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Found 6,411 Skills
This skill should be used when the user wants to review code, audit a diff, get a second opinion on changes, or run an adversarial review of files in the current working tree. Common triggers include "review this code", "audit this diff", "find issues in", "second opinion on this", "harsh review of", "adversarial review", and "security review of". Picks one or more reviewer personas (adversarial, security, architecture, performance). Reviews local files, `git diff`, or `git diff --staged` only — does not fetch external content. Runs in one of four modes: single-agent (one persona in the current agent), cross-model handoff (independent second opinion via another local AI CLI, with secret-shield preflight + prompt-shield wrap), multi-bg-agent (one persona per parallel background subagent), or agent-team (Claude Code Teams or equivalent on supporting agents). Skip when the user wants formatting fixes (use a linter) or refactoring patterns (use ts-best-practices or ts-best-practices-functional).
Review and improve HelixDB query performance and query shape. Use when the task is to optimize a slow Helix query, improve anchor choice, tighten index usage, reduce traversal breadth, slim projections, fix BM25 or vector search scope, or decide between stored and dynamic routes.
Legacy-project style inheritance skill. Use when the user types /inherit-legacy-style, or when onboarding an AI coding agent onto a hand-written legacy project and you need to prevent "style drift" (the model imposing its pretrained mainstream idioms onto the project). Language- and framework-agnostic — it aligns meta-architecture only, not syntax. Once run, it becomes a behavioral constraint on all subsequent coding tasks. Do NOT use for pure research or one-off questions unrelated to code-style alignment.
Continuously question users about their plan or design. Suitable for scenarios where users want to stress-test their plan before building, or when using any "grill" trigger phrases.
Consult an advisory council of three AI personas — Cato (skeptic), Ada (optimist), Marcus (pragmatist) — backed by different frontier LLM agents (Gemini, Claude, Codex). Each persona runs as a separate agent process with full repo context and returns independent feedback. Use when the user says "/council", asks for a second opinion, wants feedback on code changes, needs a premortem, wants to pressure-test a decision, or asks "what do you think about this approach?" Claude may also proactively suggest consulting the council before major architectural decisions, risky deploys, or ambiguous trade-offs (but should ask for user approval first).
Execute a single Ralph iteration - implement one user story autonomously. Use for manual mode where you want maximum control and fresh context per story. Triggers on: ralph iterate, execute one story, run single iteration, manual ralph.
Summarize code changes by author type and scope. Inputs are author and scope with product plus PR as defaults.
Creates complete VoltDB client applications with optimized table partitioning, DDL schemas, stored procedures, and integration tests. Use when user wants to create a VoltDB client, connect to VoltDB, create VoltDB schemas, write VoltDB stored procedures, or write VoltDB integration tests.
Realm integration. Manage data, records, and automate workflows. Use when the user wants to interact with Realm data.
Use these skills when you need to discover and manage PostgreSQL extensions or fine-tune engine-level settings such as memory allocation and server configuration parameters.
Use these skills when you need to troubleshoot performance bottlenecks, analyze query execution plans, identify resource-heavy processes, and monitor system-level PromQL metrics.
Qdrant integration. Manage Collections, Snapshots. Use when the user wants to interact with Qdrant data.