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概要と使いどころ
Review open mastra-ai/mastra GitHub issues, identify direct @mastra/core bugs, and apply the @mastra/core label. Use when auditing issues for core ownership, labeling direct core bugs, or periodically reconciling the @mastra/core issue label.
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。
Re-review a pull request after a push — reconcile the previous review against the new commits, look for new defects the push introduced, then a fresh pass over the whole PR, and finish with a verdict on the 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。
Smoke test the Agent Builder feature branch end-to-end against a hermetic project scaffolded by the skill (linked to the current worktree). Covers workspace reconciliation, stored agents/skills CRUD, ownership, visibility, stars, registry/library Copy flow, picker allowlists, model policy, RBAC role gating, role impersonation UI, builder defaults, infrastructure diagnostics, channels, and Studio + Agent Builder UI. Trigger when validating the agent-builder feature branch, PRs that touch packages/server, packages/playground, packages/playground-ui agent-builder routes, or builder EE code paths.
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。
Comprehensive incident response framework from detection through resolution and post-incident review. Battle-tested SRE/DevOps practices: severity classification, timeline reconstruction, structured post-incident analysis. Use when declaring an incident, coordinating multi-team response during an outage, leading a post-mortem, or setting up on-call practices for a new service.
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 or update a professional-grade design system in Figma from a codebase. Use when the user wants to create variables/tokens, build component libraries, set up theming (light/dark modes), document foundations, or reconcile gaps between code and Figma. This skill teaches WHAT to build and in WHAT ORDER — it complements the `figma-use` skill which teaches HOW to call the Plugin API. Both skills should be loaded together.
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。
Judge a supplied subject against the project's evidence and constraints. Use when assessing an external-adoption question, a holistic take on a document, or a supplied approach set. Use for an oracle panel to consult other models and reconcile their opinions. Use ce-explain for understanding and ce-doc-review for findings review.
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。
Reconstruct a customer relationship from recorded interactions before answering or drafting a response.
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。
Reconstruct a daily or weekly worklog from observed activity and outcomes.
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。
Find explicit promises and deadlines in selected work history and reconcile their latest status.
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。
Reconstruct a bounded incident timeline and separate observed events from suspected causes.
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。
Knowledge and governance closeout: reconcile project docs, rule files (CLAUDE.md/AGENTS.md), authorized agent memory, and workspace residue with what the code and runtime actually do, so the next session or the next person starts from one current answer. Trigger when the user names "neat-freak", "洁癖", or "/neat" — and also on clear knowledge-closeout intent without the name: syncing or tidying project docs/rules/memory after development ("把文档和记忆整理一下", "收尾时把文档同步掉", "docs 和代码对不上了"), stale or conflicting CLAUDE.md/memory, a clean handoff to a teammate or a fresh session, or auditing whether workspace rules are actually followed. Do not trigger for pure coding/refactoring/debugging tasks, tidying data or prose (JSON, 周报, changelog announcements), or a bare "整理" with no project-knowledge context.
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。
Author, validate, test, and deploy YARA-L 2.0 detection rules and evaluate end-to-end detection coverage gaps in Google SecOps. Use when writing new detection rules, tuning existing rules, validating syntax, testing logic against historical telemetry, or evaluating detection coverage against threat intelligence blogs, CVE disclosures, and Threat Detection Opportunities (TDOs) using synthetic UDM events and long-running coverage analysis. Don't use for alert triage (use secops-triage), deep forensic event reconstruction on infected hosts (use secops-investigate), or case management operations (use secops-cases).
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。
Creates Cloud Storage on Google Cloud (also known colloquially as GCS) buckets. Analyzes the workload (sensitive data, media hosting, ingestion, web hosting, archiving, backup, logging, analytics, AI/ML, or general-purpose), validates project-level security settings, and designs a secure-by-default, cost-effective configuration (location, storage class, uniform bucket-level access, public access prevention, soft delete, lifecycle) before creating it. Use whenever a user wants to create, make, set up, provision, or spin up a bucket, or needs object storage for an app, service, pipeline, or dataset — even a "simple" or "default" bucket, or when bucket creation is one step in a larger workflow. Outputs or executes the creation via gcloud, the JSON/REST API, Terraform, or SDK client libraries (C++, Java, Python, Go). Don't use for anything other than creating new buckets — for uploads, downloads, access changes, or reconfiguring existing buckets, use google-cloud-storage-basics.
