dcf-model

Pass

Audited by Gen Agent Trust Hub on Sep 15, 2026

Risk Level: SAFEEXTERNAL_DOWNLOADSCOMMAND_EXECUTIONINDIRECT_PROMPT_INJECTIONDYNAMIC_EXECUTION
Full Analysis
  • External Data Ingestion: The skill retrieves financial information from SEC filings, analyst reports, and web search results. This process is essential for financial modeling but introduces a potential surface for indirect prompt injection if external sources were to contain instructions intended to influence the agent's behavior. (Category 8)
  • Ingestion points: SEC filings, analyst reports, and web search results referenced in SKILL.md.
  • Boundary markers: The skill focuses on extracting numeric data into structured Excel formulas, which inherently limits instruction following from the source text.
  • Capability inventory: File system access (writing Excel files), network operations (web search), and local command execution (recalc.py, validate_dcf.py).
  • Sanitization: The skill uses a dedicated validation script (validate_dcf.py) and a recalculation tool to ensure the integrity of the generated model.
  • Command Execution & Scripting: The skill utilizes Python scripts to validate model logic and recalculate formulas. Specifically, it executes scripts/validate_dcf.py and references a recalc.py utility provided by the platform's spreadsheet environment. These operations are restricted to the skill's local environment and intended workflow. (Category 4, 10)
  • Standard Dependencies: The skill identifies openpyxl and requests as dependencies in requirements.txt. These are well-known, established libraries for spreadsheet management and HTTP communication, respectively. (Category 4)
Audit Metadata
Risk Level
SAFE
Analyzed
Sep 15, 2026, 03:06 PM
Security Audit — agent-trust-hub — dcf-model