The Agent Skills Directory

[DYNAMIC_EXECUTION]: The script examples/03_full_optimization.py contains an implementation of a mock calculator tool that uses the Python eval() function to process mathematical expressions. Although the implementation attempts a sandboxed approach by clearing __builtins__ and using a whitelist of functions, eval() is notoriously difficult to secure and could potentially be bypassed if integrated into production environments.
[INDIRECT_PROMPT_INJECTION]: The skill operates by capturing and analyzing reasoning traces from AI agent sessions. These traces contain untrusted data, including user inputs and tool outputs. The TraceAnalyzer and PromptOptimizer components interpolate this data into system prompts to identify patterns or generate new instructions. There is an inherent risk that malicious content within a trace could influence the analysis logic or the generated system prompts.
[EXTERNAL_DOWNLOADS]: The skill makes legitimate network requests to api.minimax.io and uses the anthropic Python SDK to perform its core functions. These are necessary for the skill's stated purpose of utilizing the MiniMax M2.1 reasoning model but should be noted as points of external communication.

reasoning-trace-optimizer