Design patterns for building autonomous coding agents. Covers tool integration, permission systems, browser automation, and human-in-the-loop workflows. Use when building AI agents, designing tool APIs, implementing permission systems, or creating autonomous coding assistants.
82
Quality
82%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Critical
Do not install without reviewing
Security
5 findings — 1 critical severity, 1 high severity, 3 medium severity. Installing this skill is not recommended: please review these findings carefully if you do intend to do so.
Detected high-risk code patterns in the skill content — including its prompts, tool definitions, and resources — such as data exfiltration, backdoors, remote code execution, credential theft, system compromise, supply chain attacks, and obfuscation techniques.
Malicious code pattern detected (high risk: 0.85). This content is not overt malware but includes several high-risk patterns that enable deliberate abuse: automatic permission for file reads (easy data exfiltration), dynamic code generation + writing + hot-reload of MCP servers (remote code execution / backdoor creation), use of shell=True and unsanitized subprocess calls, and tools that return raw page screenshots/contexts that can leak sensitive data.
The skill handles credentials insecurely by requiring the agent to include secret values verbatim in its generated output. This exposes credentials in the agent’s context and conversation history, creating a risk of data exfiltration.
Insecure credential handling detected (high risk: 1.00). The skill includes tools (ReadFileTool, ContextManager.add_file/add_folder, format_for_prompt, and ReadFileTool outputs) that unconditionally read file contents into the agent's prompt/history and return them as outputs, which can expose secrets and cause the LLM to include secret values verbatim in generated outputs.
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
Third-party content exposure detected (high risk: 1.00). Yes — SKILL.md explicitly fetches and ingests arbitrary web content (e.g., ContextManager.add_url uses requests.get to add URL content, BrowserTool.open_url/get_page_content load and return page text/screenshots, and VisualAgent.describe_page/find_and_click send page content/screenshots to the LLM), so untrusted third‑party webpages can directly influence agent decisions and tool use.
The skill fetches instructions or code from an external URL at runtime, and the fetched content directly controls the agent’s prompts or executes code. This dynamic dependency allows the external source to modify the agent’s behavior without any changes to the skill itself.
Potentially malicious external URL detected (high risk: 0.90). The ContextManager.add_url method fetches arbitrary external pages at runtime via requests.get(url) and appends that content into the agent's prompt (flagged: any URL passed to ContextManager.add_url / requests.get(url)), allowing remote content to directly control instructions.
The skill prompts the agent to compromise the security or integrity of the user’s machine by modifying system-level services or configurations, such as obtaining elevated privileges, altering startup scripts, or changing system-wide settings.
Attempt to modify system services in skill instructions detected (high risk: 0.90). The skill defines and encourages tools that read/write/edit arbitrary filesystem paths, execute shell commands, and generate/install executable MCP servers (including writing and hot-reloading code), while its safeguards (permission levels, sandbox) are incomplete or optional—so it can be used to modify system files, create services/users, or run privileged actions that compromise the host.
20ba150
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