SKILLEMALL.ai
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CC god-of-all-browsers

A 100x smarter browser automation CLI that mimics human behavior using a native stateful Chromium instance. It supports multi-tab management, bypasses bot detection, auto-closes popups, and preserves cookies permanently.

Not recommendedcritical or high security findings
ClawHub Agent Skills author: MaThanMiThun1999 v1.0.6 MIT-0 11 files · 1 script body ≈ 2 129 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process C 62/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationInfrastructuretype 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
C
72/100
safety, quality, tests
Safety 60%
72
Quality 40%
71
Run on models
none yet
Process rating
C
62/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Exfiltration
If you install

The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
  2. 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 · 7

  • high Exfiltration intent-browser-credential-store README.md:139
    Accesses a browser credential / cookie store
    *   **Persistent Profiles**: By default, this tool saves all session data, cookies, and local storage in the `./chrome_profile/` directory. This is intentional to allow stateful AI workflows.
Medium and low: 6
  • medium Exfiltration intent-browser-credential-store browser.js:160
    Accesses a browser credential / cookie store (quoted — discussed, not commanded)
    console.log("Your cookies/session are natively stored in 'chrome_profile' folder.");
    quoted
  • low Secrets in code secret-high-entropy-token package-lock.json:41
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…09f+cXft…VU2/9xiCuXMA==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:51
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…bKX+KS9G…yMA/NhKJ…RGz/Q==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:106
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…Wwy+ghLE…vfU/YnxW…fdg==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:207
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…2BV+FY5ZFezP/ypmwayk68+NzzA…NFD/uUmBJuGoXw==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:279
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…GLw+xYSd…cqA==",
    detector

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")
  • note frontmatter-key unknown frontmatter key "tools"

Process rating: all ten parameters 62/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 70Failures and branches. 6 branches
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 22 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2129 tokens
  • 100Running it twice. Mutating operations check current state
  • 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

  • +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 220: enough signal without eating the budget
  • +4Structure: 17 headings
  • +3Step-by-step instructions: 22 items
  • +4Has examples (15 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.

External checks

ClawHub: suspicious
This is a powerful browser automation skill whose core behavior is disclosed, but it combines persistent login sessions, bot-evasion, arbitrary in-page JavaScript, and automatic confirmations in ways users should review carefully.
LLM: suspicious (high) · VirusTotal: · 29 May 2026