'data write' 검색 결과

SurrealDB Surrealism WASM extension development. Write Rust functions, compile to WASM, deploy as database modules. Part of the surreal-skills collection.

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Delegate tasks to AI agents via Box0. Use when the user asks to review code, check security, run tests, compare tools, get multiple perspectives, research a topic, analyze data, write docs, or any task that could benefit from specialized or parallel execution. Also use when the user mentions agent names or says "ask", "delegate", "get opinions from", or "have someone".

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Generate engaging, localized App Store release notes (What's New) from git log, bullet points, or free text using canonical metadata under `./Store`. Optionally pairs with promotional text updates.

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Use for Bun file I/O: Bun.file, Bun.write, streams, directories, glob patterns, metadata.

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Use when choosing between engines or models for an agent pipeline and the answer must come from measurement on your own data, not from marketing pages: speech recognition for meeting recordings, the model that turns a transcript into notes, the critic model that checks it. Runs every variant in an isolated container, measures time, cost per hour of input (USD and RUB, with price source and date) and quality (WER/CER and course terms for ASR; code checks plus a judge of a different model for LLM steps), writes results.json/csv and one static analytics page. Triggers on "бенчмарк", "сравни движки", "сколько стоит час записи", "какую модель взять для пайплайна", "benchmark the pipeline", "compare ASR engines".

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Run an honest market-fit and viability audit of any project or idea and produce a decision doc, not code. Use when someone asks "is this viable as a business", "audit the market fit", "make the case and compare to competitors", "should I apply to YC or bootstrap", or wants to validate a project, product, or market before investing more time. Gathers verifiable traction data first, researches the competitive field, gets an independent cold read, writes a doc with pre-committed pass/middle/kill criteria and a concrete week-1 assignment, then hardens it with an adversarial review loop.

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Turn any X (Twitter) profile into a 10.3s animated "POSTING LICENSE" card video — a fake driver's license in X's branding: the card slides in over an animated dot-matrix ground, license text types on letter-by-letter, follower / following / post counters tick up, a diagonal glimmer sweeps as the card tilts in 3D, it flips to a fine-print back with a signature write-on, then crouches and leaps out of frame. Trigger on: "X driver's license", "posting license", "make an X license for @handle", "license card video". The whole composition is a finished template — the agent only supplies profile data and renders.

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Write clear, searchable help center articles and FAQ entries based on support data, product documentation, and common customer questions. Use when the user requests knowledge base article writing or provides relevant inputs for this workflow.

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Produce audio-first podcast episodes with generative tools — design the show and episode format (interview, narrative, news brief, two-host conversational), write scripts for the ear, decide between fully-synthetic and hybrid (recorded human + synthetic) production and meet the disclosure duty each triggers, cast and direct multi-voice TTS for consistency and chemistry, build episode structure (cold open, intro/outro, segments, ad slots), assemble and edit, clear music and SFX rights, hit podcast loudness and delivery standards, ship metadata/chapters/transcripts through RSS, and pass platform AI-content policy and QA before publishing. Use this skill whenever the deliverable is a podcast episode or a podcast show bible, or when an agent must make production, rights, disclosure, or delivery decisions for spoken-word audio. Not for music tracks, single-voice notification prompts, or video where picture leads (route audio-for-video to a video skill).

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Generate data-backed content briefs by analyzing Google SERP results, competitor content, keyword intent, and audience questions. Produces writer-ready briefs with target queries, required subtopics, recommended format, word count, and competitive differentiation angles.

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Author and maintain MANUAL and hybrid test cases and suites in TestRail, Xray (Jira), Zephyr Scale, and Qase. Covers test-case anatomy (title, preconditions, steps, expected results, test data), suite/section organization, bulk authoring from user stories and acceptance criteria, ambiguous-step linting, CSV/API import-export payloads per tool, requirement traceability and coverage gaps, review hygiene, and when a manual case should graduate to automation. Use when: "write a test case," "manual test case," "TestRail case," "Xray test," "Zephyr Scale case," "Qase case," "import CSV into TestRail," "lint these steps," "traceability report," "should this be automated." Not for: Generating automated TEST CODE — that is ai-test-generation. Sprint-level WHAT-to-test selection — that is test-planning. Related: ai-test-generation, test-planning, exploratory-testing, qa-project-context.

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Turn a vague bug report into a VERIFIED minimal reproduction and then a failing regression test, agent-driven end to end. Covers extracting the implicit repro from a thin report (env, build, steps, data), the reproduce-minimize-isolate-capture loop, git bisect to find the introducing commit, building a deterministic minimal repro (fixed seeds, frozen time, stubbed network), writing the failing regression test BEFORE the fix (red) and confirming the fix flips it green, and writing repro evidence back into the ticket. Distinguishes flaky-not-reproducible from environment-specific. Use when: "reproduce this bug," "minimal reproduction," "repro steps," "find the commit that broke it," "git bisect," "make the repro deterministic," "write a failing test for this bug," "regression test for a defect," "can't reproduce this bug." Not for: Classifying/deduplicating/severity-routing existing failures without reproducing them — that is ai-bug-triage. Generating tests from specs rather than from a defect — that is ai-test-generation. Related: ai-bug-triage, ai-test-generation, test-reliability, systematic-debugging, qa-project-context.

