dcf-model
Pass
Audited by Gen Agent Trust Hub on Apr 2, 2026
Risk Level: SAFEPROMPT_INJECTIONEXTERNAL_DOWNLOADSCOMMAND_EXECUTION
Full Analysis
- [EXTERNAL_DOWNLOADS]: The requirements.txt file includes openpyxl, yfinance, and requests. These are well-known, standard libraries for spreadsheet manipulation and market data retrieval. In accordance with security guidelines, dependencies from these well-known technology services for the skill's primary purpose are documented neutrally.
- [COMMAND_EXECUTION]: The skill instructs the agent to run validation scripts, specifically recalc.py and scripts/validate_dcf.py. This command execution is intended for verifying the integrity and logical consistency of the generated financial models, ensuring the absence of formula errors prior to delivery.
- [PROMPT_INJECTION]: The skill processes financial data retrieved from external sources such as SEC filings, analyst reports, and MCP servers. This constitutes an indirect prompt injection surface where untrusted data could theoretically contain embedded instructions to influence agent behavior. This is a common property of skills that process large volumes of external data.
- Ingestion points: SEC filings, analyst reports, and financial data via MCP servers (identified in SKILL.md).
- Boundary markers: None identified for delimiting untrusted external data.
- Capability inventory: Local file system writes (Excel generation) and Python subprocess execution for model validation (scripts/validate_dcf.py).
- Sanitization: Automated formula error checking via recalc.py and financial logic validation in scripts/validate_dcf.py.
Audit Metadata