Use when encountering questions about WHY code is built a certain way, when about to make architectural changes (new patterns, restructuring, choosing between approaches), or when the user asks about design rationale in a Repowise-indexed codebase (.repowise/ directory exists). Also activates when commit messages or…
Use when reviewing a set of changes before they merge — a PR, a branch diff, or the working-tree changes you just made — in a Repowise-indexed codebase (.repowise/ directory exists). Activates for "review this PR", "is this safe to merge", "what's the blast radius of these changes", "did I miss anything", or "what…
Use when exploring, understanding, or answering questions about a codebase that has Repowise indexed (a .repowise/ directory in the project root). Activates for "how does X work", "explain the architecture", "where is Y implemented", "what does this module do", or any task that needs an understanding of structure…
Use browser automation to review docs pages, preview URLs, rendered output, or web-facing fallow surfaces. Use when the user wants a screenshot-based review, browser smoke test, docs site check, or preview deployment inspection.
Prepare local changes for review with an intentional commit, push, and ready PR for fallow. Use when the user wants to publish work, open a PR, or turn local changes into a reviewable branch.
Investigate and harden Skylos security behavior. Use when the user asks to validate a security finding, reproduce a scanner bypass, assess false negatives, review LLM evidence filters, analyze CI/cloud policy trust boundaries, classify severity, or add regression tests for security-sensitive analyzer behavior.
Run, interpret, or modify Skylos safely. Use when the user asks to scan code with Skylos, explain SKY- findings, triage dead-code false positives, audit security/secrets/SCA/LLM behavior, update Skylos rules/docs/CI, benchmark analyzer behavior, or change this repository safely.
Opinionated defaults and full lifecycle playbook for secrets and environment variables. Decides where a secret or env-specific value lives (constant, .env, CI secret, env var), scaffolds .env.example and .gitignore, and manages the lifecycle end to end — add, update, rotate, remove, migrate between buckets, audit…
Proves a behavior-preserving code change (refactor, rename, split, merge, extract, inline, or delete of confirmed-dead code) is actually complete. Plans the change as a dependency tree, executes it from the leaves up, and after each step proves 1:1 semantic equivalence through four independent checks — exported…
Review maintainability like a principal engineer. Use when the user asks what a senior/staff/principal maintainer would notice, whether code looks vibe-coded, what is gross, what should be fundamentally different, or which architecture smells matter beyond ordinary deduplication.
Optimize performance scientifically with current scip-query evidence. Use for benchmarking, profiling, cold or warm indexing, command latency, memory and computational cost, or comparing current-pipeline tuning with alternative designs.
Audit whether implementations are real with scip-query. Use for suspected faked or half-implemented features, decorative checkers or verifiers that never fail, dead code paths hidden behind graceful fallbacks, metrics that may be lying, or a "does any of this actually work" interrogation of a system.
Use the Weavatrix MCP when a repository task benefits from indexed evidence: codebase orientation, symbol/source search, dependency or call graphs, change impact, API/event tracing, architecture checks, Git/coverage evidence, duplicates, dead-code review, or semantic context. Skip it for trivial single-file edits or…
Use the Weavatrix MCP when a repository task benefits from indexed evidence: codebase orientation, symbol/source search, dependency or call graphs, change impact, API/event tracing, architecture checks, Git/coverage evidence, duplicates, dead-code review, or semantic context. Skip it for trivial single-file edits or…
Finds real dead code (unused imports, functions, classes) and unused dependencies in a Python repository, and proposes a safe, test-gated branch+PR to remove the safely-removable ones. Use this whenever the user asks to find or clean up dead code, unused imports, unused dependencies, or "bloat" in a Python project…
Scaffold a new project from product discovery through production-oriented quality gates. Runs a multi-round Grill Me interview covering users, outcomes, scope, brand assets and colors, accessibility, platforms, signing, distribution, service model, data, security, operations, and release pipeline before stack…
Scan an existing codebase and bring it into compliance with strict quality standards — style, formatting, linting, type checking, dead-code removal, magic-number and literal extraction, sanitizer wiring, secret scanning, and CI-ready gates. Extends existing configuration rather than replacing it, and lands changes in…