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Create or extend reusable Terraform modules with proper structure, interfaces, and documentation. Use when building new infrastructure modules or extending existing ones.

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。

Documentation for just and justfile. This skill should be used before editing justfile or running just commands. TRIGGER when run just command, or edit justfile; or when about to write any `just ...` shell invocation in Bash, pueue, or scripts.

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。

Cache and refresh remote git repositories under ~/.cache/checkouts/<host>/<org>/<repo> so future references can reuse a local copy. Use this skill when the user points you to a remote git repository as reference or you encountered a remote git repo through other means.

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。

Unified Kaggle skill. Use when the user explicitly mentions Kaggle, kaggle.com, a Kaggle URL, Kaggle competitions, Kaggle datasets/models/notebooks, Kaggle forums/discussions/writeups, Kaggle benchmarks, hackathons hosted on Kaggle, Kaggle badges, or Kaggle account setup. Do not use for generic ML, GPU/TPU, notebook, dataset, benchmark, or data-science tasks unless the user clearly ties them to Kaggle.

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。

Inspect repository session replay and verify configured MetaHarness field memory boundaries before reusing outcomes.

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Shared review framework that every domain reviewer (pci, oracle, gov, edtech, healthcare, mlops, etc.) MUST follow. Defines the output artifact (TM-{slug}.md), mandatory sections, severity scale, verdict format, the workflow scaffold (when-invoked, Step-0 read-inputs, HANDOFF), and the "domain heuristic vs generic check" boundary. Eliminates duplication across the ~30 reviewer prompts.

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Reusable reporting contract for any agent that hands work back to the pipeline. Forces ONE of two terminal statuses (DONE or BLOCKED) with a specific evidence shape. Stops vague "probably finished" and "kind of stuck" verdicts.

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Reusable writing-style contract for agent outputs (reports, ARCH docs, verdicts, threat models). Forces direct prose with concrete evidence, no marketing voice, no hedge words. The single most-referenced skill across the pipeline — used by 28 agents.

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Reusable 3-round self-challenge + arbiter pattern for filtering false positives from findings/verdicts. Use when the cost of a false-positive gate block exceeds the cost of ~4 extra LLM turns.

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Turn multiview fit reports into a sequential or parallel repair queue for aligning Blender products to source-of-truth templates. Use after validation shows disalignment, when the agent must iteratively fix wireframe, texture, lighting, or projection mismatches, and when skill gaps should trigger self-refinement before another rebuild.

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Run a self-refinement loop when a Blender result is subpar, user expectations are not met, validation fails, or repeated issues reveal missing skill depth. The loop diagnoses the gap, decides whether to repair the artifact or acquire/refine a generic skill, sanitizes lessons for reusable publication, updates docs/versioning, validates, and prepares stage/commit/push when explicitly requested.

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Animate objects, cameras, lights, and properties in Blender — keyframes, F-curves, easing (Bezier, Linear, Sine, Bounce, Elastic), shape keys (morph targets / blendshapes / visemes), drivers (Python expressions on properties), NLA actions for reuse and layering. Use whenever the user asks to "animate this", "make it move / rotate / scale over time", "add keyframes", "loop / oscillate", "shape key / morph / blendshape", "visemes for lip sync", or any time-based property change. Make sure to use this skill even if the user does not say "animate" — also covers "spin it slowly", "make it wave", "fade in / out", "pulse", "facial expression".

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Builds backend services and APIs with durable defaults. Use when implementing REST, GraphQL, tRPC, or gRPC services with auth, queues, data, or observability.

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Designs workflow automation with n8n, Zapier/Make, Temporal, Trigger.dev, Inngest. Use when choosing platforms, durable execution, or approval gates; not job queues or agents.

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Designs team Git workflows for branching, PRs, and releases. Use when choosing branching models, stacked PRs, merge queues, worktree isolation for agents, or collaboration rules.

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Creates reusable vector-brain implementations: repo, docs, compliance. Use when building pgvector SQL, manifests, ingest scripts. Not for context design (dev-context-engineering).

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Create, redesign, repair, validate, preview, and package lightweight standalone HTML deliverables. Use for marketing experiences, product prototypes, infographics, motion narratives, documents, browser tools, dashboards, guided workflows, knowledge interfaces, mini-games, presentations, reusable style and brand systems, and local-model text, vision, image, or code tools that must run without a build chain or hosted service.

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Maps an unfamiliar or large codebase before implementation by locating entry points, ownership, execution paths, conventions, tests, dependencies, change hotspots, and unresolved questions. Use when onboarding to a repository, scoping a cross-cutting change, preparing a handoff or reusable CodeTour, explaining a subsystem, or when the agent is guessing where behavior lives. Not for diagnosing one reproduced failure or designing a new architecture before the current system is understood.

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。

Operate HitKeep safely in isolated Git worktrees. Use when inspecting workspace state, resolving ports or URLs, starting or stopping development services, coordinating concurrent agents or QA runs, reusing active runs, reading bounded logs, or preparing a secret-free handoff.

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Improve existing code without changing behavior: scan smells, simplify, dedupe, reuse utilities, and verify after edits. Use for refactor, cleanup, simplify, reduce duplication, extract method, dead code, or code smells. No PR.

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。

SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) comprehensive development methodology with multi-agent orchestration

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Automated coordination, formatting, and learning from Claude Code operations using intelligent hooks with MCP integration. Includes pre/post task hooks, session management, Git integration, memory coordination, and neural pattern training for enhanced development workflows.

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。

Cloud-based AI swarm deployment and event-driven workflow automation with Flow Nexus platform

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Triage Monte Carlo alerts interactively or build an automated workflow. Fetch, score, and troubleshoot alerts using MCP tools now, or design a reusable workflow that runs on a schedule.

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。