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cccskills

「node」の検索結果

1,333 件 ・ 関連度順

概要と使いどころ

Discovery, download, and configuration hub for the entire aelf agent skill ecosystem. Use when the user wants to: (1) explore or list available aelf skills, (2) install/bootstrap aelf skills into Cursor, Claude Desktop, OpenClaw, Codex, or Claude Code, (3) route an aelf-related intent to the correct skill, (4) check health or audit installed skills, (5) onboard a new skill into the aelf ecosystem. Covers domains: Portkey CA wallet, Portkey EOA wallet, Awaken DEX, eForest NFT marketplace, AelfScan explorer, TomorrowDAO governance, aelf node interaction.

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。

modbender/skill-library-mcp162026年9月28日 更新

Query and manage personal finances via the official Actual Budget Node.js API. Use for budget queries, transaction imports/exports, account management, categorization, rules, schedules, and bank sync with self-hosted Actual Budget instances.

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。

modbender/skill-library-mcp162026年9月28日 更新

Use ActivityWatch to analyze user's computer activity (Requires Node.js)

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。

modbender/skill-library-mcp162026年9月28日 更新

Validate the GenAI stack (services, authentication, models, notebooks, GPU). Arguments: [all|services|auth|models|notebooks|vram] [--full] [--auth-only] [--nodes-only] [--notebooks]

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。

jsboige/CoursIA162026年10月14日 更新

Appwrite TypeScript SDK skill. Use when building browser-based JavaScript/TypeScript apps, React Native mobile apps, or server-side Node.js/Deno backends with Appwrite. Covers client-side auth (email, OAuth, anonymous), database queries, file uploads, real-time subscriptions, and server-side admin via API keys for user management, database administration, storage, and functions.

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。

appwrite/cursor-plugin152026年7月27日 更新

Production-grade error handling for Node.js/TypeScript backends. Error classes, HTTP mapping, logging, retry strategies.

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。

porcupine-md/jonggrang152026年9月15日 更新

当您的律师协会来问"给我看看您是如何为 AI 辅助工作计费的"——而 ABA 512、佛罗里达 24-1、加利福尼亚、纽约和哥伦比亚特区都已发布意见——您需要一个经得起审查的工件。billable-time 就能产生它。 从您的 Claude Code 会话日志中,它起草可审查的计时条目,外加可打印的 HTML 审计包,包括:SHA-256 证据链(源文件 + matter.yml + 活动披露包 + 可验证工件自哈希)、律师身份和签名块、包含五个法域起始语言的律师协会意见披露包,以及由文件名和工具形态导出的、内容感知的确定性叙述——默认绝不来自提示文本。 该工具拒绝自行计费。--strict 模式在任何审计不变式失败(宽泛路径、缺少律师、缺失/未核验披露)时拒绝交付工件。提供 Node CLI 和自包含浏览器版本(无后端;JSONL 绝不离开页面)。15 个不变式测试验证该契约。AGPL-3.0。

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。

CSlawyer1985/legal-skillhub152026年9月23日 更新

Use this skill whenever the user asks to generate, edit, inpaint, restyle, or create bitmap images through OpenAI's Responses API image_generation tool from Codex. This skill calls the Responses API, saves generated base64 image results to files, uses no npm or pip dependencies, works on Linux/macOS/Windows with either Node.js 18+ or Python 3, and reuses Codex's configured API base URL, model, and key instead of asking the user for credentials.

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。

Amamiya23/custom_image_generation152026年7月2日 更新

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

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。

susomejias/rembric142026年10月13日 更新

Use when building APIs on Hono (Cloudflare Workers, Bun, Deno, Node), debugging route ordering, wiring middleware, validating with @hono/zod-validator, returning streaming responses, configuring CORS with credentials, handling errors via app.onError, or composing typed RPC clients. Triggers: c.env binding types, c.header + c.redirect interaction, missing await next() bugs, Set-Cookie not attaching to redirect, route-precedence surprises, JWT middleware setup, hono/client typed RPC end-to-end. NOT for Express/Fastify/Koa idioms, tRPC/GraphQL paradigms, or Next.js Route Handlers.

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。

curiositech/windags-skills142026年10月12日 更新

Matches natural language task descriptions to appropriate skills using semantic similarity, ranks candidates by fit and performance history, and maintains the skill catalog. Use when assigning skills to DAG nodes, searching for the right skill for a task, ranking competing skills, or browsing the skill catalog. Activate on "find skill", "match skill", "which skill", "skill for this task", "skill catalog", "rank skills", "best skill". NOT for executing DAGs (use dag-runtime), creating skills (use skill-architect), or grading skills (use skill-grader).

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。

curiositech/windags-skills142026年10月12日 更新

Decompose DAGs into execution chains using width bounds, stratification, virtual nodes, and matching. Use when minimizing workflow lanes in dependency graphs. NOT for cyclic graphs, generic scheduling, or one-off queries with no preprocessing payoff.

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。

curiositech/windags-skills142026年10月12日 更新

Validates agent outputs against schemas and quality criteria, scores confidence, detects hallucinations, monitors convergence, decides when to iterate, and synthesizes actionable feedback. Use when checking if a node's output is acceptable, scoring confidence, detecting fabricated content, deciding whether to re-execute, or generating improvement feedback. Activate on "validate output", "check quality", "confidence score", "hallucination check", "should we iterate", "improvement feedback". NOT for executing DAGs (use dag-runtime), planning DAGs (use dag-planner), or matching skills (use dag-skills-matcher).

