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• REA

  Cavanaugh-Design-Studio

  A

  license

  -Not graded

  quality

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  maintenance

  Enables agents to reverse-engineer software across native binaries, managed code, Electron apps, websites, and live runtime behavior, returning findings linked to the evidence and limitations behind each conclusion. It also maintains a durable workspace where those behaviors can be inspected, questioned, compared against real execution, and exported as runnable handoffs.

  Updated 2 days ago (2026-10-15 10:48 UTC)

  231,579 npm

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• HexWitness

  siaginw

  A

  license

  -Not graded

  quality

  A

  maintenance

  Enables AI agents to query persistent, build-scoped evidence memory for reverse engineering, combining static analysis, runtime captures, and claims with honest uncertainty. Provides read-only access to an evidence graph and MCP prompts for structured investigations.

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• io.github.morluto/flameox

  BrianDabrowski64376

  F

  license

  -Not graded

  quality

  A

  maintenance

  Enables coding agents to turn explicit artifacts or commands into bounded local runtime evidence from profilers, benchmarks, trace processors, and direct targets, with typed provenance, coverage, and optional durable preservation. It exposes analysis and capture tools for tracing, profiling, and investigating hotspots in application and native code, GPU kernels, and inference stacks.

  Updated 12 hours ago (2026-10-16 12:14 UTC)

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• REA

  Prompt-Motion

  A

  license

  -Not graded

  quality

  B

  maintenance

  Enables agents to inspect and reverse engineer native binaries, JavaScript/Electron applications, .NET assemblies, websites, and runtime behavior, returning evidence-backed findings that can be explained, implemented, or tested.

  Updated 2 days ago (2026-10-15 05:57 UTC)

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• REA

  zheedevVn

  F

  license

  -Not graded

  quality

  B

  maintenance

  Connects AI agents and CLI users to local analysis tooling that inspects native binaries, JavaScript/Electron apps, .NET assemblies, websites, and saved network captures, returning evidence-backed findings with their limitations. This lets users understand how an existing app feature works and rebuild a similar version in their own project.

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• ChaiChai

  17lijunyi

  A

  license

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  quality

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  maintenance

  Enables AI clients to inspect local software structure, code, and runtime behavior through evidence-backed analysis, including sources, coverage, and limitations.

  Updated 3 days ago (2026-10-14 01:21 UTC)

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