xcode-dev-loop
>
acceptance-review
WHEN deciding whether a PR, branch, diff, or current code satisfies an authoritative issue, specification, or decision contract; NOT for reconstructing meetings, tracing decision lineage, general code review, or implementation; returns a criterion-by-criterion proof and acceptance verdict.
babysit
>
gauntlet-loop
WHEN a user asks for a Gauntlet Loop or relentless improvement of an ambitious artifact against a concrete, inspectable bar; NOT for routine changes with clear acceptance tests; coordinates separate builders and fresh critics until evidence supports stopping.
github-monitor
>
graph-engineering
WHEN orchestrating interdependent specs, stories, or work items across agents—deciding what runs serially, what may run in parallel, and how each unit is independently verified; NOT for single-task delegation, code review, or PR delivery mechanics; returns a contract-first execution graph with a per-node verifier.
pseudocode
WHEN rendering pseudocode of how code composes—module boundaries, types, signatures, arguments, and execution flow—for code that exists or a change about to be built; NOT for code review, verdicts, diagrams, or implementation; returns the shape and a cited call graph.
reducer
WHEN reducing whole-system complexity—branches, state, dependencies, layers, or moving parts—in an existing system or feature; NOT for functionality cuts or unproven rewrites; derives the minimum mechanism from first principles and proves behavior and guarantees are conserved.
ship-pr
WHEN shipping finished local changes through a pull request on GitHub (`gh`) or on Forgejo or Gitea (`tea`) and staying with it until the user merges; NOT for developing unfinished work or choosing substantial behavioral or conflict resolutions; commits with commit-messages, pushes, creates the pull request, repairs minor CI or conflicts, and polls through merge.
wtf
>
yagni
WHEN changing production code under this codebase's working agreements, or when a task risks overengineering—extra abstractions, speculative design, or test sprawl; NOT for removing complexity from existing code; enforces TDD, minimum sufficient execution, hard scope boundaries, and documentation practices.
decision-trace
WHEN tracing a decision or delivery-status claim from a meeting, transcript, decision record, handover, or status document through specs, issues, PRs, and commits; NOT for meeting summaries, acceptance verdicts, or implementation; preserves source uncertainty, grades each delivery handoff, and prepares an acceptance-review contract.
meeting-to-action-brief
WHEN turning a completed or live meeting, transcript, recording, or notes into a concise decision-and-action brief; NOT for verbatim minutes, drafting requirements, tracing decision lineage, or reviewing implementation; preserves proposals, uncertainty, and provenance.
story-pr-orchestrator
WHEN delivering an approved multi-story feature or several specs as dependency-gated pull requests; NOT for a single story, product discovery, or generic task delegation; coordinates one isolated task, worktree, branch, and PR per ready story.
mermaid-generator
>
vault-search
Semantic search and Dataview-style queries across the Obsidian vault. Use when searching for notes by meaning, finding related content, querying frontmatter metadata, or answering questions about vault contents. Trigger phrases include "search vault", "find notes about", "what do I have on", "related notes", "list tasks", "show positions".
convex-actions-general
This skill should be used when working with Convex actions, HTTP endpoints, validators, schemas, environment variables, scheduling, file storage, and TypeScript patterns. It provides comprehensive guidelines for function definitions, API design, database limits, and advanced Convex features.
Convex Agents RAG
Implements Retrieval-Augmented Generation (RAG) patterns to enhance agents with custom knowledge bases. Use this when agents need to search through documents, retrieve context from a knowledge base, or ground responses in specific data.
Convex Agents Rate Limiting
Controls message frequency and token usage to prevent abuse and manage API budgets. Use this to implement per-user limits, global caps, burst capacity, and token quota management.
Convex Agents Streaming
Streams agent responses in real-time to clients without blocking. Use this for responsive UIs, long-running generations, and asynchronous streaming to multiple clients.
