architect-for-startups

Pass

Audited by Gen Agent Trust Hub on Sep 24, 2026

Risk Level: SAFE
Full Analysis
  • [SAFE]: The skill serves as a recommendation engine for AWS architecture. It guides the agent through a discovery phase, service-specific recommendations, and a challenger framework to ensure advice is stage-appropriate for startups.
  • [INDIRECT_PROMPT_INJECTION]: The skill contains a mechanism (Contextual Offers) that instructs the agent to read data from a relative file path (../knowledge-base-for-startups/references/offers.md). This constitutes an indirect prompt injection surface as the agent ingests data from a source outside the immediate skill body.
  • Ingestion points: SKILL.md contains instructions to read an external offer index and individual offer detail files.
  • Boundary markers: The instructions include behavioral constraints ("condensing eligibility faithfully", "never fabricate") but do not use explicit delimiters like XML tags for the ingested content.
  • Capability inventory: The agent performs file reads and text generation based on the ingested content, including constructing user-clickable URLs.
  • Sanitization: The instructions emphasize faithful extraction, relying on the model's instruction-following capabilities rather than technical filtering.
  • Risk Assessment: This is considered safe as the ingestion targets a sibling skill from the same trusted vendor (awslabs), and the output is presented for human review/interaction rather than automated execution.
  • [DATA_EXPOSURE]: The skill includes a discovery framework (Step 1) that asks users for business-sensitive information (AWS budget, technical team profile, traffic projections). This is a standard part of architectural consulting and does not involve harvesting system secrets or credentials.
  • [DATA_EXFILTRATION]: The skill appends a source parameter to offer URLs to identify the host environment (e.g., claude, vscode). While this leaks metadata about the user's execution environment to the offer destination, it is performed transparently within a user-clickable Markdown link and is a common practice for partner referral attribution.
Audit Metadata
Risk Level
SAFE
Analyzed
Sep 24, 2026, 06:20 PM