「stream」の検索結果

Applies general coding standards and best practices for Kafka development with Scala.

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。

Orchestrate multi-agent Claude Code teams with Minoan-Semitic naming — auto-discover project context (CLAUDE.md, roadmaps, plans, issues) and generate named team configurations with structured task lists and file ownership. Triggers on parallel workstreams, agent teams, multi-agent, spawn agents, swarm, minoan-swarm.

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。

Research UI component patterns across the component.gallery corpus — 60 canonical component types, ~95 production design systems, 2,600+ examples — plus an AI-era overlay (prompt inputs, tool-call cards, streaming status, citations) and composite patterns (command palette, app shell, agent console). Compare implementations, find alternative component names, ground frontend decisions in real-world precedent. Pairs with minoan-frontend-design for research-then-build workflows. Triggers on component patterns, how do others implement X, design system research, component comparison, AI chat components, agent UI 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。

Deploy, diff, bootstrap, inspect, roll back, or destroy AWS CDK applications with the community CDKD CLI while preserving safe production and state-management boundaries. Use when the user mentions cdkd or CDK Direct, asks for faster CDK deployments in development or test environments, or wants to evaluate whether an existing CDK app can use CDKD. Also use for CDKD import, export, state, events, and deployment troubleshooting. Prefer the upstream AWS CDK CLI for production and for existing CloudFormation-managed stacks unless the user explicitly approves a management migration.

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。

Produces structured markdown session continuation documents for multi-session workflows. Captures active work streams, decisions with rationale, knowledge-file deltas learned during the session, the exact files to load next conversation, ingested content, artifacts, and open items into an ingestion-optimized handoff. Carries pending KF updates and unresolved items forward across handoff chains so context never drops. Generates a closeout checklist and echoes the starter prompt to chat. Use when approaching context limits, wrapping up a session, or managing work across conversations. Trigger on: "create a handoff," "session closeout," "wrap up this session," "build session handoff," "BSH," "continue next session," "we're running out of context," "context is getting long." Do NOT use for Memory optimization, context budget analysis, project audits, deciding whether work is ready for autonomous/Claude Code execution (use rootnode-handoff-trigger-check), or summaries with no continuation intent.

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。

Protein language models through the EvolutionaryScale `esm` Python SDK. Generate and embed sequences with ESM3 (multimodal sequence, structure and function prompting), extract per-residue and mean-pooled embeddings with ESM C, fold sequences with ESMFold2, and run inference locally or against the Forge and Biohub hosted clients. Use this skill for protein representation learning, variant effect and mutational scanning from likelihoods, sequence generation and inpainting, structure prediction from sequence alone, and embedding features for downstream models. Also trigger on esm, ESM3, ESMC, ESM Cambrian, ESMFold2, `from esm.models`, ESMProtein, GenerationConfig, forge.evolutionaryscale.ai, biohub.ai, or ESM_API_KEY.

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 B2B SaaS product needs upstream positioning or messaging clarity — defining who it's for, the category, competitive alternatives, differentiation, value props, strategic narrative, or a messaging hierarchy. Triggers include "my messaging isn't working," "we sound like everyone else," repositioning, or auditing an existing positioning doc. Use before homepage, deck, or sales-narrative work. Not for writing the final copy (use copywriter-skill) or running the sales process (use sales-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。

Use when the user is working a B2B SaaS deal from qualified opportunity to closed-won — preparing discovery calls, structuring demos or POCs, handling a specific objection, qualifying with MEDDIC/MEDDPICC/SPICED, building mutual action plans, navigating negotiation or procurement, or reviewing pipeline health, forecast accuracy, and deal velocity. Not for finding or prospecting new leads (use prospecting) or upstream positioning (use product-position).

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。

Redact reverse-engineering findings for public disclosure while preserving methodology, generalizable patterns, and teaching value. Covers the private-vs-public repo split, deny-list pattern maintenance, orphan-commit publish pattern that prevents `git log` leaks, category-based redaction calibration (methodology/pattern/version-finding/internal), and the `check-redaction.sh`-style CI gate that blocks merges when a deny-listed pattern appears. Use when publishing findings about a CLI harness you don't own, when preparing upstream proposals to an unrelated project, or when archiving a private research repo for public reference.

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, track, switch, sync, and clean up Git branches. Covers naming conventions, safe branch switching with stash, upstream synchronization, and pruning merged branches. Use when starting work on a new feature or bug fix, switching between tasks on different branches, keeping a feature branch up to date with main, or cleaning up branches after merging pull requests.

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。

Install and configure the putior R package for workflow visualization. Covers CRAN and GitHub installation, optional dependencies (mcptools, ellmer, shiny, shinyAce, logger, plumber2), and verification of the complete annotation-to-diagram pipeline. Use when setting up putior for the first time, preparing a machine for workflow visualization tasks, when a downstream skill requires putior to be installed, or restoring an environment after an R version upgrade or renv wipe.

