「rce」の検索結果

Fix 404 errors for frontend JS files when using Vite proxy. Use when: (1) Browser shows "Failed to load resource: 404" for JS/JSX files that exist on disk, (2) Vite serves HTML instead of JavaScript for module imports, (3) You have a client folder named "api" (or similar) AND a Vite proxy configured for "/api". The proxy intercepts requests for client-side files when folder names match proxy paths. Applies to Vite, Vite+React, Vite+Vue projects with dev server proxy configuration.

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Fix false-positive Cloud Run deploys where `gcloud builds submit --tag` silently fails but the follow-up `gcloud run services update --image :latest` succeeds against a stale image, producing a confident "Deploying... Done" message with pre-fix code still live. Use when: (1) gcloud builds submit prints "ERROR: (gcloud.builds.submit) Invalid value for [source]: Dockerfile required when specifying --tag" but the shell scrolls past it, (2) code changes verified locally aren't visible in production after a deploy that printed "revision ... has been deployed and is serving 100 percent of traffic", (3) Chaining `gcloud builds submit` and `gcloud run services update` in a single copy-paste block, (4) Using the mutable `:latest` tag for Cloud Run deploys.

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。

Fix deployed Rust binaries not reflecting code changes when using docker buildx. Use when: (1) Code changes are verified locally (tests pass) but production behavior doesn't change after deploy, (2) Docker image has a new tag but contains old compiled binary, (3) Dockerfile uses multi-stage build with dependency pre-compilation layer and source copy layer. Docker buildx layer caching can serve stale compilation output even when source files change, especially with cross-compilation (--platform linux/amd64).

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。

Source-backed research workflow for AI agents: scope, sources, claims, and task-appropriate Lite or Full checks.

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。

Source-backed research for AI agents: scope, sources, claims, and task-appropriate Lite or Full workflows.

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。

Combines search results from multiple sources into coherent, deduplicated answers with source attribution. Handles confidence scoring based on freshness and authority, and summarizes large result sets effectively.

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。

This skill applies brand guidelines to content creation. It should be used when the user asks to "write an email", "draft a proposal", "create a pitch deck", "write a LinkedIn post", "draft a presentation", "write a Slack message", "draft sales content", or any content creation request where brand voice should be applied. Also triggers on "on-brand", "brand voice", "enforce voice", "apply brand guidelines", "brand-aligned content", "write in our voice", "use our brand tone", "make this sound like us", "rewrite this in our tone", or "this doesn't sound on-brand". Not for generating guidelines from scratch (use guideline-generation) or discovering brand materials (use discover-brand).

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。

Populates investment banking pitch deck templates with data from source files. Use when: user provides a PowerPoint template to fill in, user has source data (Excel/CSV) to populate into slides, user mentions populating or filling a pitch deck template, or user needs to transfer data into existing slide layouts. Not for creating presentations from scratch.

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。

Builds traceability matrices connecting requirements to design documents to source code implementation, tracking the complete development lifecycle. Use when you need to verify implementation completeness, ensure all requirements are implemented in code, generate compliance documentation, audit requirement coverage, identify orphaned code, or create traceability reports for stakeholders. Supports parsing requirements from Markdown, Word, and PDFs; extracting design from architecture docs and API specs; and scanning source code for implementations. Outputs to Markdown tables, Excel/CSV, and HTML visualizations.

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Analyze source code statically to detect potential functional bugs including null dereferences, incorrect condition checks, unreachable code, inconsistent state updates, logic errors, resource leaks, and type mismatches. Report suspicious code locations with detailed explanations, severity levels, and confidence assessments. Use when reviewing code for bugs, performing code audits, or when the user asks to find bugs, detect issues, analyze code for problems, or perform static analysis.

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Systematic external reference searching across documentation, open-source repositories, and web resources. Use when working with unfamiliar libraries, APIs, or when needing production-quality implementation examples.

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。

Enforces strict modular code architecture: SRP, no monolithic index files, no catch-all utils, 200 LOC hard limit. This rule is NON-NEGOTIABLE. Violations BLOCK all further work until resolved.

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Analyze existing test suites and source code to suggest additional unit tests that improve test coverage. Use this skill when working with test files and source code to identify untested code paths, missing edge cases, uncovered branches, untested error conditions, and gaps in test coverage. Supports major testing frameworks (pytest, Jest, JUnit, Go testing, etc.) and generates targeted test suggestions based on coverage analysis.

