「code graph」の検索結果

Make kinetic-typography motion reels (MP4) in code: showreels, portfolio or work reels, product promos, intro films, "motion design"-style videos with bold condensed type, HUD micro-type, black/cream/lime palette, three.js generative layers (particle terrain, liquid marble, chrome knot, particle clouds), shape-continuity transitions and a synthesized, beat-locked score. Canvas 2D + WebGL rendered frame by frame in headless Chrome, encoded with ffmpeg. Use when the user asks for a reel, showreel, motion-graphics / kinetic-type video, a "Work Reel" in this style, or to extend/re-cut the Work Reel ’26.

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。

Authoritative reference for the neo4j-agent-memory Python package — a graph-native memory system for AI agents built on Neo4j — and for the hosted service (NAMS) at memory.neo4jlabs.com. Use this skill whenever the user mentions neo4j-agent-memory, agent memory with Neo4j, context graphs, the POLE+O model, MemoryClient/MemorySettings, the memory MCP server, or any of the framework integrations (LangChain, PydanticAI, CrewAI, AWS Strands, Google ADK, Microsoft Agent Framework, OpenAI Agents, LlamaIndex). Also use when the user mentions the hosted service at memory.neo4jlabs.com, NAMS, the Neo4j Agent Memory Service, the `nams_` API key prefix, or the hosted MCP endpoint. Also use when writing documentation, blog posts, tutorials, PRDs, or code samples for the project, when comparing agent memory approaches, or when positioning graph-native memory against vector-only approaches — even if the user doesn't explicitly name the package.

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

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 for architecture review, dependency graphs, coupling analysis, or circular dependency detection. Establishes project module namespaces and traces imports plus Claude plugin hook, skill, script, PEP 723, and MCP boundaries. Emits partitioned Mermaid graphs with cycle, coupling, and ownership signals; verifies contract and consequence before assigning severity. Registers diagrams as codebase-analysis artifacts.

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 whenever the user wants to find, shortlist, vet, or enrich US software development firms — custom software, web development, mobile app development, backend/API development, DevOps/cloud, system integration, and hosting. Triggers on "find a software dev shop in Austin", "shortlist three custom-software firms with healthcare experience", "we need a mobile app developer for our iOS launch", or "pull contact info for these 10 dev shop domains", even when described indirectly (build a tool, ship a feature, technical partner). Drives the ServiceGraph API (api.servicegraph.co) — a 100k+ US firm catalog filterable by industry, services, location, size, ratings. Defer to find-web-developer for strictly website/landing-page projects. Defer AI/ML, ML pipelines, model building, and data-engineering asks — those are a sibling industry, not software development. Skip in-house engineer hires, code-writing/debugging tasks, cloud-product comparisons, hardware/civil engineering, non-US firms, individual freelancers.

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 — routes to Skeleton Index, CodeGraph, Architecture Diagram, or Smart Context Builder based on task shape. Loads deep refs on demand.

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 asking whether something in imp is actually finished - hunting stubs, placeholders, request fields that are parsed and then ignored, code paths or kernels that never run, gate-based features that silently no-op, tests that assert nothing. Triggers on "is this implemented", "unfinished", "stub", "placeholder", "dead path", "does this flag do anything", "accepted but ignored", "kernel never launched", "test asserts nothing", "neutral A/B on a gated feature". Do NOT use for structural debt / god files / duplication (codebase-audit) or for who-calls-what (code-graph).

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 a repository's type system and generate type-safe DAG execution pipelines with GraphSentry-style certificate verification. This skill should be used when building LLM-driven workflows that need deterministic type safety, when composing typed operations into validated execution graphs, or when adding contract-checked pipeline orchestration to any codebase. Supports Python (Pydantic) and TypeScript (Zod).

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。

GraphQL, WebSockets, and microservices patterns for NestJS. Apply only when the relevant package is in dependencies (`@nestjs/graphql`, `@nestjs/websockets`, `@nestjs/microservices`). Each section is orientation, not exhaustive — defer to NestJS docs for deep dives. Use this skill to: - Wire a GraphQL resolver (code-first) with class-validator inputs. - Build a WebSocket gateway with auth and room management. - Set up a microservice transport (TCP/RabbitMQ/NATS/Redis/Kafka) and message handlers. Do NOT use this skill for: - REST controllers (see nest-conventions + decorator-patterns). - ORM (see nest-data-layer). - Auth strategies (see security-analyst phase guidance).

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 needs to search or navigate code with Sourcegraph MCP tools. Provides disciplined search workflows for finding implementations, understanding systems, debugging issues, fixing bugs, and reviewing code.

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。

Review owned or authorized code for security using structure-first evidence: AST/structure maps, call graphs, complexity, Source/Sink flow, and defensive findings. Use when asked for security review, vulnerability review, AST structure map review, SAST triage, Source/Sink, taint flow, parser/scanner hardening, CI/CD security, LLM/agent tool boundary review, 脆弱性レビュー, 構造マップ, セキュリティレビュー.

