startup-researcher

Research AI startups, funding, and product announcements. Generates a structured intelligence report as a PDF. Use when asked to research startups, update th...

This skill appears to do what it says: run web research, save per-company markdown profiles, synthesize category analyses, and produce a styled PDF. Before installing or running it, consider: (1) PDF generation: the skill may try to install system C-libraries (apt/brew/dnf) if WeasyPrint is absent — running these commands requires package-manager access and sometimes root privileges, so only allow installs in an environment where you trust the agent to run them; (2) file writes: it will write temporary and final files to your workspace under references/<date>/..., so ensure that directory is appropriate and does not contain sensitive data; (3) web access: the agent will browse and fetch public sites (including paywalled sources like Crunchbase/Pitchbook), so expect network activity and possible rate limits; (4) autonomous invocation: the skill can be invoked autonomously by the agent (default) and has tools to call the browser subagent, run shell commands, and write files — if you want to restrict automated runs, disable or require confirmation before execution. If you want to avoid installs, pre-provision Python + weasyprint + system libraries in the environment and/or instruct the agent not to attempt package-manager installs.

Type: OpenClaw Skill Name: startup-researcher Version: 1.3.2 The skill bundle is classified as suspicious because SKILL.md explicitly instructs the AI agent to use the 'run_command' tool to perform system-level modifications, including installing C-libraries and Python packages via 'apt-get', 'brew', 'dnf', and 'pip'. While these actions are plausibly needed for the stated purpose of rendering PDFs with WeasyPrint, providing an agent with instructions to execute arbitrary system-level installation commands represents a high-risk capability that could be exploited for remote code execution (RCE). No evidence of intentional malice, data exfiltration, or hidden backdoors was found in the code or the research prompts.