'source' 검색 결과

Choose financial data sources and tools for price history, financial statements, news, and economic research. The skill maps market coverage, credentials, access limits, and fallback options, and provides rules for checking important figures against independent sources.

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• Choose price data sources for historical strategy testing
• Find tools for financial statements, news, and economic indicators
• Check required API keys and alternative data sources

Organize papers from Zotero into an Obsidian project knowledge base. The skill separates source notes, research synthesis, and writing outputs, requiring evidence records and source links before findings become claims used in later work.

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• Organizing Zotero papers into project source notes
• Connecting literature findings to their supporting evidence
• Preparing evidence-linked research writing

[omh] Gathering candidate papers, datasets, or repos: source candidate inventory - prepare typed source candidates and acquisition status before downstream work; use ulw-research to fetch and cite them, or research-brief to turn them into a decision-ready brief. Use when the user says: source-finder, source finder, source acquisition, source intake, find papers and datasets, find datasets and repos, find papers, find arxiv link.

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Guides an end-to-end data-warehouse migration to Amazon Redshift — discovery, schema/SQL/stored-procedure/macro/script conversion, data migration, validation, performance comparison, and reporting. Source-routed via `references/<source>/`; Teradata (Vantage) is the supported source; additional sources are added as their own `references/<source>/` sets. Text-only knowledge (no executable code) — the AI generates all execution at runtime. Applies when a user wants to migrate Teradata to Amazon Redshift, convert Teradata DDL/SQL/stored procedures/macros/BTEQ to Redshift/RSQL, or assess Teradata-to-Redshift migration complexity. Applies only to migrations targeting Amazon Redshift; migrations to other platforms (Snowflake, BigQuery, Databricks, etc.) are out of scope regardless of source. Does not cover general Redshift administration, performance tuning, or troubleshooting of existing Redshift clusters (no migration involved), or sources not listed under references/.

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Research trending topics, collect source articles, and generate a structured research brief for content creation. Stop writing from thin air — write from real sources. Use this skill when the user wants to research a topic before writing, collect sources for an article, create a research-backed content brief, or says "research [topic] for me", "find sources about [keyword]", "content brief for [topic]", "what's the latest on [product]", "research before writing", "collect articles about [keyword]", "trending news about [topic]", "gather sources for my article", "brief me on [topic]", "what are people saying about [product]", "news roundup for [keyword]", "research brief", "source collection", "content research", "prep research for writing".

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Review slow page loads and choose resource hints, browser instructions that start loading or connecting earlier. Use measurements to identify bottlenecks, then recommend preload, preconnect, prefetch, or dns-prefetch for important assets and likely next-page resources.

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• Reviewing slow loading of prominent images and fonts
• Preparing connections to external services
• Prefetching resources for likely next-page visits

Find resources loaded over unencrypted HTTP within HTTPS pages, a problem called mixed content. Review resource URLs and security headers, then guide HTTPS replacements and automatic request upgrades to address blocked or insecure resources.

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• Auditing HTTP resources on HTTPS pages
• Checking resource URLs after an HTTPS migration
• Fixing old content with embedded HTTP URLs

Review HTML to find important fonts, images, and scripts discovered late during loading. Suggest resource hints, instructions that start fetching or connecting earlier, and check the final markup delivered to the browser.

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• Reviewing preload hints for important fonts and images
• Checking early connections to third-party domains
• Auditing resource hints in rendered HTML

Manage AWS infrastructure as TypeScript code with SST v4 and Pulumi. Guides resource creation, connections between services, infrastructure tests, deployment checks, troubleshooting, and resource migrations while accounting for existing project conventions.

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• Adding AWS resources to an SST v4 application
• Connecting resources and reviewing access permissions
• Adding infrastructure tests and reviewing deployment changes

Find and read documents, code, papers, and notes stored in OpenViking. The skill chooses a search method, uses directory summaries to locate relevant files, and cites resource addresses so readers can open the supporting material.

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• Checking requirements in a saved design document
• Finding files by an error message or exact term
• Locating relevant passages in stored papers and notes

Provides guidance for retrieving China A-share prices and trading volumes through the TDX protocol. The source is currently retired from automatic routing because servers stopped responding, with explicit selection retained for possible future recovery.

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• Reviewing the retired data source and its limitations
• Checking daily and intraday data retrieval methods
• Understanding ticker formats and output columns

Find information across connected workplace sources by turning a question into targeted searches. The skill adapts queries for each source, ranks and deduplicates results, and combines findings into an answer about decisions, status, documents, or policies.

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• Find past decisions across chats and documents
• Check project status across connected sources
• Locate specifications or internal policies

Turn search results from chat, email, documents, and other sources into a coherent answer. Merge duplicate information, retain source references, highlight conflicting accounts, and reflect source freshness and authority when expressing confidence in the findings.

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• Reconstruct a decision from chat, email, and documents
• Combine duplicate search results while preserving sources
• Identify conflicting accounts and changes over time

Operate Gemini Notebook through notebooklm-py commands or its Python API. Set up authentication, organize notebooks and sources, ask questions grounded in those sources, and generate or download outputs such as audio, reports, quizzes, and slide decks.

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• Organizing research sources in notebooks
• Asking questions based on collected sources
• Generating audio or reports from source material

Research topics across multiple sources, cross-check findings, and verify source URLs before producing a report with confidence labels. Choose from quick lookups to iterative investigations that preserve findings, with community sources prioritized for questions about public reactions.

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• Compare AI technology trends
• Map a market and its products
• Investigate community reactions

Retrieve Chinese medical guidelines, drug information, and regulatory documents when original sources are inaccessible. It checks document identity and version before using alternative copies, while keeping summaries and reposts separate from independent clinical evidence.