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。

Configure Nginx as a web server and reverse proxy. Covers static file serving, reverse proxy to upstream services, SSL/TLS termination with Let's Encrypt, location blocks, load balancing, rate limiting, and security headers. Use when serving static files in production, reverse proxying to backend services (Node.js, Python, R/Shiny), terminating SSL/TLS, load balancing across instances, or adding rate limiting and security headers to harden an endpoint.

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。

Deploy and configure an API gateway (Kong or Traefik) to handle API traffic management, authentication, rate limiting, request/response transformation, and routing. Covers plugin configuration, upstream services, consumer management, and integration with existing infrastructure. Use when multiple backend services need a unified API endpoint, when centralized authentication or rate limiting is required, when implementing API versioning, or when needing detailed analytics and load balancing for microservices.

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。

Data fetching, caching, and revalidation patterns in Next.js App Router. Covers native fetch caching, ISR/SSG/SSR per-route choice, generateStaticParams, unstable_cache, revalidatePath/revalidateTag, Route Handlers, dynamic vs static rendering. Use this skill to: - Pick the right rendering mode (SSG / ISR / SSR / streaming) per route. - Use native fetch caching options correctly. - Build Route Handlers that match REST conventions. - Invalidate cached data after mutations. - Use generateStaticParams for dynamic SSG. Do NOT use this skill for: - RSC vs Client boundaries (see server-component-patterns). - Routing primitives (see nextjs-routing). - General conventions (see nextjs-conventions).

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。

Orchestrate complex development with AUTOMATIC parallel subagent execution, continuous dispatch scheduling, dependency analysis, file conflict detection, and IOSM quality gates. Analyzes task dependencies, builds critical path, launches parallel background workers with lock management, monitors progress, auto-spawns from discoveries. Use for multi-file features, parallel implementation streams, automated task decomposition, brownfield refactoring, or when user mentions "parallel agents", "orchestrate", "swarm", "continuous dispatch", "automatic scheduling", "PRD", "quality gates", "decompose work", "Mixed/brownfield".

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 writing CUDA kernels, managing the thread, block, and grid hierarchy, tiling shared memory, using streams, setting nvcc flags, or using Thrust. Not for kernel debugging: use cuda-debugging.

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 configuring ADC sampling time, DMA-driven ADC, calibration, or DAC channel setup on bare-metal MCUs. Not for the DMA stream itself: use dma-baremetal.

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。

Define release scope and move backlog workstreams between release targets.

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 grounded Radar backlog workstreams.

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。

Recover from stale RFDB nodes that survive `commit_batch` cleanup despite having their `file` field listed in `changed_files`. Use when: (1) re-running an enricher/orchestrator step but old data with the same file field stays in the graph, (2) `commit_batch(changed_files=[X], ...)` reports success but a query later still returns nodes with `file = X`, (3) you re-pointed structural nodes (e.g., DIRECTORY/FILE) from a synthetic file path to real file paths and the old synthetic-path nodes won't go away, (4) graph-stream / find_by_type returns a mix of "stale" and "new" nodes for the same logical entity. Root cause: `handle_commit_batch` calls `engine.find_by_attr({file: X})` to enumerate nodes-to-delete, but that query path returns only a PARTIAL set after compaction (L1 segments and the file→nodes index can desync). Workaround: enumerate stale nodes via the TS rfdb client `queryNodes({file: X})` (different code path that finds all of them) and call `deleteNode(id)` per node, then re-commit the intended state. Related: rfdb-manifest-l1-carryforward (same L1 family).

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。

Troubleshoot and resolve common issues with the ClickHouse Node.js client (@clickhouse/client). Use this skill whenever a user reports errors, unexpected behavior, or configuration questions involving the Node.js client specifically - including socket hang-up errors, Keep-Alive problems, stream handling issues, data type mismatches, read-only user restrictions, proxy/TLS setup problems, or long-running query timeouts. Trigger even when the user hasn't precisely named the issue; vague symptoms like "my inserts keep failing" or "connection drops randomly" in a Node.js context are strong signals to use this skill. Do NOT use for browser/Web client issues.

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。

Prepare outstanding commits on a feature branch for a pull request to upstream

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 Ascend NPU schedule, operator dispatch, operator launch, and Host Bound profiling issues in Ascend profiling data. Use when need to diagnose device Free time, framework/operator dispatch latency, launch latency, PYTORCH_API/CANN_API launch gaps, aclrtSynchronizeStream stalls, task queue behavior, CPU scheduling interference, GC/lock pauses, CPU affinity, or schedule-side optimization actions.

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 Ascend NPU computation-side profiling data for single-card runs or a selected rank from multi-card runs. Use this skill when the user asks to diagnose computation bottlenecks, AI Core / AI Vector / AICPU hotspots, dynamic shape overhead, block dim issues, redundant TransData/Transpose/Cast, cross-stream waits, frequency/runtime-state issues, or fusion opportunities.

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。