Deep API security assessment beyond surface scanning. Covers the full OWASP API Security Top 10 (2023): Broken Object Level Authorization (BOLA / IDOR), Broken Authentication, Broken Object Property Level Authorization (mass assignment + excessive data exposure), Unrestricted Resource Consumption, Broken Function Level Authorization (BFLA / vertical privilege escalation), Unrestricted Access to Sensitive Business Flows, Server-Side Request Forgery via API parameters, Security Misconfiguration, Improper Inventory Management (shadow/zombie/deprecated endpoints, v1/v2 drift), and Unsafe Consumption of third-party APIs. Works across REST, GraphQL, gRPC, SOAP, and MCP servers. Discovers APIs from OpenAPI/Swagger specs, GraphQL introspection, gRPC reflection, .well-known endpoints, JS bundles, and traffic capture. Uses kiterunner, ffuf, schemathesis, restler-fuzzer, openapi-fuzzer, graphql-cop, clairvoyance, batchql, inql, jwt_tool, postman, mitmproxy, and manual http(action="request", ...) payloads. Every technique includes actual payloads, commands, and verification logic. Chains from /pentester or /codebase when API endpoints are discovered, chains into /web-exploit when classic injection points are found in API parameters, chains into /post-exploit when RCE is achieved, and chains into /ai-redteam when an LLM/AI endpoint is discovered (chat APIs, completion endpoints, RAG search, agentic tool-use, MCP servers).

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。

Reviews Web Audio API JavaScript/TypeScript code for correctness, thread safety, and deprecated patterns. Use when the user asks to review AudioWorklet code, check an AudioWorkletProcessor, audit Web Audio graph construction, or diagnose crackling/dropouts in a web audio app. Trigger on phrases like "review my Web Audio code", "check my AudioWorklet", "is my AudioWorkletProcessor safe", or "why does my web audio crackle".

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。

Serena code intelligence — LSP-powered symbol navigation, diagnostics, and targeted code surgery. Activate before complex refactors, cross-file analysis, or when graph tools need symbol-level depth.

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。

Crystal structure fundamentals — lattices, space groups, Miller indices, and reading crystallographic data correctly.

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 and functional brain connectivity — tractography, functional networks, and graph-theoretic 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。

Improve an existing agent SKILL.md through one gated cycle: select the target (default this skill), snapshot the committed baseline, diagnose against skill-design-principles plus four rubric dimensions, apply exactly one focused change, and ship only if a different agent than the author PASSes with quoted evidence. Use when the user says "improve this skill", "improve-skill", "iterate on SKILL.md", or "apply skill-design-principles to a skill". Do not use for code slop over a duration (anneal), generic timeboxed work (timeboxed-iterating), graph orchestration (workgraph), metric hill-climb on a codebase (autoresearch), or stripping slop from existing prose (catalog-deslop).

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 the Skmtc CLI to scaffold projects, install or clone generators from JSR, configure schema sources and enrichments, and produce code artifacts from an OpenAPI v3 or GraphQL SDL schema. Teaches the workspace mental model (`<root>/.skmtc/<project>/`, client.json, bundle, manifest) and the agent contract (strict text / strict JSON modes, exit codes, recipe errors, `agent-context` + `doctor`); the command surface itself is discovered from the binary — `skmtc --help`, `skmtc <cmd> -h` — rather than carried in this skill. Use this skill when the user asks to "run skmtc", "generate code from an OpenAPI schema", "install a skmtc generator", "scaffold a skmtc project", "watch a skmtc project", "configure enrichments", "publish a stack", "deploy to skmtc-hub" (the command is `publish`; there is no `deploy`), "skmtc in CI", or invokes any CLI subcommand. For *authoring* a generator package (Projections, Snippets, transform functions), defer to `skmtc-generator`. When something is broken (no output, wrong output, error messages, a failed bundle build), verify before proposing a fix: read the manifest and the parse issues, and reproduce the failure first.

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] Use when you need to build, update, or sync the code review knowledge graph. Flag: --scope={full|update|sync} (default auto-detect); --scope=full forces a full rebuild, --scope=update re-parses uncommitted working-tree changes, --scope=sync syncs committed git changes then updates the working tree.

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] Use when you need to analyze the blast radius of current code changes using the structural knowledge graph.

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] Use when you need to query code relationships and connections using the structural knowledge graph.

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。

Add tree-sitter language support to codegraph end-to-end — wire the grammar + extractor, write tests, then benchmark extraction quality and retrieval value on 3 popular real-world repos. Use when the user runs /add-lang <language> or asks to add/support a new language (e.g. Lua, Elixir, Zig, OCaml) in codegraph.

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。

Validate Commodore MPS-801 serial dot matrix printer behavior in EMULATORS, including SerialPrinterMPS801 classes and their MatrixPrinterEmulation and SerialPrinterPeripheralSimulation hierarchy, IEC/KERNAL-trap printer routing, device numbers, secondary addresses, PETSCII/character sets, 6x7 glyphs, double width, graphics mode, reverse field, tab and dot positioning, line/page geometry, PostScript output, and fidelity boundaries. Use when Codex reviews or edits COMMODORE MPS801 printer code, generated printer output, PostScript printer templates, C64/VIC-20/C264 serial-printer behavior, or compares implementation against .codex/docs/MPS801.pdf and historical MPS-801 sources.

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。

Load when asked where code lives, how modules relate, what calls a symbol, what implements a feature, or for an architecture/codebase tour using the knowledge graph; not for bug diagnosis, diff review, or refactoring.

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。