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• Finding a guideline when its original page is inaccessible
• Checking whether an alternative PDF matches the original version
• Reviewing fallback rules for Chinese medical sources

Verify statistics and claims in blog posts by fetching cited source URLs and checking if the claimed data actually appears on the page. Extracts all load-bearing claims (statistics, product or policy claims, ranking and comparative claims, named sources), validates cited URLs before fetching, and scores match confidence (exact match 1.0, paraphrase 0.7-0.9, not found 0.0). Flags uncited claims as UNVERIFIED and marks a claim verified only when this run fetched the source and found the passage. Checks that a source says what the post says it says; it cannot prove the source is true or verify first-hand experience. Use when the user says "fact check", "verify statistics", "check sources", "factcheck". Report only; not for rewriting posts (blog-rewrite).

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Implement Terraform provider ephemeral resources with the Plugin Framework: the Open/Renew/Close lifecycle, ephemeral schema design, registration via EphemeralResources, renewal for expiring credentials, and how ephemeral values flow into write-only attributes and provider configuration. Use when adding an ephemeral resource, exposing secrets/tokens/certificates that must never persist in state or plan, deciding between an ephemeral resource and a data source, or wiring short-lived credentials from one provider into another.

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When you want to monitor known sources on a schedule and feed the good stuff into your second brain. Configure sources once (YouTube, RSS/newsletters, subreddits, Hacker News, Bluesky, Mastodon, X, LinkedIn, keyword searches); each run fetches only what's new, scores it against your stated focus, writes one digest to the vault, and auto-captures high-signal items into raw/. Everything else waits in the digest until you promote it. Modes — run, digest, promote, add / sources / pause, doctor, schedule (daily launchd or systemd job). Triggers on "/radar," "run my radar," "check my sources," "what's new from my sources," "add a source," "monitor this channel," "watch this subreddit," "track this account," "daily digest," "promote item 4," "radar doctor." Complements second-brain (radar fills raw/, second-brain compiles it) and deep-research (standing surveillance vs a one-off dive).

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Build custom Python data sources for Apache Spark using the PySpark DataSource API — batch and streaming readers/writers for external systems. Use this skill whenever someone wants to connect Spark to an external system (database, API, message queue, custom protocol), build a Spark connector or plugin in Python, implement a DataSourceReader or DataSourceWriter, pull data from or push data to a system via Spark, or work with the PySpark DataSource API in any way. Even if they just say "read from X in Spark" or "write DataFrame to Y" and there's no native connector, this skill applies.

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Use Nexscope (Search Intelligence Framework) data to analyze ASIN traffic source composition and exposure distribution, covering current period/previous period/newly entered/exited period comparisons. Trigger when the user mentions ASIN traffic sources, traffic structure analysis, organic traffic vs paid traffic share, exposure score breakdown, period comparison, new/exited traffic keywords, competitor traffic analysis, SP ad keyword count, brand ad exposure, Amazon's Choice exposure, editorial recommendation exposure, Top Rated exposure, video ad exposure, organic search exposure ratio, PPC traffic sources, promotional deal traffic sources, recommendation slot structure breakdown, ASIN traffic analysis, traffic sources, organic traffic share, ad traffic share, exposure analysis, traffic structure, period-over-period comparison, keyword churn, Nexscope. Even if the user does not explicitly mention "Nexscope", if their need involves analyzing an ASIN's traffic sources, exposure channel distribution, cross-period comparison, or competitor traffic structure comparison, this skill should also be triggered.

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Use when verifying information (fact, number, quote, event, statement) against authoritative primary sources, or cross-checking a number via one-level metric decomposition (Z = P × Q). Triggers: "verify X", "is this true", "find the original source", "where is this number from", "two sources disagree", "is it true X never did Y". Covers five scenarios: (1) basic truthfulness check, (2) completeness / out-of-context quoting, (3) one-level reasoning verification, (4) negative-statement handling, (5) multi-source conflict side-by-side output. Dig into whitelisted primary sources only (user-supplied files, official websites & databases, authoritative industry sources); cited reports / charts / datasets must be downloaded and read locally to count as verified — if download is blocked, hand the link to the user. If nothing can be found, plainly state "cannot verify" rather than guessing, patching, or citing secondary paraphrases. Always reply in the user's question language.

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Verify statistics and claims in blog posts by fetching cited source URLs and checking if the claimed data actually appears on the page. Extracts all load-bearing claims (statistics, product or policy claims, ranking and comparative claims, named sources), validates cited URLs before fetching, and scores match confidence (exact match 1.0, paraphrase 0.7-0.9, not found 0.0). Flags uncited claims as UNVERIFIED and marks a claim verified only when this run fetched the source and found the passage. Checks that a source says what the post says it says; it cannot prove the source is true or verify first-hand experience. Use when the user says "fact check", "verify statistics", "check sources", "factcheck". Report only; not for rewriting posts (blog-rewrite).

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Performs comprehensive FiveM resource security, performance, and compatibility audits. Detects backdoors, RATs, SQL injection, event exploitation, NUI vulnerabilities, dupes, crash/DoS vectors, npm and build-chain supply chain attacks, and malware patterns across ESX, QBCore, QBox, ox_lib, and ND_Core frameworks, on both GTA V Legacy and Enhanced builds. Use whenever a FiveM/cfx resource is being reviewed — even if not explicitly asked — including: audit FiveM script, review FiveM security, optimize FiveM resource, check FiveM performance, FiveM code review, review Lua script security, audit ESX resource, audit QBCore resource, audit QBox resource, check for exploits, FiveM vulnerability scan, GTA V Enhanced migration check, resmon optimization, or asking whether a leaked, cracked, nulled or unknown-origin script is safe to run.

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