User needs to understand something opaque, undocumented, legacy, or partially broken. Agent handles behavioral tracing, artifact mapping, hypothesis testing, and concise documentation for binaries, APIs, file formats, protocols, devices, and human workflows.
Memory lives in ~/reverse-engineering/. If ~/reverse-engineering/ does not exist, run setup.md. See memory-template.md for structure.
text
~/reverse-engineering/
├── memory.md # durable preferences, approvals, and common target types
├── current-target.md # active engagement snapshot
├── targets/ # one file per target or system
└── artifacts/ # traces, decoded notes, and reproduction snippets
Use these files on demand instead of loading the whole method every time.
TopicFileSetup guidesetup.mdMemory templatememory-template.mdTRACE protocolprotocol.mdConfidence modelevidence-ladder.mdSurface mappinginterface-map.mdDeliverable templatesdeliverables.mdSafety boundariesboundaries.md
protocol.md#evidence-ladder.md.interface-map.md before writing an implementation story.deliverables.md: target brief, interface map, hypothesis ledger, reproduction note, and remaining unknowns.These failures usually waste the most time or create false confidence.
TrapWhy It FailsBetter MoveJumping straight to decompilationYou lose the external contract and contextStart with behavior, interfaces, and captured artifactsTreating logs as truthLogs reflect one code path and one viewpointCross-check with traces, outputs, and controlled inputsReverse engineering the whole systemScope explodes and confidence dropsPick one question, one layer, and one target surfaceConfusing correlation with mechanismSimilar timings or names can misleadDesign a falsifiable probe before concludingKeeping findings in loose notesKnowledge becomes untestable and unreusableConvert findings into deliverables with evidence tagsPoking live systems casuallyYou create risk and destroy signalPrefer offline copies, captures, and explicit approvals
Data that leaves your machine:
Data that stays local:
~/reverse-engineering/This skill does NOT:
Install with clawhub install <slug> if user confirms:
analysis — structure ambiguous problems and turn raw evidence into decisionsapi — reason about endpoints, payloads, contracts, and integration behaviorarchitecture — model system boundaries, components, and data flow once the target is understoodbash — build small inspection and replay loops for traces, logs, and artifactscybersecurity — evaluate trust boundaries, attack surface, and safe handling of sensitive targetsclawhub star reverse-engineeringclawhub sync