「code graph」の検索結果

SSL/TLS auditing, cipher suite analysis, hash algorithm identification, encryption implementation review, and cryptographic weakness detection in code

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Use when you need to apply Java secure coding best practices — including validating untrusted inputs, defending against injection attacks with parameterized queries, minimizing attack surface via least privilege, applying strong cryptographic algorithms, handling exceptions securely without exposing sensitive data, managing secrets at runtime, avoiding unsafe deserialization, and encoding output to prevent XSS. This should trigger for requests such as Review Java code for secure coding; Find input validation risks in Java code; Review Java code for injection vulnerabilities; Improve secure error handling in Java services; Harden Java code against common security flaws. Part of Plinth Toolkit

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Decision protocol for wiring a verify-then-fix loop around a code-editing LLM agent. The agent edits → runs lint/test → reads the output → fixes → re-runs, bounded by an iteration cap and an escalation rule. Activates whenever a coder agent has a verifiable success criterion (exit code, type-checker output, failing assertion) and the user wants the agent to converge to "green" on its own. Framework-agnostic — wraps Aider's `--auto-lint`/`--auto-test`, an OpenHands SWE-Bench loop, a manual LangGraph cycle, or Claude Code's bash tool just the same.

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Automatically find relevant context from knowledge graph and code relationships while coding. Detects when context would be helpful (new files, unfamiliar code, architectural decisions) and surfaces related entities, prior decisions, and code dependencies.

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Audit application source code against the OWASP Top 10 (2021) vulnerability categories — broken access control, cryptographic failures, injection, insecure design, security misconfiguration, vulnerable components, authentication failures, data integrity, logging failures, SSRF. Use when the user mentions 'OWASP,' 'OWASP Top 10,' 'security audit,' 'security review,' 'secure code review,' 'code security review,' 'vulnerability audit,' 'find vulnerabilities,' 'appsec review,' 'application security audit,' 'check for security issues,' 'broken access control,' 'IDOR,' 'SQL injection,' 'XSS,' 'SSRF,' or wants to check their codebase for common security weaknesses.

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Diagrams and checkable docs from a codebase. Draws ERDs, C4 context/container/component views, API endpoint catalogues, lifecycle/state machines, and service-to-service call maps as a validated JSON spec plus a standalone HTML viewer, with Mermaid export. Imports OpenAPI, GraphQL SDL and Prisma; otherwise reads the code (NestJS, TypeORM, Express) and writes the spec. Use for: database diagram, ERD, data model, table relationships, C4 or architecture diagram, system context, API map, endpoint list, "show me the endpoints", status flow, state machine, allowed transitions, "what happens after X is approved", how services call each other, microservice map, Mermaid diagram. Also writes documentation as a fact graph: each statement carries its source and a computed confidence, and a drift check fails CI when the code moves. Use to document a system, write architecture or onboarding docs, or explain how a system works.

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Applies Han's shared Human-Readable Output Standard to a target you already have — a file on disk, text pasted into the prompt, or a draft already produced in the conversation — by dispatching the readability-editor to rewrite its prose so the main point comes first, headings are descriptive, each paragraph carries one idea, and sentences stay short and active, while preserving every fact. Use when you want to make a document or draft readable, edit or polish prose for readability, clean up writing, tighten wording, or re-apply the readability standard to something already written. Rewrites prose only, leaving code, diagrams, and citation identifiers unchanged. Does not write new feature or system documentation — use project-documentation. Does not restructure code or review it — use refactor to restructure code and code-review to audit it. Does not judge the underlying work or raise findings; it only rewrites the writing.

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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.

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generate, refine, validate, and render diagrams from natural language, notes, code snippets, schemas, tables, or existing diagram source. use for flowcharts, swimlanes, sequence diagrams, state diagrams, er diagrams, class diagrams, architecture/c4-style diagrams, dependency graphs, gantt charts, mind maps, user journeys, sankey-style flows, org charts, network graphs, and other visual models. supports mermaid by default, graphviz dot for complex graph layout, plantuml for uml-heavy engineering diagrams, and svg output when direct markup is more reliable.

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Use Neo4j GenAI Plugin ai.text.* functions and procedures for in-Cypher embedding generation, text completion, structured output, chat, tokenization, and batch ingestion. Covers ai.text.embed(), ai.text.embedBatch(), ai.text.completion(), ai.text.structuredCompletion(), ai.text.aggregateCompletion(), ai.text.chat(), ai.text.tokenCount(), ai.text.chunkByTokenLimit(), and provider configuration for OpenAI, Azure OpenAI, VertexAI, and Amazon Bedrock. Requires CYPHER 25. Replaces deprecated genai.vector.encode(). Use when writing pure-Cypher GraphRAG, embedding nodes in-graph, generating structured maps from prompts, or calling LLMs inside Cypher queries. Does NOT handle neo4j-graphrag Python library pipelines — use neo4j-graphrag-skill. Does NOT handle vector index creation/search — use neo4j-vector-index-skill.

