「exa」の検索結果

Use this skill when the user requests current information, documentation, coding examples, or web research beyond the knowledge cutoff. Queries Google's AI Search mode to retrieve comprehensive AI-generated overviews with source citations from 100+ websites. Returns markdown with inline footnoted references [1][2][3]. You will receive a detailed Markdown file with references and information summarized directly from Google's AI search. Ideal for you to get new information and clues for further research.

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Search oip-visual-v2 for traceable prompt-image pairs and open local result galleries. Use when finding, inspecting, comparing, browsing, or copying real image-generation references or exact source prompts. After references are selected, adapt them into a derived bilingual prompt when requested; use img-gen-taste first when the visual direction is still unclear.

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。

Create original short videos using the 尺度展开｜微小材质扩张后原样回收 Creative DNA for MiniMax H3 or Seedance 2.0. Use when the user wants this causal, camera, motion, rhythm, or payoff structure with new subjects and surfaces.

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。

Use when a skill is brittle, drifting, repeatedly failing, or needs a Reliable Skill Contract. Trigger for phrases like skill lifeguard, reliable skill, self-maintaining skill, negative examples, verification checkpoints, drift signals, replay hooks, or failure log to skill patch. Audits or patches skills so high-value workflows include explicit forbidden behaviors, checkpoints, machine-checkable done conditions, replay or smoke hooks, and drift detection.

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。

Scaffold or standardize a production-ready repository structure with specs, source layout, tests, CI, agent context, config examples, release notes, and operational docs. Use when starting a new repo, turning a prototype into a maintainable project, adding missing repository foundations, or creating a repo skeleton before implementation. For AGENTS.md-only context scaffolding, use agentsmd-scaffold.

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。

n8n workflow automation knowledge base. Provides n8n node information, node functionality details, workflow patterns, and configuration examples. Covers triggers, data transformation, data input/output, AI integration, covering 10 nodes. Keywords: n8n, workflow, automation, node, trigger, webhook, http request, database, ai agent.

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。

Recommend font combinations for different use cases. Provide Google Fonts alternatives to premium fonts with hierarchy 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。

Design or audit a Jacobian operation’s mathematical contract, boundedness, exact results, and composition.

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。

Use Jacobian’s typed operations when exact computation or structural analysis can help solve a mathematical problem.

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。

Analyze web page content, structure, and layout to understand what a page contains and how it is organized. Trigger when the user asks to: analyze a page, understand page structure, inspect a website, summarize page content, examine page layout, review a web page, or describe what is on a page.

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。

Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.

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 Riverpod "Cannot use Ref or modify other providers inside life-cycles/selectors" crash in @riverpod provider bodies. Use when: (1) Crash during provider disposal with this exact error message, (2) Using keepAlive() with timer-based disposal, (3) Async callbacks (.then, .catchError) try to use ref.read() or ref.invalidateSelf(), (4) Error occurs after ref.onCancel/onResume/onDispose callbacks fire. Solution: wrap ref operations in try-catch or avoid using ref in async callbacks entirely.

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 ClickHouse query errors in Rust when using clickhouse-rs crate. Use when: (1) "string is not valid utf8" errors - typically FixedString columns need CAST to String, (2) "tag for enum is not valid" errors - typically Option<T> fields receiving non-NULL values, (3) Sum/count aggregations returning Float64 but Rust expects u64, (4) LEFT JOIN results with empty strings where Rust expects Option::None, (5) "not enough data, probably a row type mismatches a database schema" - query SELECT returns fewer columns than the Rust Row struct expects (common when multiple query functions share the same struct but one function is missing columns added later), (6) Garbled/corrupted data when INSERTing to FixedString(N) columns using String Rust type - silently corrupts data (no error!) because String adds a length prefix but FixedString expects exactly N raw bytes. Fix: use [u8; N] with #[serde(with = "BigArray")] from serde-big-array, (7) "the trait bound `[u8; 64]: serde::Serialize` is not satisfied" when using [u8; N] arrays in Row structs - need #[serde(with = "BigArray")] annotation from serde-big-array crate.