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Installs and configures ktx, the open-source context layer for data agents — runs ktx setup non-interactively with hidden CLI flags, configures database connections and embeddings, installs agent integration, and verifies readiness. Use when the user asks an agent to add ktx to a project, connect data sources, install agent rules, ingest schema, or troubleshoot a local ktx install.

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Search the web, read source pages, and retrieve structured records with Firecrawl. Use for current information, finding sources, reading a supplied URL, or looking up data-provider capabilities.

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| Nuxt 5 production optimization: hydration, performance, testing with Vitest, deployment to Cloudflare/Vercel/Netlify, and migration from Nuxt 4. Use when: debugging hydration mismatches, optimizing performance and Core Web Vitals, writing tests with Vitest, deploying to Cloudflare Pages/Workers/Vercel/Netlify, or migrating from Nuxt 4 to Nuxt 5.

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| Nuxt 4 production optimization: hydration, performance, testing with Vitest, deployment to Cloudflare/Vercel/Netlify, and v4 migration. Use when: debugging hydration mismatches, optimizing performance and Core Web Vitals, writing tests with Vitest, deploying to Cloudflare Pages/Workers/Vercel/Netlify, or migrating from Nuxt 3 to Nuxt 4.

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。

Learn reusable 2D motion-generation knowledge from user-specified action resources with `/img2mo-learn <resource>`. Use when the user provides videos, extracted frame sequences, spritesheets, Spine assets, generated outputs, failed attempts, or reference motion folders and wants to summarize animation timing, pose beats, style traits, prompt patterns, extraction/cropping rules, or failure lessons into the project `img2mo-knowledge/` folder for later `/img2motion` generation.

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Think and work like an expert Biophysicist. Use when a task calls for Biophysicist judgment. Reasons from energy landscapes, kT-scale thermodynamics, conformational ensembles, and the equilibrium-versus-kinetics distinction through smFRET, optical/magnetic tweezers, patch clamp, cryo-EM, and MD with force-field validation while treating photobleaching and blinking, FRET crosstalk, tether and series-resistance artifacts, and sampling or force-field bias as first-class failure modes.

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。

Content-derived infographic poster — reads the source file and builds a statistical poster from the facts already in it. Not a dashboard, not a CV, not an AntV template. Uses common-scale encodings (Cleveland–McGill floor), ISOTYPE unit counts (Neurath), custom data glyphs (Lupi/Fragapane), and a lossless data table. Palette, glyphs, and composition are derived from the source's own content. No pies, donuts, gauges, 3D charts, or fabricated KPIs. Part of the reimagine-it Content-Derived Design suite.

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。

Production guidance for converting sourced data and approved claims into truthful, accessible, deterministic animated visualizations with D3. Use for data-driven charts, maps, networks, hierarchies, transitions, annotations, responsive video variants, frame-by-frame browser rendering, and visualization QA; not for generic dashboards, unsourced decorative charts, or ordinary motion graphics without a data contract.

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。

Provider-independent ecommerce product imagery production for marketplace listings, product pages, hero shots, lifestyle scenes, comparison charts, infographics, variant/packaging images, virtual try-on or placement mockups, ads, and AI-assisted product visuals. Use when an agent must plan, generate, edit, review, localize, package, or QA truthful commercial product images while managing SKU continuity, marketplace requirements, claims, rights, releases, accessibility, and approval.

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。

Provider-independent media quality control and delivery direction for generated images, video, audio, ads, product content, social clips, broadcast and streaming assets, localization packages, and mixed-source edits. Use when an agent must define final export specs, inspect technical and perceptual quality, check captions/audio/color/accessibility/provenance/rights, create delivery sheets, version filenames, checksums, manifests, package deliverables, set acceptance or rejection criteria, and perform final delivery QA before handoff to a platform, broadcaster, streamer, client, or ad trafficker.

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。

Generates 3D conformer ensembles using RDKit ETKDGv3 with knowledge-enhanced distance geometry, MMFF94/UFF force-field optimization, CREST + GFN2-xTB semi-empirical refinement, and macrocycle-aware torsion preferences. Provides explicit decision rules for single vs ensemble conformer use, RMSD pruning, energy windows, conformer count, and force-field choice. Use when preparing 3D ligands for docking, generating descriptor input for 3D QSAR, or sampling macrocycle/peptide conformational ensembles.

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。