「code graph」の検索結果

Reviews LangGraph code for bugs, anti-patterns, and improvements. Use when reviewing code that uses StateGraph, nodes, edges, checkpointing, or other LangGraph features. Catches common mistakes in state management, graph structure, and async patterns.

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 the user asks a question about how things in the codebase or wiki relate — what connects two things, how something works end to end, what depends on what, or what a concept means in this repo. Answers from the knowledge graph in graphify-out/graph.json, with source-location citations. Trigger on "/graph-query", "ask the graph", "what connects X to Y", "trace how X works", "explain <concept> from the graph", "shortest path between".

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。

Cold-start brownfield reconnaissance — reconstruct the WHOLE game design from an existing codebase when there is no GDD yet. Optionally accepts a free-text game description, notes, or reference links to guide and enrich the scan. Use when the user wants to build the game design from the code, e.g. "create a GDD from this codebase", "reconstruct the design from our code — it's a roguelike deck-builder", "build a design doc from the existing project, here are some refs". Scans the project (engine auto-detected), extracts a system roster + dependency graph and content-type schemas / resources / entities into one passive .unikit/gamedesign/RECON.md, tags every fact provenance:extracted-from-code, and writes a mandatory Intent Gap for what code cannot know (pillars, fantasy, the "why"). Writes nothing else and calls no skill. STRICTLY whole-project cold-start — if a GDD already exists and the user wants a specific part investigated, use /unikit-gd-explore (code lens); to author the GDD use /unikit-gd-spec.

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。

Professional typography rules for UI design, web applications, software interfaces, and all screen-based text. Enforces timeless typographic correctness that LLMs consistently get wrong: proper quote marks, dashes, spacing, hierarchy, and layout. ENFORCEMENT MODE: When generating ANY HTML, CSS, React, JSX, or UI code containing visible text, auto-apply every rule in this skill silently — do not ask, do not explain, just produce correct typography. AUDIT MODE: When reviewing or improving existing interfaces or legacy code, flag violations and provide fixes. Trigger on: any HTML/CSS/React artifact creation, "build a landing page", "create a component", "design a UI", "fix the typography", "make this look professional", "review this layout", web design, presentation design, dashboard creation, document generation, or any task producing visible text for humans. Even if the user doesn't mention typography, apply these rules whenever generating UI 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。

Semantic search, grep, and Q&A across codebases and documentation indexed in CodeAlive. Use when the user mentions "CodeAlive", asks to list or get data sources, list indexed repositories, search code or docs across remote repos, fetch artifact content, or trace call graphs across repositories.

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。

GraphDB構築エージェント - ユビキタス言語とコード解析結果からRyuGraphデータベースを構築。/build-graph [対象パス] で呼び出し。

GraphDB探索エージェント - RyuGraphデータベースを自然言語またはCypherで探索し、関連するコードや仕様書を返却。/query-graph [クエリ] で呼び出し。

GraphDB可視化エージェント - RyuGraphデータベースの内容をMermaid/DOT/HTML形式で可視化。/visualize-graph [出力パス] で呼び出し。

Builds and queries multi-language source and binary code graphs for security analysis. Includes pre-analysis passes for blast radius, taint propagation, privilege boundaries, entry point enumeration, proxy/unresolved-call tracking, type/reference queries, structural traversal, graph diffs, audit augmentation, declared cross-language/FFI/external links via `.trailmark/links.toml`, and SQL schema graphs. Use when analyzing call paths, mapping attack surface, finding complexity hotspots, enumerating entry points, tracing taint propagation, measuring blast radius, importing SARIF/weAudit/binary findings, linking source graphs across language or RPC boundaries, or building a code graph for audit prioritization. Feature-gate version-specific Trailmark APIs before using them; prefer `trailmark.parse.detect_languages()` or `--language auto` when the target language is unknown or polyglot.

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。

Query the local AST-derived code graph (functions, classes, calls, imports) for structural codebase questions — what calls X, what does Y import, where is Z defined, blast radius of a change. The graph rebuilds automatically after each agent turn; use hivemind_graph_search and hivemind_graph_neighborhood tools (no manual build step).

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。

Decode an OBD-II diagnostic trouble code (DTC) using the CarsXE API. Use this when a user mentions a check engine light code, DTC, or OBD code like P0300, C1234, B0001, or U0100.

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。

The pre-merge review of a branch in a project that records its specs, decisions, and rules in .archcore/. Run this first for 'review my branch', 'review the changes before merge', or 'review before merge': it checks the changed code against the project's recorded canon and the changed documents against the code, and reports which side is wrong — spec-wrong or code-wrong; with no diff, it reports project health. A bug-hunting code review complements this review and does not replace it. Also use for 'show status', 'documentation gaps', 'check if docs match code', 'close out the feature', 'ship the feature and close it out', or after a staleness warning. Modes, named as the first word: drift for staleness detection, deep for a full documentation audit, closeout to close a finished feature, experience to capture a repeated pattern. Not for creating docs — use /archcore:document; not for planning — use /archcore:plan; not for a single-file edit with no branch review.