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。

Code intelligence over repositories Guaardvark has indexed: semantic code search, exact-text search, file listing, PageRank repository map, import dependency graph, reading one class or function, analysis and generated rewrites, plus the System Mapper and self-improvement status. Use when the user asks where something is implemented, how modules depend on each other, or wants an architecture map of an indexed repo.

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。

Run the mandatory verification stack when changes affect runtime code, tests, examples, or build and test behavior in the OpenAI Guardrails Python repository.

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。

Create the required PR-ready summary block, branch suggestion, title, and draft description for openai-guardrails-python after runtime, tests, examples, build/test configuration, or behavior-impacting docs change.

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。

Assign, validate, normalize, and explain Luhmann/Zettelkasten-style project-note codes for Chinese book manuscripts, Obsidian Markdown folders, Mandala-Grid section files, HyperCard Markdown stacks, and project-note JSON to EPUB workflows. Use when Codex needs to scan folders for 部/章/節/項/目 numbering, generate stable card ids, insert branch codes without renumbering existing notes, map letter-coded branches to Obsidian Mandala sections, preserve K### keyword index cards, sanitize private catalogs into public examples, or prepare card IDs for EPUB and HyperCard output.

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。

Extract exactly 8 context-sensitive keywords from Chinese, English, or mixed text and turn them into a distributed weighted Graph View with no center goal node. Use when Codex needs keyword extraction, blacklist filtering, co-occurrence edges, node definitions/notes, weighted graph JSON, or an online Graph View tool for text analysis.

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。

Scan repositories for newly disclosed CVEs in dependencies after a specific cutoff date. Takes a repository path, cutoff date (YYYY-MM-DD), and optional parameters for transitive dependencies. Parses dependency manifests (package.json, pom.xml, requirements.txt, go.mod, Cargo.toml) and lockfiles to extract exact versions. Queries vulnerability databases (OSV.dev, NVD, GitHub Advisory) to identify CVEs disclosed strictly after the cutoff date. Distinguishes between newly disclosed CVEs and previously known CVEs. Use when: (1) Performing security audits to find new vulnerabilities since last review, (2) Checking if new CVEs affect a historical codebase version, (3) Generating compliance reports showing vulnerability status at specific dates, (4) Tracking security posture changes over time. Supports npm, Maven, pip, Go modules, Cargo, and other major ecosystems.

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。

Automatically reduces bug-triggering test cases to minimal form while preserving the failure. Use when debugging with large, complex test cases that need simplification, reproducing bugs with minimal examples, or creating regression tests from verbose failure scenarios. Takes a failing test and systematically removes unnecessary inputs, steps, assertions, and code using delta debugging and other reduction algorithms. Supports unit tests, integration tests, input files, and multiple programming languages (Python, JavaScript, Java, C/C++).

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。

Removes unnecessary code from a repository while preserving exactly the behavior exercised by a given test suite. Use this skill when you need to debloat, slim down, or remove unused code from a codebase based on test coverage. The skill analyzes which code elements (files, classes, functions, methods, branches, imports) are exercised by tests, identifies unreachable or unused code, and safely removes it while ensuring all tests continue to pass. Triggers when users ask to remove unused code, debloat based on tests, eliminate dead code guided by test coverage, or slim down a repository to only test-required functionality.

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。

Explains runtime errors and compilation failures with actionable debugging guidance. Use when Python or Java code throws runtime exceptions (NullPointerException, TypeError, AttributeError, etc.), compilation errors (syntax errors, type mismatches, import failures), or dependency issues. Analyzes error messages, stack traces, and code context to identify root causes and provide concrete fixes with examples. Distinct from test-related errors - focuses on errors during normal code execution and build processes.

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。

Analyzes and verifies semantic equivalence between two functions, classes, or modules by examining control flow, data flow, and observable behavior. Use when comparing code implementations (refactored vs original, different implementations of same functionality, migration verification), determining if two code artifacts produce identical behavior, identifying behavioral differences between code versions, or validating that code changes preserve semantics. Supports formal reasoning and symbolic execution approaches.

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。

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。