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。
Guides agents through a 6-step discovery process to design and deploy Google Cloud global external Application Load Balancers with Cloud CDN, Cloud Armor, and Service Extensions, mapping workload requirements to best-practice configurations. Use when: - Designing, configuring, or deploying a Google Cloud global external Application Load Balancer, Cloud CDN, Cloud Armor WAF, or Service Extensions. - Discovering existing Google Cloud resources (Cloud Storage, MIGs, GKE, Cloud Run) to use as backends. - Generating production-grade Terraform HCL or gcloud CLI scripts for global external Application Load Balancers. - Actuating deployments via Infrastructure Manager or bash scripts, including IAM pre-checks. - Detecting, analyzing, or reconciling configuration drift on deployed global external Application Load Balancers. Don't use for: - Non-Google Cloud load balancing or security configurations. - Purely regional or internal load balancing setups (unless part of a hybrid/failover global design).
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。
Weekly SaaS spend audit loop for {{subscription_sheet}}. Pulls recurring card and bank charges from Plaid, reconciles them against the subscription register, flags duplicate/overlapping tools, unused seats, price hikes, upcoming renewals, and shadow IT, and posts a digest to {{alert_channel}} — recommending cancellations and downgrades only, never acting on them.
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。
Turns feedback from Plain, public reviews, and a Slack channel into deduplicated, quantified themes, and reconciles each theme against one Linear issue in {{linear_team}} — never prioritizing, assigning, or closing.
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。
Monthly close runbook: how to walk {{close_sheet}}'s checklist, reconcile Stripe revenue against the recorded ledger, judge a missing supporting document, and spot an anomaly against prior months. Load this before touching a single checklist line so every item is judged to the same standard and only genuine open items reach a human.
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。
Ethical people-finding and identity verification via parallel research agents across people-search sites, social media, public records, and reverse phone/email/image/username lookups, with confidence-scored results requiring 3+ matching identifiers. USE WHEN find person, locate person, reconnect, lost contact, old friend, reverse phone lookup, who owns this email, reverse image search, find by username, verify identity, people search, public-data background check, who is this caller. NOT FOR structured due-diligence or company/entity intelligence investigations, or general web research synthesis (use Research).
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。
Owns the Ideal State Artifact — the primitive holding a project or task's articulated ideal state; scaffolds, interviews, grills a half-formed idea into shape via checkpointed discovery, scores completeness, reconciles feature excerpts to master, seeds from a repo, and appends decisions/changelog/verification across a locked seventeen-section order. USE WHEN ISA, ISC, ideal state, ideal state criteria, project specification, hill-climb, articulating done, fog, not yet specified, grill me, discovery interview. NOT FOR creating new skills (use CreateSkill).
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。
Physics-based reasoning framework (Musk methodology) that deconstructs a problem to irreducible fundamental truths, classifies every element as hard constraint, soft constraint, or assumption, then reconstructs the optimal solution from fundamentals alone. USE WHEN first principles, fundamental truths, challenge assumptions, real constraint, rebuild from scratch, start over, physics first, question everything, reasoning by analogy. NOT FOR structural feedback loops (use SystemsThinking).
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。
Turn an object or character reference image into a quality-gated, animation-ready procedural Three.js model built in code. Use for image-to-3D reconstruction, detail-accurate object rebuilds, stylized/likeness-maximized human characters, sculpt specs, and staged code generation.
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-powered tools for Web3 bug bounty automation. Use when you want to automate recon, run autonomous audits, or use AI agents for vulnerability discovery.
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。
Hunter mindset, recon setup, and target scoring for Web3 bug bounty. Use at the START of any new protocol hunt - scoring targets, setting up environment, understanding architecture.
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。
Reconcile contributor skills, AGENTS.md, CONTRIBUTING.md, issue and PR templates, and workflow references after repository workflow changes.
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。