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。

curiositech/windags-skills142026年10月12日 更新

Analyze hierarchical DAG-like systems by separating undirected substrate from ordering metadata, then classifying diamonds, mixers, shortcuts, and hidden cycle structure. Use for workflow architecture, citation or genealogy DAG comparison, and information-flow diagnosis. NOT for ordinary cycle detection in arbitrary graphs, one-node runtime debugging, or systems with no real ordering constraint.

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。

curiositech/windags-skills142026年10月12日 更新

Manages context passing between DAG nodes and spawned agents. Handles context summarization, selective forwarding, and token budget optimization. Activate on 'bridge context', 'pass context', 'summarize context', 'context management', 'agent context'. NOT for execution (use dag-parallel-executor) or aggregation (use dag-result-aggregator).

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。

curiositech/windags-skills142026年10月12日 更新

The intelligence layer of WinDAGs. Decomposes natural language tasks into Hierarchical Task DAGs (HTDAGs), matches subtasks to skills, executes waves in parallel, and dynamically expands nodes when complexity exceeds executor capability. Use for 'orchestrate', 'execute DAG', 'parallel agents', 'decompose task', 'coordinate skills'. NOT for single-skill tasks or simple linear 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。

curiositech/windags-skills142026年10月12日 更新

Tracks cumulative LLM costs across DAG execution and makes real-time decisions to stay within budget. Downgrades models, skips optional nodes, or stops early when cost exceeds thresholds. Use when managing execution budgets, analyzing cost breakdowns, or optimizing model routing for cost. Activate on "cost budget", "too expensive", "reduce cost", "cost optimization", "model downgrade", "budget exceeded". NOT for LLM model selection logic (use llm-router), pricing comparisons across providers, or billing/invoicing.

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。

curiositech/windags-skills142026年10月12日 更新

Choose, compare, and decompose work into the right coordination topology: dag, workflow, manager-driven team, swarm, blackboard, team-builder, or recurring loop. Use when the coordination shape is unclear, when you need topology-native breakdown instructions instead of a generic DAG, or when planning topology and runtime topology may differ. NOT for actual execution, node-level skill matching, or framework/tool installation.

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。

curiositech/windags-skills142026年10月12日 更新

Traces complete execution paths through DAG workflows. Records timing, inputs, outputs, and state transitions for all nodes. Activate on 'execution trace', 'trace execution', 'execution path', 'debug execution', 'execution log'. NOT for performance analysis (use dag-performance-profiler) or failure investigation (use dag-failure-analyzer).

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。

curiositech/windags-skills142026年10月12日 更新

dag-ops

無料

Operations, debugging, and optimization for DAG workflows. Performs root cause analysis on failures, profiles execution performance, aggregates results from parallel branches, bridges context between nodes, and learns patterns from execution history. Activate on "DAG failed", "why did it fail", "root cause", "performance profile", "aggregate results", "merge branches", "execution patterns", "optimize DAG". NOT for planning DAGs (use dag-planner), executing DAGs (use dag-runtime), or validating outputs (use dag-quality).

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。

curiositech/windags-skills142026年10月12日 更新

Parses complex problems into DAG (Directed Acyclic Graph) execution structures. Decomposes tasks into nodes with dependencies, identifies parallelization opportunities, and creates optimal execution plans. Activate on 'build dag', 'create workflow graph', 'decompose task', 'execution graph', 'task graph'. NOT for simple linear tasks or when an existing DAG structure is provided.

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。

curiositech/windags-skills142026年10月12日 更新

Expert in 2000s-era music visualization (Milkdrop, AVS, Geiss) and modern WebGL implementations. Specializes in Butterchurn integration, Web Audio API AnalyserNode FFT data, GLSL shaders for audio-reactive visuals, and psychedelic generative art. Activate on "Milkdrop", "music visualization", "WebGL visualizer", "Butterchurn", "audio reactive", "FFT visualization", "spectrum analyzer". NOT for simple bar charts/waveforms (use basic canvas), video editing, or non-audio visuals.

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。

curiositech/windags-skills142026年10月12日 更新

Reconstruct ancestral states at internal phylogenetic nodes for sequences (PAML codeml, IQ-TREE --ancestral, GRASP, FastML), discrete traits (corHMM hidden-rate Markov, ape::ace, phytools::make.simmap stochastic mapping, BayesTraits), and continuous traits (phytools::fastAnc, geiger Brownian/OU, RPANDA). Use when designing constructs for ancestral protein resurrection, tracing trait evolution along a tree, performing stochastic character mapping, testing models of trait evolution (BM vs OU vs EB), inferring ancestral genome content via Dollo or DTL reconciliation, or quantifying ancestral-state uncertainty for downstream comparative analyses.

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。

lilinji/GeneTind-Life-Skills142026年8月21日 更新

This skill recommends localizing and resecting ectopic ACTH-secreting tumors with node dissection when ectopic ACTH secretion is suspected or confirmed. Clinical triggers include unexplained persistent hypercortisolism after pituitary surgery, elevated ACTH with negative pituitary MRI, or identification of occult ectopic ACTH syndrome (EAS) on biochemical testing.

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。

dromlakhani/MD2SKILL142026年10月5日 更新