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Use when indexing a code repository into Cognee's code graph or querying it (callers, impact analysis, paths, endpoints) from Codex.

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Index a code repository into Cognee's code graph and query it deterministically (callers, impact analysis, paths, endpoints). Use for structural code questions, "index this repo", and checking what a re-index changed.

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Builds per-repo code graphs in JSON and markdown-ready derived artifacts. Use when you need blast radius, symbol-level maps, import graphs, inheritance, or test links.

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Expert guide for designing and consuming GraphQL APIs. Covers Apollo Server/Client, NestJS GraphQL (Code-First & Schema-First), TypeGraphQL, caching, and N+1 query optimization.

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Expert guide for in-memory Abstract Syntax Tree (AST) code knowledge graphs, real-time symbol dependency mapping, refactoring blast radius calculation, and dead code eradication / Panduan ahli graf pengetahuan AST kode in-memory, pemetaan dependensi simbol real-time, kalkulasi radius dampak refaktor, dan pembersihan kode mati.

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AAD アプリ登録を行わずに、Microsoft Graph API 経由で SharePoint を包括的に操作する。リスト（ドキュメントライブラリ）・列・リスト項目の作成、ファイルアップロード、ページ作成、M365 グループ経由のサイト作成に対応。Microsoft Graph PowerShell の well-known パブリッククライアントで委任認証し、auth_helper.py のキャッシュを再利用する。

Build and query architecture-aware code search, dependency graphs, call flows, impact analysis, and belief maps for Python, TypeScript, TSX, Rust, C#, Java, Go, Ruby, and Ruby on Rails repositories. Use before non-trivial code changes to find module boundaries, blast radius, architecture violations, and the minimal source files to read.

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generate, refine, validate, and render diagrams from natural language, notes, code snippets, schemas, tables, or existing diagram source. use for flowcharts, swimlanes, sequence diagrams, state diagrams, er diagrams, class diagrams, architecture/c4-style diagrams, dependency graphs, gantt charts, mind maps, user journeys, sankey-style flows, org charts, network graphs, and other visual models. supports mermaid by default, graphviz dot for complex graph layout, plantuml for uml-heavy engineering diagrams, and svg output when direct markup is more reliable.

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Create text effects impossible with CSS alone — kinetic typography, flowing text around animated obstacles, calligrams, shrinkwrap chat bubbles, typographic ASCII art, glyph path animation, variable font waves, glyph morphing, illuminated manuscripts. Single-file HTML output, zero build step. Powered by @chenglou/pretext + opentype.js. Triggers on text effects, kinetic typography, text animation, calligram, glyph art, typography art.

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Generate cinematic case study pages for films, documentaries, photography portfolios, and creative projects — film-frame hero images, structured crew credit grids, dark footage galleries, festival award sections, scroll-choreographed reveals via data-attribute animation orchestration. Warm cream palette with analog typography. Single-file HTML, zero build step. Triggers on film case study, documentary showcase, filmmaker portfolio, production company website, film credits page, creative project case study, director portfolio, photography case study.

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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.

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Elite website image-to-code skill for Codex. For visually important web tasks, it must first generate the design image(s) itself, deeply analyze them, then implement the website to match them as closely as possible. In Codex, it must prefer large, readable, section-specific images instead of tiny compressed boards, generate fresh standalone images for sections or detail views instead of cropping old ones, avoid lazy under-generation, avoid cards-inside-cards-inside-cards UI, and keep the hero clean, spacious, readable, and visible on a small laptop.

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Guide for writing idiomatic Rust code based on Apollo GraphQL's best practices handbook. Use this skill when: (1) writing new Rust code or functions, (2) reviewing or refactoring existing Rust code, (3) deciding between borrowing vs cloning or ownership patterns, (4) implementing error handling with Result types, (5) optimizing Rust code for performance, (6) writing tests or documentation for Rust projects.

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How to use the coding agents installed on this machine (claude, codex, droid, grok, vktr, hermes, opencode, copilot, pi) as plain sub-agents in orchestrated workflows: one headless invocation, one prompt in, one result out. Deliberately ignores each CLI's own orchestration features (droid --mission, codex multi_agent, hermes delegation/moa/kanban, grok --agents, opencode personas). The orchestrator is whatever session is running the skill; the CLIs are interchangeable workers. Use when the user asks "which agent should run this", "fan out workers", "run X headless", or when a lifeos skill (overnight, timeboxed-iterating, workgraph, gauntlet, bughunt, dark-factory) needs to launch an agent CLI, or when a worker needs company context it should ask Viktor for (vktr).

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