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Run an extremely strict maintainability review for abstraction quality, giant files, and spaghetti-condition growth. Use for a thermo-nuclear code quality review, thermonuclear review, deep code quality audit, or especially harsh maintainability review.

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Use for Vercel cost and performance optimization on deployed projects, especially Next.js, SvelteKit, Nuxt, and limited Astro apps. Collect Vercel metrics, usage, project config, and code scan results first; investigate only metric-backed candidates; produce ranked recommendations grounded in verified files and version-aware Vercel/framework docs. Trigger for Vercel bill reduction, slow or expensive routes, caching opportunities, Function Invocations, Build Minutes, Fast Data Transfer, Core Web Vitals, Bot Management, Fluid compute, or cost breakdown requests.

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Canonical rules for writing and reviewing Rust code in Shift's crates. Use whenever you add or change `.rs` code, especially error handling (`ok_or`, `ok_or_else`, `map_err`, `?`, `CoreError`, `StoreError`, `SlugError`, `BridgeError`), entity lookups by id, checked arithmetic and integer conversions, or helpers that several call sites repeat. Load `rustdoc` as well when the change adds or edits doc comments.

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Add or revise source-level Rustdoc for Shift Rust APIs. Use before writing or editing documentation comments in `.rs` files, especially for public or crate-visible APIs, domain structures, compiler adapters, persistence boundaries, trait implementations, unsafe code, or any API where ownership, units, coordinate spaces, mutation, I/O, sparse behavior, failure modes, panics, or concurrency are easy to misunderstand.

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When the user wants to host a tech event, meetup, workshop, or community gathering — especially using Luma. Also use when the user mentions "host an event", "meetup", "workshop", "Luma event", or "community event".

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When the user needs to analyze, categorize, or extract actionable insights from customer feedback across multiple sources, especially feature requests.

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Use when receiving critical feedback on an analysis or manuscript, before implementing suggestions, especially if feedback seems unclear or methodologically questionable - requires verification, not performative agreement or blind changes

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Keep a running implementation-notes.md during a build, logging every deviation from the plan and every discovered edge case. Use whenever implementing against an agreed plan or spec, especially in long autonomous sessions.

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Write an implementation plan that leads with the decisions the user is most likely to change, and buries the mechanical work at the bottom. Use when planning is requested before a build, especially after brainstorming or an interview.

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Continue the current local Codex conversation and coding task in an AgentKit Studio cloud Codex Sandbox using a Studio URL and short one-time pairing code. Use when the user asks to hand off, migrate, or continue a local repository in Studio, especially when a prompt contains a Studio address and pairing code. Export the complete user-visible user and assistant message history from every prior turn, including interrupted turns and progress commentary, create a temporary Studio Sandbox, restore tracked and non-ignored working-tree files plus Git metadata, inject that visible history into the cloud Thread, transfer GitHub CLI authentication separately when needed, and send one final continuation message; never copy system or developer prompts, reasoning, tool logs, SQLite state, global configuration, local skills, or SSH private keys.

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Use before writing code against a library, SDK, API, or framework whose current version you are not certain of — especially fast-moving ones. Trigger when an import fails, a method does not exist, a config key is rejected, a deprecation warning appears, or the user says the code was written against an old version.

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Writes, explains, debugs, and optimizes BI calculations - Power BI / Fabric DAX measures and calculated columns, Tableau calculated fields (FIXED/INCLUDE/EXCLUDE LOD expressions, table calculations), and Looker LookML measures, dimensions, and derived tables. Use it whenever the request involves DAX, CALCULATE, a Power BI measure, a Tableau calc or LOD, LookML, or a business metric such as YoY, YTD, rolling 12 months, running total, percent of total, distinct customers, ranking, new vs returning customers, closing balances, or basket analysis. Use it especially when someone says a measure "shows the wrong total", "is blank", "ignores my slicer/filter", "repeats the same value on every row", or "is slow" - those are filter context, context transition, LOD order-of-operations, or fanout bugs this skill is built to diagnose. Produces the formula, the context it evaluates in, and a hand-checkable test with expected numbers.

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Score and compare covariance estimates with precise's assessor panel. Use when you need to judge an estimate out-of-sample or rank competing estimators — and especially in high dimensions, where the plain held-out likelihood is misleading.

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Cost discipline for recurring /loop runs. A loop multiplies per-iteration cost by iteration count, so waste compounds. Encodes cache-aware pacing (avoid the 300s dead zone), event-driven-over-polling, a no-change short-circuit, a compact state handle carried between ticks, and a stop condition. Use when a /loop is running or being set up — especially long-lived or frequently-firing ones.

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Write less code and say less about it. Applies YAGNI and stdlib/native-first so the agent writes the minimum code that needs to exist, and responds tersely — stripping filler, hedging, and pleasantries while keeping code, identifiers, and technical terms exact. Use whenever writing, modifying, refactoring, reviewing, or explaining code, or any response where output volume drives token cost — even if the user never says "minimal" or "concise". Especially in agentic coding, where the volume of generated code and prose runs up the bill.

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Build authority by teaching the problem space, not announcing features. Use when the user finds "marketing" distasteful and does none, publishes only product updates, or wants a sustainable content and GitHub-README strategy that developers actually respect.

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Advogado criminalista especializado em Maria da Penha, violencia domestica, feminicidio, direito penal brasileiro, medidas protetivas, inquerito policial e acao penal.

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Estratega de Inteligencia de Dominio de Andru.ia. Analiza el nicho específico de un proyecto para inyectar conocimientos, regulaciones y estándares únicos del sector. Actívalo tras definir el nicho.

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Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .xltx, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

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Improves the quality of images, especially screenshots, by enhancing resolution, sharpness, and clarity. Perfect for preparing images for presentations, documentation, or social media posts.

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Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

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Generate or update repository-specific AGENTS.md instruction files from real repo evidence. Use when asked to create, design, scaffold, split, or improve root or scoped AGENTS.md files for Codex/Claude/agent workflows, especially when a repo needs directory-specific rules, validation commands, generated-file boundaries, or a short agent onboarding router.

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Mandatory audit workflow for UI/UX changes that reads current state FIRST, checks for redundancy, respects clean design philosophy, and identifies genuine gaps before implementation. Auto-invoked when user mentions UI, UX, design, layout, homepage, page improvements, visual changes, or interface modifications.

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Applies the reasoning style of Daphne Koller (machine learning pioneer, co-founder of Coursera, founder and CEO of Insitro). Use this skill whenever you encounter problems involving AI and machine learning in biology, drug discovery, interdisciplinary collaboration, data generation vs. data mining, or transitioning from academia to industry. Trigger this skill when advising on career trade-offs, building cross-functional teams (especially bridging engineers and domain experts), designing data pipelines, evaluating causality vs. correlation, or applying AI to physical systems ('where bits meet atoms'). Channel her focus on fit-for-purpose data, pragmatism, and disproportionate leverage.

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。