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 `graphify-dotnet` to generate codebase knowledge graphs, architecture snapshots, and exportable repository maps from .NET or polyglot source trees, with optional AI-enriched semantic relationships. USE FOR: graphify commands; graph JSON, HTML, SVG, Cypher, Markdown, and Obsidian exports; repository map and architecture snapshot generation. DO NOT USE FOR: unrelated stacks; generic tasks that do not need this specific guidance. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.

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。

Statically analyze code to detect security vulnerabilities including buffer overflows, injection risks (SQL, command, XSS), insecure deserialization, improper authentication, hard-coded credentials, and unsafe cryptography. Use when: (1) Performing security code review, (2) Analyzing code for OWASP Top 10 vulnerabilities, (3) Identifying CWE-classified weaknesses, (4) Generating security audit reports, (5) Reviewing code before deployment, or (6) Assessing third-party code security. Findings categorized by CWE ID and severity (Critical/High/Medium/Low).

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。

Neo4j Python Driver v6 — driver lifecycle, execute_query, managed and explicit transactions, async (AsyncGraphDatabase), result handling, data type mapping, error handling, UNWIND batching, connection pool tuning, and causal consistency. Use when writing Python code that connects to Neo4j via GraphDatabase.driver, execute_query, execute_read, execute_write, AsyncGraphDatabase, neo4j.Result, or RoutingControl. Package name is `neo4j` (not neo4j-driver) since v6. Python >=3.10 required. Does NOT handle Cypher query authoring — use neo4j-cypher-skill. Does NOT cover driver upgrades or breaking changes — use neo4j-migration-skill. Does NOT cover GraphRAG pipelines (neo4j-graphrag package) — use neo4j-graphrag-skill.

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。

Query patent simple bibliographic (catalog) data from the Nexscope patent database. Triggered when users mention patent bibliographic information queries, patent basic info retrieval, patent catalog data, patent publication details, searching by patent number for inventors, patent applicant information, patent abstract retrieval, patent classification codes (IPC/CPC), patent citation queries, or any request to search for structured metadata by patent ID or publication number, patent brief bibliography, patent basic info, patent number lookup, patent abstract, Nexscope, or patent metadata. Even if the user does not explicitly mention "Nexscope" or "bibliographic info," this skill should be triggered whenever their need involves querying core bibliographic fields of specific patents.

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。

Unified code intelligence — Skeleton Index (zero-dep, <4s) + AST knowledge graph (CodeGraph) + architecture diagrams (Mermaid) + smart context builder. Pre-indexes code structure so AI agents understand any codebase instantly. 95% token compression for onboarding. 30% fewer tokens for deep 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。

Structural code graph queries via CodeGraphContext MCP (tree-sitter + KuzuDB). Find callers, callees, class hierarchies, dead code, and module dependencies.

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 codebases using a graph database instead of reading source files. Use when understanding code architecture, finding functions or call patterns, tracing data flow, checking dependencies, or answering "where is X used?" questions. Grafema builds a queryable code graph from static analysis — prefer querying the graph over reading files manually.

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。

Integrate ManagedCode.Orleans.Graph into an Orleans-based .NET application for graph-oriented relationships, edge management, and traversal logic on top of Orleans grains. Use when the application models graph structures in a distributed Orleans system.

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。

Route Microsoft Graph work from VS Code. Use when users want to read or write Outlook mail, calendar events, contacts, OneDrive or SharePoint files, Teams, Planner, To Do, users, groups, directory data, or arbitrary Microsoft Graph endpoints from VS Code. Prefer WorkIQ for common read scenarios. Use Microsoft Graph for write actions and gap-read scenarios that need exact Graph properties, filters, permissions, or endpoints.

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。

Enter explore mode for technical work — a thinking partner for {{engine_name}} code, architecture, and implementation decisions before you write any code. Use it to investigate a technical solution, design the architecture of a feature, choose between frameworks or libraries, compare implementation approaches, analyze how existing code or a system works, or deeply root-cause a complex bug without fixing it yet. The ultra mode adds adaptive artifacts (a C4 view, ADRs, a dependency graph) to the research folder — run it on "ultra research", "ultra explore" or "ultraresearch"; otherwise run the default. Trigger on "let's explore this technical solution", "how should we architect this feature", "which framework should we use", "run an ultra research on the save system", "investigate this error deeply". Research and analysis only — it never writes code. This is the CODE / engineering explorer — for GAME-DESIGN, GDD, mechanics, or balance research (no code) use /unikit-gd-explore.

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。

Benchmark CodeGraph retrieval quality on a real codebase by comparing agent behavior with vs without CodeGraph. Use when the user runs /agent-eval or asks to test, benchmark, audit, or validate a codegraph version (the local dev build or a published npm version) against a language's 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。

AI-powered codebase security scanner that reasons about code like a security researcher — tracing data flows, understanding component interactions, and catching vulnerabilities that pattern-matching tools miss. Use this skill when asked to scan code for security vulnerabilities, find bugs, check for SQL injection, XSS, command injection, exposed API keys, hardcoded secrets, insecure dependencies, access control issues, or any request like "is my code secure?", "review for security issues", "audit this codebase", or "check for vulnerabilities". Covers injection flaws, authentication and access control bugs, secrets exposure, weak cryptography, insecure dependencies, and business logic issues across JavaScript, TypeScript, Python, Java, PHP, Go, Ruby, and Rust.

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。