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    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables coding agents to capture and replay intermittent software failures, minimize reproductions, compare trials, search regressions, verify proposed fixes against a saved failing baseline, and retrieve investigation evidence without rerunning commands.
      86 npm
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables agents to turn a real model failure into a deterministic benchmark task by forging it with exact assertions, grading the task itself across six weighted factors, and inspecting a tamper-evident SHA-384 audit trail. Exposes eleven typed JSON-RPC 2.0 tools that call the same idempotent service layer as the UI, so mutations and decisions stay sealed and reproducible.
      MIT
    • A
      license
      B
      quality
      C
      maintenance
      Enables deterministic security testing of AI agents that use tools by serving synthetic MCP environments with poisoned data, fake secrets, and privileged actions. Records agent tool calls and evaluates security invariants (e.g., canary leaks, forbidden access, approval binding) without an LLM judge or real systems.
      8
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables evidence-first regression testing for AI agents by turning production traces into reviewed, replayable cases that gate releases. It supports reproducible, auditable agent evaluation with controlled tool execution, evidence-based judging, and versioned quality gates.
      MIT