Query the GitLab Knowledge Graph (Orbit) via `glab orbit remote` CLI subcommands or run a local copy with `glab orbit local`. Use for code-structure questions (who calls this function, where is this symbol defined), cross-project dependency and blast-radius analysis, merge-request and contributor queries, and any question answerable by traversing GitLab's unified entity graph (projects, users, MRs, issues, pipelines, files, definitions, vulnerabilities).
Audit and update documentation after code changes. Use when architecture, APIs, or behavior changed and docs may have drifted.
Investigate query evaluation failures in the Knowledge Graph synthetic data pipeline. Use when queries fail or return unexpected results after running the evaluate binary.
Profile GKG queries against ClickHouse with the query-profiler CLI. For optimizing query performance, comparing query plans, investigating slow queries, or checking ClickHouse resource usage.
AST-based code search and rewrite via tree-sitter patterns. Use instead of Grep/Edit for structural matching, batch rewrites, or context-aware queries (e.g. "unwrap inside impl blocks").
Investigate the history, usage, and liveness of code using search and git blame/log. Use when determining if code is dead, understanding why something exists, finding all callers before refactoring, or deciding whether something is safe to remove. Also useful for answering "who added this and why" or "is anything still using this".
GitLab Pajamas Design System expert for building UIs with Pajamas components and patterns. Use when: (1) implementing UI that should follow GitLab's Pajamas design system, (2) selecting or configuring Pajamas/GlComponent components (GlButton, GlAlert, GlModal, etc.), (3) translating Figma designs into Pajamas-compliant code, (4) questions about Pajamas component usage, variants, categories, or accessibility, (5) building GitLab-style interfaces, or (6) the user mentions "Pajamas", "GitLab UI", "Gl components", or "design system" in a GitLab context. Works hand-in-hand with the implement-design skill and Figma MCP tools.
Trace and document how data transforms through a multi-step pipeline or function chain, showing intermediate state at each step with concrete example values. Use when explaining a data pipeline or complicated codepaths, tracing how a value changes across function calls, answering questions like "how does X get to Y", or producing a step-by-step dataflow walkthrough for a code review or design doc.