dhanoopbhaskar/sdlc-plugins

Generates and maintains OKF v0.2-compliant knowledge bases documenting a codebase's modules, classes, functions, architecture, and configuration. Use when creating a knowledge base for a codebase, updating documentation after code changes, or exporting codebase knowledge in a portable, provenance-tracked format. Not for migration discovery or due-diligence mapping; use legacy-code-discovery for that.

Plans and runs a multi-phase, evidence-graded discovery program for an unfamiliar or legacy estate before a migration, replatform, rewrite, or major upgrade. Use when asked to produce a discovery dossier, estimate migration scope across a whole system, or coordinate reconnaissance, mapping, and risk/seam analysis over multiple sessions. Orchestrates repo-reconnaissance, system-cartography, and migration-seams and writes an OKF v0.2 knowledge bundle. Not for single-file changes, greenfield work, routine code navigation, or routine API documentation.

Turns a system map into migration decisions: scores risks, finds coupling hotspots and shared-data traps, identifies safe migration seams, assesses deployable readiness, compares migration options, and sequences candidate migration slices. Use as the risk-and-seams phase of legacy-code-discovery, or standalone when asked what could break, what must move together, where to start a migration, how to split a monolith or legacy service, or which risks threaten cutover. Prefer legacy-code-discovery when the request spans more than one phase or needs a durable bundle. Not for code review, architecture aesthetics, or selecting a destination stack.

Performs a fast, read-only structural survey of a repository, monorepo, or multi-repo estate before a migration, replatform, or due-diligence assessment. Use as the reconnaissance phase of legacy-code-discovery, or standalone when you need to inventory a codebase for migration scope: which stacks and versions it uses, how it builds, tests, and deploys, which deployable units exist, what should be excluded, or how to split a large repository into workable analysis shards. Prefer legacy-code-discovery when the request spans more than one phase or needs a durable bundle. Produces a repository registry, stack map, and coverage ledger. Not for everyday code exploration, feature work, or behavior analysis.

Behavioral guardrails for SDLC planning, implementation, and review. Use when shaping plans, implementing approved scope, or reviewing changes to surface assumptions, keep solutions simple, enforce surgical diffs, and require verifiable checks.

Maps the internal and external structure of a legacy system for a migration or due-diligence assessment: components, dependency edges, entry points, end-to-end flows, integration contracts, data ownership, and runtime topology. Use as the cartography phase of legacy-code-discovery, or standalone during a migration or due-diligence assessment when asked what depends on what, where requests and events go, or what data is shared. Prefer legacy-code-discovery when the request spans more than one phase or needs a durable bundle. Works from source, build metadata, and contracts without assuming a tech stack. Not for routine code navigation or single-feature analysis.

Verifies AI-generated code changes by enforcing explicit proof of correctness across five core dimensions before declaring a task DONE. Use before accepting or claiming that a task is complete.