skill-builder-by-rdd
Pass
Audited by Gen Agent Trust Hub on Sep 20, 2026
Risk Level: SAFEINDIRECT_PROMPT_INJECTIONCOMMAND_EXECUTIONEXTERNAL_DOWNLOADSCREDENTIALS_UNSAFE
Full Analysis
- [INDIRECT_PROMPT_INJECTION]: The skill is designed to ingest and process user-provided materials such as laws, tables, and case examples during the discovery phase. This creates a surface for indirect prompt injection if those documents contain malicious instructions. The skill proactively addresses this in its security documentation (
references/SECURITY.md), instructing the agent to treat all uploaded content strictly as data and evidence, and explicitly forbidding the execution of commands found within attachments. - Ingestion points: Discovery and Collection phases in
SKILL.mdwhere external materials are cataloged. - Boundary markers: Explicit instructions in
references/SECURITY.mdandSKILL.mdto ignore 'ignore previous rules' type commands in data. - Capability inventory: Local file reading for linting purposes and execution of validation scripts using the standard Python library.
- Sanitization: The
scripts/lint_bundle.pyscript includes checks for null bytes and specific secret patterns. - [COMMAND_EXECUTION]: The skill bundle includes Python scripts (
lint_bundle.py,scope_gate.py) used for validating the structure and consistency of generated skills. The unit tests intests/test_controls.pyutilizesubprocess.runto invoke these local scripts during the testing phase. This is an expected development practice for tool verification and does not involve executing untrusted network-sourced commands. - [EXTERNAL_DOWNLOADS]: The skill's documentation (
references/RUNTIME_COMPATIBILITY.md) contains links to official specification pages and help articles from well-known services such asagentskills.io, OpenAI, and Anthropic. These references are used for providing platform-specific context and are considered safe. - [CREDENTIALS_UNSAFE]: The skill contains a security linter (
scripts/lint_bundle.py) that implements regex-based detection for sensitive information, such as OpenAI API keys, AWS access keys, and private RSA keys. This feature is intended to prevent the accidental leakage of credentials during the skill development process.
Audit Metadata