AB qqbrowser-use
Browser automation CLI for AI agents. Use when: (1) open, navigate, or interact with a website (fill forms, click, screenshot, download, inspect); (2) extract structured data; (3) analyze already-open tabs without a new tab; (4) record, save, or reuse a browser task (保存为脚本, 录一下, 下次还要用); (5) run an existing playbook. Fallback when web_fetch hits captcha (wappoc)/login/empty SPA. Do NOT use for HTML/CSS/JS questions without a browser task, or bookmarks/history.
As a process B 75/100 · Nearly there — weak spots: consistency, progress reporting
How to improve
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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: 5. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 7607 tokens (recommended < 5000); move details to references/ - note
frontmatter-keyunknown frontmatter key "source" - note
frontmatter-keyunknown frontmatter key "homepage" - note
frontmatter-keyunknown frontmatter key "permissions"
Process rating: all ten parameters 75/100
- 0Progress reporting. Says nothing while it works
- 40Consistency. Frontmatter name (qqbrowser-use) differs from the folder (qqbrowser-skill)
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70Inputs and preconditions. Inputs and preconditions are listed
- 70Execution cost. Instruction body is 7607 tokens
- 100Steps. 42 steps
- 100When it triggers. States when to use and when not to
- 100Failures and branches. 9 branches, has a failure section
- 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 10 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
- -215 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +4Description says when NOT to use the skill
- +3Description length 463: enough signal without eating the budget
- +4Structure: 44 headings
- +3Step-by-step instructions: 42 items
- +3Output format is stated explicitly
- +4Has examples (33 code blocks)
- +4Reference files are cited in the instructions (3 of 3)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.