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AC browser-cdp

Real Chrome browser automation via CDP Proxy — access pages with full user login state, bypass anti-bot detection, perform interactive operations (click/fill/scroll), extract dynamic JavaScript-rendered content, take screenshots. Triggers (satisfy ANY one): - Target URL is a search results page (Bing/Google/YouTube search) - Static fetch (agent-reach/WebFetch) is blocked by anti-bot (captcha/intercept/empty) - Need to read logged-in user's private content - YouTube, Twitter/X, Xiaohongshu, WeChat public accounts, etc. - Task involves "click", "fill form", "scroll", "drag" - Need screenshot or dynamic-rendered page capture

ClawHub Agent Skills author: Jialin v1.0.0 MIT-0 4 files body ≈ 885 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process C 55/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerYouTubeMedia and videoSoftware developmentAI and agentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
79
Run on models
none yet
Process rating
C
55/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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.
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: 4. 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")

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
  • 20When it triggers. No condition that starts the skill
  • 100Tools and files. No external tools needed
  • 100Steps. 9 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 885 tokens
  • 100Running it twice. No mutating operations
  • 100Progress reporting. Reports progress

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

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -2localhost URLs: will not work for another user
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 2 example trigger phrases
  • +3Description length 629: enough signal without eating the budget
  • +4Structure: 10 headings
  • +3Step-by-step instructions: 9 items
  • +4Has examples (7 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.

External checks

ClawHub: suspicious
This skill is a disclosed real-browser controller, but it gives broad unauthenticated control over logged-in Chrome browsing without enough scoping or consent guardrails.
LLM: suspicious (high) · VirusTotal: · 29 May 2026