graphify
Pass
Audited by Gen Agent Trust Hub on Oct 23, 2026
Risk Level: SAFEINDIRECT_PROMPT_INJECTIONDYNAMIC_EXECUTIONCOMMAND_EXECUTION
Full Analysis
- [INDIRECT_PROMPT_INJECTION]: The skill ingests untrusted data from external task trackers and user-provided ideas to populate decision graphs and task records.\n
- Ingestion points: Remote tracker records (labeled
graphify:map), project configuration files likeAGENTS.md, and user-supplied descriptions inSKILL.md.\n - Boundary markers: The skill utilizes Markdown structural elements (headings, lists) to organize content, though it lacks explicit "ignore embedded instructions" delimiters for data retrieved from remote sources.\n
- Capability inventory: The skill can execute shell commands, run project task runners (
pnpm,python,bun), and perform file system and git operations across multiple scripts (e.g.,references/local-graph.md,references/research.md).\n - Sanitization: No specific sanitization logic is described for data processed from external trackers.\n- [DYNAMIC_EXECUTION]: The skill generates and executes dynamic code as part of its prototyping workflow to answer design and logic questions.\n
- It creates self-contained HTML/JS logic prototypes (
references/logic.md) and UI variations (references/ui.md) that are executed in the user's environment.\n - It uses project-specific task runners (e.g.,
pnpm,python,bun) to launch these experimental artifacts.\n- [COMMAND_EXECUTION]: The skill employs system-level commands to interact with the host environment and present artifacts to the user.\n - It uses tools like
open(macOS) orxdg-open(Linux) to display generated HTML visualizations and prototypes (references/html.md).
Audit Metadata