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概要と使いどころ
Execute one complex task as ordered, dependent steps run sequentially, passing context from each step to the next, with per-step LLM-as-a-judge verification. Use when later steps depend on the results of earlier 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。
Explain any topic, code, concept, or error tailored to a specific audience's level of understanding. Use this skill whenever the user says 'explain like I am', 'ELI5', 'explain this to my', 'break this down for', 'dumb it down', 'simplify this for', or asks you to explain something to a specific person or audience type (e.g., 'explain this to a manager', 'how would I explain this to my mom', 'make this understandable for a 5th grader'). Also trigger when the user mentions wanting to understand something at a particular level, or asks for an explanation targeting a non-technical audience. Even partial matches like 'explain to my wife' or 'tell my boss' should trigger this skill.
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 and build the visual layer of a long-form talking-head video as one persistent world the camera moves through, instead of a sequence of separate graphics. Use when asked to edit a video, add motion graphics, design the visuals for a script, plan an edit, or fix an edit judged confusing, text-heavy, hard to follow, or "clearly made by an AI". Covers the persistent world, camera grammar, the spotlight rule, spatial open loops, ornament and token discipline, transcript timing, and the verification gates.
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。
Generate a co-author / collaborator handoff brief for a multi-author, multi-machine project — summarizing what changed since the last brief (git delta), the current state of each artifact (manuscript, analysis, slides), open questions, how to reproduce locally, and any restricted-data access steps. Use when user says "coauthor brief", "handoff brief", "bring my coauthor up to speed", "what changed since last week", "onboard a collaborator", "write a handoff for [name]", or before sending a co-author the repo. NOT a commit or a checkpoint — it is the cross-machine, cross-person summary `meta-governance.md` only partially covers.
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。
Draft a funder-compliant Data Management Plan (NSF DMP, NIH DMS Policy 2023, ERC, Horizon Europe) by composing the confidential-data and environment-capture primitives. Sections cover data description, formats/metadata, storage/backup, access/sharing, preservation/archiving, and roles. Use when user says "data management plan", "DMP", "DMSP", "NIH data sharing plan", "write the data plan for my grant", or when a grant proposal needs a data-management section. NOT a submission tool — produces a draft the user pastes into the funder portal (DMPTool, NIH ASSIST, Horizon Europe portal).
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。
Compare two implementations of the same thing — a port (R↔Python↔Stata), a reimplementation, a replication package, a refactor, or a new version against the old — so that agreement means something. Freeze inputs first, inventory every expected output, test the comparator itself, compare every channel (not just the headline number), and give each divergence a stable ID and a smallest witness. Use for cross-language parity, replication, upgrade/regression gates, or whenever "the numbers match" is about to license a claim.
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。
Generate a structured response-to-referees document from a referee report and the revised manuscript. Maps each referee comment to the specific revision, classifies coverage (addressed / partially / deferred / disagreement), and drafts polite but firm responses. Use during the R&R (revise-and-resubmit) stage of paper revision.
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。
Pre-screen analysis outputs (tables, figures, logs) built on restricted or confidential data for statistical-disclosure-limitation problems before any release. Scans for small cell counts, complementary-suppression gaps, dominance (p-percent / (n,k)), re-identifiable exact counts, PII leakage, and unrounded sensitive statistics; classifies each finding CRITICAL / WARNING / OK and gates on any CRITICAL. Use before depositing or sharing restricted-data results, or when the user says "disclosure check", "SDL scan", "is this output safe to release", "check for small cells", "disclosure avoidance", "pre-screen for the RDC", or "can I export this from the enclave".
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。
Assemble a submission-ready replication package to the AEA Data and Code Availability Standard (DCAS) / openICPSR / Social Science Reproduction Platform expectations — standard replication README, dataset manifest, computational-requirements capture, a Table/Figure → script:line map, and a confidential-data deposit plan. Use when user says "build the replication package", "prepare the openICPSR deposit", "make the AEA data and code package", "DCAS compliance", "assemble the deposit for the journal", or after a paper is accepted and the journal's data editor needs the package. NOT a numeric verifier — it calls /audit-reproducibility to confirm claims reproduce before packaging.
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。
AI DevKit · Requirements phase guidance for starting features and reviewing requirements. Use when the user wants to capture a new requirement, clarify product scope, initialize feature docs, review requirements, or run dev-lifecycle phases 1-2.
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 a selective defect needs IS/IS-NOT difference analysis or a consequential option choice needs must/want weighting and adverse-consequence comparison.
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 the reflex is to add a feature, layer, or process. Prefer removing harmful or nonessential elements first, with an irreversibility guard before deletion.
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。
Forecast Azure spend and price planned resources or workloads. WHEN: "forecast Azure spending", "project next month cost", "compare forecast to my planning target", "how much will Azure cost", "estimate VM cost", "compare storage tiers", "compare Azure regions", "retail price", "EA rate card", "negotiated pricesheet". DO NOT USE FOR: configured budget health or alerts, bill analysis, cost spikes, rightsizing, or commitments.
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。
Azure VM/VMSS router. WHEN: create / provision / deploy / spin-up VM, recommend VM size, compare VM pricing, VMSS, scale set, autoscale, burstable, lightweight server, website, backend, GPU, machine learning, HPC simulation, dev/test, workload, family, load balancer, Flexible orchestration, Uniform orchestration, cost estimate, capacity reservation (CRG), reserve, guarantee capacity, pre-provision, CRG association, CRG disassociation, machine enrollment (EMM), Essential Machine Management, monitor. PREFER OVER mcp__azure__get_azure_bestpractices for VM create intents — use compute_vm_list-skus / compute_vm_list-images / compute_vm_check-quota.
