You are an API mocking expert specializing in realistic mock services for development, testing, and demos. Design mocks that simulate real API behavior and enable parallel development.
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概要と使いどころ
You are an API mocking expert specializing in realistic mock services for development, testing, and demos. Design mocks that simulate real API behavior and enable parallel development.
日本語の概要は準備中です。原文の説明を表示しています。
Configure and orchestrate parallel agents using the standalone Antigravity 2.0 Agent Manager and Antigravity IDE.
日本語の概要は準備中です。原文の説明を表示しています。
Design production-grade multi-agent workflows with clear pattern choice (sequential, parallel, hierarchical), handoff contracts, failure handling, and cost/context controls. Use when architecting a multi-step agent pipeline, choosing between single-agent vs multi-agent approaches, or refactoring an LLM workflow that suffers from context bloat or unreliable handoffs.
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Use for Six Thinking Hats or de Bono's parallel thinking, or when a decision or idea needs facts, gut feel, risks, benefits and new options kept apart: "look at this from all sides", "full perspective check". Skip for plain factual questions or single-angle hot takes.
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Delegate a prompt to Claude via `claude -p`. Use when the user wants to offload a task to Claude from another agent (Codex, Cursor, another Claude session), get a second opinion, or run a parallel implementation. Default model is opus.
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Coordinate complex engineering work across bounded subagents while protecting the main context, preventing edit conflicts, and measuring whether delegation was worthwhile. Use when the user asks to delegate, parallelize, orchestrate, use subagents, fan out a review, or handle a large task with independent workstreams; do not use for small, tightly coupled, or inherently sequential tasks.
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Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes — Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/PRD asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use when the user wants to review a branch, a PR, work-in-progress changes, or asks to "review since X".
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Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies
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Generate multiple radically different interface designs for a module using parallel sub-agents. Use when user wants to design an API, explore interface options, compare module shapes, or mentions "design it twice".
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Structures git workflow practices. Use when making any code change. Use when committing, branching, resolving conflicts, or when you need to organize work across multiple parallel streams.
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Breaks work into ordered tasks. Use when you have a spec or clear requirements and need to break work into implementable tasks. Use when a task feels too large to start, when you need to estimate scope, or when parallel work is possible.
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Implement a ready rolling-wave slice without locking it down with broad tests yet. Use when the user explicitly wants to code the current docs/rolling-wave/{project}/slices/NNN-slug.md slice, mark it in progress while working, implement small or cohesive work in the main context by default, use one to three gpt-5.6-terra workers only for genuine parallel chunks or large discovery/mechanical work where delegation pays for its handoff cost, pause or hand off chunks marked human-fit when appropriate, record implementation notes and final-test backlog, preserve the original slice contract, and mark completed implementation ready for review.
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Prepare and risk-check the next rolling-wave slice for implementation. Use when the user wants to continue a rolling-wave project, draft one bounded slice in the main context by default, use a fresh planning author only when context or discovery cost warrants it, use a fresh preparation reviewer when semantic risk or uncertainty warrants independent pressure-testing, decompose parallel implementation chunks where appropriate, identify agent, human, either, or hybrid execution fit, write or update docs/rolling-wave/{project}/slices/NNN-slug.md, and mark that slice ready even when other slices are active.
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Investigate two separate areas of the codebase simultaneously and combine findings into a comparison report. Use when you need research on two independent topics at once, want to compare two subsystems, or need to understand how two components relate to each other.
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Subagent that scans CopilotKit + AG-UI releases shipped in (and just after) the report window, diffs the git tags to extract what each release actually fixed, and returns a fix-map the weekly-report writer cross-checks against open issues. Catches issues that are quietly already-fixed in a shipped release, and is the authoritative source for the "current release vX.Y.Z" version claims. Invoked by weekly-report (spawned in parallel with the Discord/GitHub pulls); runs as a general-purpose subagent so the orchestrator's context stays small.
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Expert-level computer architecture covering CPU design, instruction sets, pipelining, cache hierarchy, memory systems, parallel architectures, and GPU computing.
日本語の概要は準備中です。原文の説明を表示しています。
Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies
日本語の概要は準備中です。原文の説明を表示しています。
Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes — Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/spec asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use when the user wants to review a branch, a PR, work-in-progress changes, or asks to "review since X".
日本語の概要は準備中です。原文の説明を表示しています。
Review code changes adversarially using parallel review layers (Blind Hunter, Edge Case Hunter, Acceptance Auditor) with structured triage into actionable categories. Use when the user says "run code review" or "review this code"
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Use when choosing .NET concurrency patterns for async I/O, queues, pipelines, or thread safety. Keywords: async/await, channels, dataflow, Rx, lock contention, producer consumer, parallel processing.
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Decompose an epic into atomic parallelizable tasks, route each to the right skill, and keep the four delivery records straight — issues, STATUS, ROADMAP, CHANGELOG. Use as a meta-router when several skills could apply, and as the baseline for how delivery state is recorded. Trigger at the start of any multi-track epic, when the skill count exceeds ~12, or when the records have drifted from reality.
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Bootstrap or harden a project's operating model for mixed human and AI delivery teams. Use when starting a repository, adopting an agent harness, defining authority and risk tiers, coordinating parallel agents safely, binding evidence and review to an exact candidate, or correcting fragmented rules that prevent coherent, consistent, complete delivery.
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When starting parallel work in isolation from the current branch — spawn a git worktree with ignore-safety checks and a clean test baseline — even when the user says 'try this on the side'.
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Use when orchestrating implementer/judge subagents — form gate + nine modes (do-and-judge ±two-stage, steps/parallel/worktrees, competitively, debate, live-app-judge, adversarial-council).
日本語の概要は準備中です。原文の説明を表示しています。