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Runtime per-test healing with evidence: multi-attribute selector healing, environment-aware diagnosis, flake classification, quarantine management, and confidence-scored auto-repair. Goes beyond simple locator fallbacks to cover action-level healing, data healing, and observable repair workflows. Use when: "flaky test," "test stability," "self-healing locator," "broken locator recovery," "unreliable test," "quarantine flaky test." Not for: bulk regenerating selectors after a planned UI refactor — use selector-drift-recovery (this skill heals ONE test at runtime; that one rewrites many tests offline). Not for: classifying/clustering CI failures into bug reports — use ai-bug-triage. Related: playwright-automation, selector-drift-recovery, ci-cd-integration, qa-metrics, ai-bug-triage.

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Build Cypress test suites in TypeScript: E2E tests, component tests, custom commands, cy.intercept network control, cy.session login, Cypress Cloud, and CI integration. Covers retry-ability, the command queue, cross-origin flows with cy.origin, and data-driven testing with fixtures. Use when: "write E2E test in Cypress," "Cypress page object / custom command," "cy.," "cy.intercept," "Cypress component test," "Cypress Cloud," "cypress.config.ts." Not for: Playwright suites — use playwright-automation; flaky-test healing or quarantine — use test-reliability; bulk selector regeneration after a UI refactor — use selector-drift-recovery; Selenium-to-Cypress conversion — use test-migration. Related: playwright-automation, ci-cd-integration, visual-testing, unit-testing, test-reliability.

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Create evidence-aware, interactive visual explainers as self-contained offline HTML. Use when a user asks to explain a concept, repository module, engineering tradeoff, or incident with a diagram, walkthrough, ELI5 treatment, data/request trace, failure view, or teach-back. Do not use for a plain short answer, ordinary prose rewrite, generic website implementation, or unsupported claims presented as facts.

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Deep technical SEO auditing covering crawlability, indexation, Core Web Vitals, site architecture, canonicalization, structured data validation, and performance optimization. Use when the user asks about technical SEO, site audits, crawl issues, indexation problems, Core Web Vitals, page speed, or site architecture optimization. For content-focused SEO, see the seo-content-writer skill.

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Appsmith is an open-source low-code platform for building internal tools, admin panels, and dashboards. Use when a user asks to create CRUD interfaces, connect to databases or APIs with drag-and-drop widgets, write JSObjects for business logic, or self-host Appsmith with Docker or Kubernetes.

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World-class caching strategies - cache invalidation, Redis patterns, CDN caching, and the battle scars from cache bugs that served stale data for hoursUse when "cache, caching, redis, memcached, cdn, ttl, invalidation, stale, cache aside, write through, cache stampede, thundering herd, cache warming, etag, cache-control, caching, redis, memcached, cdn, performance, http-cache, ttl, invalidation" mentioned.

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Keeps private and unapproved material out of a public build. Scans the built output (HTML, serialized component payloads, client JS and CSS chunks, static data routes, public files) against a private tier that always applies and a draft tier that applies in production. Gates work-in-progress so it shows in preview and is absent from production, and keeps sign-off in a ledger only the human writes. Use when a site or app publishes content that agents drafted or that came from private sources.

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Reverse-engineer the hook from a viral X (Twitter) tweet or thread URL. Identifies which of the 10 canonical 2026 X formulas it uses (one-liner contrarian, data-point, build-in-public, quote-tweet, mini-list, relatable cold-open, listicle-thread, story thread, curiosity-gap, how-I teardown), explains why it worked, and returns a blank template mapped to your topic with its primary goal. Use to learn from a tweet you admire. Not for writing your own (use x-post-writer or x-thread-builder).

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Read your X (Twitter) audience and niche from real data. Pull a handle's recent tweets (yours or a competitor's) with likes, replies, and views, see which formats and hooks are working, read the repliers on a tweet (X gates likers, so repliers are the signal), and scan a niche query for top tweets. Powered by Apify, no login. Triggers on "analyze my tweets", "what is working on X", "read the replies", "competitor tweets", "who is engaging". Not for writing a tweet (use x-post-writer).

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Query Google NotebookLM notebooks for source-grounded, citation-backed answers from user-uploaded documents. Manages notebook library, handles Google authentication, and supports smart discovery. Works standalone via /blog notebooklm or internally from blog-write and blog-researcher for Tier 1 research data. Falls back gracefully when not configured. Use when user says "notebooklm", "notebook", "query notebook", "ask notebook", "notebook research", "source grounded research", "document query", "notebook library".

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AI citation readiness audit ONLY (does not touch Google rankings, use blog-rewrite for combined Google+AI work). Use whenever the user wants their content to rank in ChatGPT, Perplexity, Claude, Gemini, or Google AI Overviews. AI citation optimization audit scoring blog posts for ChatGPT, Perplexity, and Google AI Overview citability. Evaluates passage-level citability, Q&A formatting, entity clarity, structured data, and AI crawler accessibility. Generates citation capsules and a 0-100 AI Citation Readiness score. Use when user says "geo", "ai citation", "ai optimization", "citation audit", "aeo", "perplexity optimization", "chatgpt citation".

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Suede-owned SEO and generative-search audit discipline. Runs a nine-lane evidence-based audit: access, intent, metadata, structure, supported schema, E-E-A-T, clusters, and exact rewrite fixes. Use when a page or site needs a deep standalone SEO/AI-visibility audit with scored lanes. NOT FOR: a fast A-F launch-appeal grade (use suede-visibility-grader); conversion-path rework after the audit (use suede-site-alchemy); getting cited by ChatGPT/Perplexity/AI Overviews (use suede-ai-seo).

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