Convex Agents Threads
Manages conversation threads to group messages into linear histories. Use this when organizing multi-turn conversations, managing per-user history, and handling thread metadata.
Convex Agents Tools
Enables agents to call external functions, APIs, and database operations through tool definitions. Use this when agents need to fetch data, perform actions, or integrate with external services while maintaining clean separation.
Convex Agents Usage Tracking
Tracks LLM token consumption and usage metrics for billing, monitoring, and optimization. Use this to log token usage, calculate costs, generate invoices, and understand which agents or users consume the most resources.
Convex Agents Workflows
Orchestrates multi-step agent operations with durable execution, automatic retries, and recovery from failures. Use this for complex workflows that need to survive server restarts or coordinate multiple agents.
convex-mutations
This skill should be used when implementing Convex mutation functions. It provides comprehensive guidelines for defining, registering, calling, and scheduling mutations, including database operations, transactions, and scheduled job patterns.
convex-queries
This skill should be used when implementing Convex query functions. It provides comprehensive guidelines for defining, registering, calling, and optimizing queries, including pagination, full text search, and indexing patterns.
Convex Agents Playground
Sets up a web UI for testing, debugging, and developing agents without code. Use this to manually test agents, browse conversation history, and verify behavior in real-time.
ai-elements-workflow
This skill provides guidance for building workflow visualizations using Vercel AI Elements and React Flow. It should be used when implementing interactive node-based interfaces, workflow diagrams, or process flow visualizations in Next.js applications. Covers Canvas, Node, Edge, Connection, Controls, Panel, and Toolbar components.
betterauth-tanstack-convex
Step-by-step guide for setting up Better Auth authentication with Convex and TanStack Start. This skill should be used when configuring authentication in a Convex + TanStack Start project, troubleshooting auth issues, or implementing sign up/sign in/sign out flows. Covers installation, environment variables, SSR authentication, route handlers, and the expectAuth pattern.
Convex Agents Context
Customizes what information the LLM receives for each generation. Use this to control message history, implement RAG context injection, search across threads, and provide custom context.
Convex Agents Debugging
Troubleshoots agent behavior, logs LLM interactions, and inspects database state. Use this when responses are unexpected, to understand context the LLM receives, or to diagnose data issues.
Convex Agents Files
Handles file uploads, image attachments, and media processing in agent conversations. Use this when agents analyze images, process documents, or generate files.
Convex Agents Fundamentals
Sets up and configures Convex agents for chat-based AI interactions. Use this when initializing agent instances, creating conversation threads, and generating basic text or structured responses from LLMs. Essential foundation for any Convex agent implementation.
Convex Agents Human Agents
Integrates human agents into automated workflows for human-in-the-loop interactions. Use this when humans need to respond alongside AI agents, handle escalations, or provide context that AI cannot determine.
Convex Agents Messages
Sends, saves, retrieves, and manages messages within agent conversations. Use this when handling user messages, displaying conversation history, and working with UIMessages for rich rendering.
convex-tanstack
Comprehensive guide for building full-stack applications with Convex and TanStack Start. This skill should be used when working on projects that use Convex as the backend database with TanStack Start (React meta-framework). Covers schema design, queries, mutations, actions, authentication with Better Auth, routing, data fetching patterns, SSR, file storage, scheduling, AI agents, and frontend patterns. Use this when implementing features, debugging issues, or needing guidance on Convex + TanStack Start best practices.
vercel-ai-elements
This skill provides comprehensive documentation for all 23 Vercel AI Elements components organized by category (Message, Conversation, Input/Interaction, Content Display, AI Processing, Advanced Features). Use when users ask about building AI chatbots, need component documentation, want API references for Vercel AI Elements, or need integration examples with the AI SDK.
build-phases
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codex-review-backlog
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design-review
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epic-conductor
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fleet-report
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fleet-setup
>-
git-hygiene
>-
impact-check
>-
issue-graph
>-
issue-review
>-
issue-sweep-batch
>-
issue-sweep
>-
land
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