「sources」の検索結果

SolidJS fine-grained reactivity — signals, effects, memos, stores, resources, control-flow components. Load when writing Solid components or reactive state.

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Mapbox GL JS interactive vector maps. Use when building a map with sources and layers, expressions, clustering, 3D terrain, geocoding or directions.

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GraphQL API server with Apollo Server — schema, resolvers, context, error handling, data sources, plugins

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A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project updates, etc.).

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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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Research what people have discussed in the last 30 days across high-signal public platforms. Use when the user asks for `/last30days`, recent trend research, competitive intelligence, market pulse briefs, or engagement-ranked synthesis from Reddit, Hacker News, GitHub, X, YouTube, Polymarket, and similar sources.

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。

Sync suite skill installation instructions with upstream sources and ensure Gaia-compliant styling.

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Phase 1 of the Gaia evidence verification pipeline. Use this skill whenever you need to gather, consolidate, or refresh raw evidence for named skills in the registry. Trigger phrases: "collect evidence", "populate the data lake", "gather sources", "run ev-collection", "Phase 1", "compile the evidence index", "refresh the unified lake", "aggregate skill evidence", "build the evidence database". Also invoke as the first step before running ev-star-verification, ev-adversarial-audit, or ev-link-validation — nothing downstream is meaningful without a fresh, compiled index. Covers GitHub repo links, stargazer signals, YouTube showcases, arXiv papers, peer reviews, benchmark results, blog/newsletter posts, and self-attestation artifacts.

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Phase 2B of the Gaia evidence verification pipeline. Verifies benchmark-result rows and benchmark-source candidates against registry/benchmark-sources.json before adversarial audit, link validation, catalog promotion, or ingestion. Use when running /ev-pipeline, checking benchmark-result evidence, reviewing benchmark-source candidates, or preparing benchmark rows for /gaia-ingest-batch.

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Discovery-only global trending extension for Gaia. Snapshots configured external skill sources, prioritizes five-candidate pages for L4 review, and stops before trust, evidence, intake, or registry mutation.

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Clones a STATIC IMAGE ad into finished ads for your own product, into a reusable prompt TEMPLATE, or both — the template is what makes the ads and the ads are what prove the template. Round-trips the frame through gpt-image-2, nano-banana-pro or reve-2.1 until it reproduces, replaces every brand-specific with a {placeholder}, then fills it with your product pinned to a real photo. Use for "clone this ad for my product", "rebuild this competitor's ad for us", "make me ads like this", "reverse engineer this ad", "make this ad reusable", "add this to my prompt library", or "clone my competitors' ads" with NO file attached — it sources one via spy-competitor-ads rather than asking which. **Among cloners the source's medium decides**: a still, or nothing attached, lands here; "clone this ad" plus a VIDEO is clone-video-ad. NOT for generating an ad from a brief (chatgpt-image-ad, nano-banana-image-ad), nor animating a still as-is (image-to-motion). Refuses to render your product without a real photo of it.

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Create or update the DocC documentation in Sources of a spark-ios-component-XXX.

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Create or update an environment file in the Environment folder in Sources of a spark-ios-component-XXX and add or update unit tests.

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Create or update a constants file in the Constants folder in Sources of a spark-ios-component-XXX and add or update unit tests.

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Create or update an enum file in the Enum folder in Sources of a spark-ios-component-XXX and add or update unit tests.

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Create or update an model file in the Model folder in Sources of a spark-ios-component-XXX and add or update unit tests.

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Create or update a token file in the Token folder in Sources of a spark-ios-component-XXX and add or update unit tests.

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Create or update an use case file in the UseCase folder in Sources of a spark-ios-component-XXX and add or update unit tests.

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Create or update an view model file in the ViewModel folder in Sources of a spark-ios-component-XXX and add or update unit tests.

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Create or update an view files for UIKit and SwiftUI in the View folder in Sources of a spark-ios-component-XXX.

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Create or update a accessibility identifier file in the AccessibilityIdentifier folder in Sources of a spark-ios-component-XXX and add or update unit tests.

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Tunes noisy detections by analyzing historical alert data to quantify false-positive sources, recommend allow-list filters and threshold adjustments, and measure precision impact. Activates for requests to tune a detection, reduce false positives, or analyze alert noise and recommend filters.

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Expands one indicator into the full scope of an incident: pivoting across data sources to find related hosts, accounts, and infrastructure, building a timeline, and bounding what is and is not affected. Activates for requests to scope an incident, pivot from a single IOC, or determine the blast radius of a detection.

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Extracts structure and indicators from a Windows PE file without executing it: headers, sections, imports/exports, resources, entropy, and embedded strings to infer capability and packing. Activates for requests to statically analyze a PE, EXE, or DLL, or inspect imports and headers.

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。