What problem does it solve? Critical modules often become dark code when comprehension lives only in the heads of departed engineers, leaving teams and AI agents unable to safely modify them. This Skill interviews you about a module's structure, interfaces, and design rationale, then produces three documentation artifacts that make the module self-describing. ## Core Features & Use Cases - Three-Layer Interview: Walks through structural context (dependencies, data flows, deployment), semantic context (idempotency, failure modes, retry semantics), and philosophical context (design decisions, rejected alternatives, hidden constraints). - Production-Ready Artifacts: Outputs a module manifest, behavioral contracts per interface, and a decision log formatted as Markdown files ready to commit to a repository. - Gap Capture: Records unknown reasoning explicitly (e.g., original author departed) and flags dark code hotspots like undocumented shared caches instead of inventing answers. - Use Case: After a dark code audit flags a high-risk payment service whose author left the team, run this Skill to interview the current maintainers and produce a MODULE_MANIFEST.md, interface contracts, and a decision log warning that parallelizing its calls would break a downstream concurrency limit. ## Quick Start Ask the agent to use the context-layer-generator skill to document your billing module, starting with its name and a brief description of what it does.
