declared in frontmatter
- 100Steps. 17 steps
- 100When it triggers. States when to use and when not to
- 100Execution cost. Instruction body is 1342 tokens
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low The response is described with custom markup (9 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
- +3Output format is not stated: the model decides each time
- -2localhost URLs: will not work for another user
- +1No license
- +2Single-language instructions
- +4Description says when NOT to use the skill
- +3Description length 539: enough signal without eating the budget
- +4Structure: 13 headings
- +3Step-by-step instructions: 17 items
- +4Has examples (5 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.