raysense
raysense contains 6 collected skills from RayforceDB, with repository-level occupation coverage and site-owned skill detail pages.
Skills in this repository
Use after a rescan to surface structural regressions across a time window. Diffs the latest scan against the saved baseline AND the trend history, ranking dimensions that worsened, files newly hot, and rules newly tripped. Configurable window (7d, 30d, 90d). Use periodically (daily, weekly, or pre-PR).
Use when the user explicitly asks for a structural audit, architecture review, dead-code report, test-gap analysis, or evolution hotspot scan. Heavier and noisier than the other raysense skills — only run on demand, not as part of the routine edit loop.
Use at the start of any coding session in a repository to scan the structure, save a baseline, and materialize splayed-table memory for fast follow-up queries. Establishes the "before" reference point that the verify skill diffs against later.
Use before refactoring, deleting, moving, or substantially modifying a file to compute its blast radius, coupling profile, and cycle exposure. Lets the agent edit with awareness of downstream effects rather than discovering them after the fact.
Use when the agent has a structural question about the saved baseline that the typed MCP tools (health, hotspots, rules, blast radius, coupling, cycles, evolution) do not directly answer. Runs Rayfall expressions against splayed baseline tables via raysense_baseline_query. Three modes are available - select queries for filter/project/aggregate (most common), .graph.* algorithms (PageRank, Louvain, topsort, shortest-path, betweenness, closeness, MST, k-shortest, BFS expand) for centrality and reachability over the call graph, and Datalog rules with transitive closure for declarative reachability ("reaches", "depends-on", "tainted-by"). Reach for this when the question shape is "files where X and Y," "most-central callers," "what does X transitively reach," or any custom slice across the 18 baseline tables.
Use after completing a logical chunk of edits to rescan the project and detect new rule violations or health regressions against the session baseline. Catches structural regressions before they reach review.