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。
Write Godot 4.7 shaders in the Godot Shading Language: canvas_item shaders for 2D and spatial shaders for 3D, with vertex/fragment functions, uniforms (source_color, hint_range), TIME/UV animation, and screen-reading via hint_screen_texture. Use when authoring .gdshader files, writing fragment/vertex code, making 2D/3D visual effects, or porting 3.x shaders (SCREEN_TEXTURE, hint_color) to 4.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。
Build a production behavior-tree runtime (Blackboard, action/condition leaves, sequence/selector/parallel composites, decorators) and a Utility AI system (response curves — linear, exponential, sigmoid, quadratic — considerations, and action evaluators), plus hybrid BT-drives-Utility agents. Use when implementing a reusable behavior-tree or utility-based decision system, or tuning enemy/NPC decisions beyond a simple FSM, or when the user mentions behavior tree, blackboard, decorator, selector, sequence, tick status, utility AI, response/scoring curve, or consideration. For choosing between FSM/BT/steering or for pathfinding, use game-ai; for Unreal's BehaviorTree/Blackboard assets, use unreal-behavior-trees.
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 C#/.NET in Godot 4.7: partial classes extending nodes, the PascalCase lifecycle (_Ready/_Process/_PhysicsProcess), [Export] fields, [Signal] delegates as C# events, type-safe node lookup, and calling between C# and GDScript. Use when writing Godot game code in C# (.cs files, .csproj), needing the Godot .NET build, converting GDScript patterns to C#, or wiring Godot signals as C# events.
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。
Structure a Godot 4.7 project with the scene tree and node composition: build reusable scenes, instance PackedScenes at runtime, navigate the tree safely, and register autoload singletons. Use when designing .tscn scenes, deciding how to split nodes, spawning instances with instantiate(), wiring autoloads, or fixing "node not found"/freed-node errors in a Godot project.
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。
Set up a Godot 4.7 3D scene: Node3D transforms, Camera3D, lighting (DirectionalLight3D/OmniLight3D), WorldEnvironment for sky/ambient/tonemap/post, MeshInstance3D materials, and GridMap for tile-based 3D levels. Use when building a 3D scene in a Godot project, placing cameras/lights, configuring environment and post-processing, or working with Node3D/.tscn 3D content and GridMap.
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。
Triage inbound journalist source queries and draft a response only when the user's expertise is a real fit. Runs each query through proven source-request lenses (4-gate fit triage, credential-standing test, deadline read, BLUF/inverted-pyramid drafting), kills weak fits, asks for missing proof, and never auto-sends.
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。
Consolidate freshness-gated newsjack signals and route them by client standing before angle generation. Collapses any remaining same-story duplicates, decides strong/partial/none standing with a journalist-shape sanity check, and sorts each story into pitch_ready, big_story (always-surfaced suggestion), or watch. Never writes angles or pitches, and never drops a fresh big story.
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。
Maintenance orchestrator for the brooks-lint plugin itself. Runs a sequential subagent pipeline — author → eval → QA → trigger-audit → release — to add or edit a skill, refresh the eval suite, keep the four manifests + all README translations + CHANGELOG + AGENTS/GEMINI in sync, audit trigger boundaries, and cut releases. Drives the five agents in .codex/agents/ (skill-author, eval-curator, consistency-qa, trigger-boundary-auditor, release-manager). Triggers when the maintainer asks to work ON brooks-lint itself: "add a new skill", "edit the brooks-debt guide", "update the eval suite", "fix the trigger descriptions", "make this change and validate it", "release brooks-lint", "bump and publish", and follow-ups: "re-run", "re-validate", "update that skill", "redo the audit", "do the X part again". Do NOT trigger for: USING the brooks-lint analysis skills on some target codebase (that's brooks-review / brooks-audit / brooks-debt / brooks-test / brooks-health / brooks-sweep); generic questions about brooks-lint that don't ask to change it; or maintenance of a different plugin.
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。
Maintenance orchestrator for the brooks-lint plugin itself. Runs a sequential subagent pipeline — author → eval → QA → trigger-audit → release — to add or edit a skill, refresh the eval suite, keep the four manifests + all README translations + CHANGELOG + AGENTS/GEMINI in sync, audit trigger boundaries, and cut releases. Drives the five agents in .claude/agents/ (skill-author, eval-curator, consistency-qa, trigger-boundary-auditor, release-manager). Triggers when the maintainer asks to work ON brooks-lint itself: "add a new skill", "edit the brooks-debt guide", "update the eval suite", "fix the trigger descriptions", "make this change and validate it", "release brooks-lint", "bump and publish", and follow-ups: "re-run", "re-validate", "update that skill", "redo the audit", "do the X part again". Do NOT trigger for: USING the brooks-lint analysis skills on some target codebase (that's brooks-review / brooks-audit / brooks-debt / brooks-test / brooks-health / brooks-sweep); generic questions about brooks-lint that don't ask to change it; or maintenance of a different plugin.
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。
Scaffold a new brooks-lint analysis skill so it passes `npm run validate` and `npm run evals` on the first try — generates skills/{name}/SKILL.md (with the mandatory "Do NOT trigger for:" clause and a Process section citing guide step ranges) plus skills/{name}/{name}-guide.md (sequentially numbered steps), then appends paired eval scenarios. Triggers when the maintainer asks to "add a new skill", "scaffold a skill", or "create a brooks-lint mode". Do NOT trigger for: editing an existing skill's content, adding a single eval to an existing skill, or authoring skills for some other plugin.
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。