skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/schema-validation/Gen Agent Trust Hub
schema-validation
Pass
Audited by Gen Agent Trust Hub on Sep 18, 2026
Risk Level: SAFEINDIRECT_PROMPT_INJECTIONDATA_EXFILTRATION
Full Analysis
- [INDIRECT_PROMPT_INJECTION]: The skill is designed to ingest and validate data from external sources, which creates a potential surface for malicious instructions to be embedded within data files.
- Ingestion points: According to
instructions.md, the agent is expected to accept project data from CSV, Excel, and JSON files or direct user input. - Boundary markers: The skill instructions do not define clear delimiters or specific warnings to prevent the agent from following instructions contained within the validated data.
- Capability inventory: As specified in
claw.json, the skill has access tofilesystemandnetworkpermissions, enabling it to read local files and potentially communicate externally. - Sanitization: The
SchemaValidatorclass inSKILL.mdimplements type, range, and regex-based format checks, but it does not sanitize data for LLM instruction patterns. - [DATA_EXFILTRATION]: The skill requests significant environment permissions that increase the impact of potential vulnerabilities.
- Evidence: The
claw.jsonmanifest requests bothfilesystemandnetworkpermissions. While necessary for processing local data files and potentially fetching external schemas, these capabilities could be misused if the agent is successfully targeted by a prompt injection attack.
Audit Metadata