Search 8,400+ AI and ML jobs across 489 companies, inspect listings and employers, match roles, and view salary and market stats via AI Dev Jobs MCP
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。
6,413 件 ・ 関連度順
概要と使いどころ
Search 8,400+ AI and ML jobs across 489 companies, inspect listings and employers, match roles, and view salary and market stats via AI Dev Jobs MCP
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。
Reference for MCP Jupyter tools (kernel management, cell execution, Papermill). Use when executing notebooks, managing kernels, or running code interactively via MCP.
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。
Iterate on a GenAI notebook against the self-hosted stack via the genai-stack CLI (config dirs, auth, subdomains, quantization, GPU/VRAM). Arguments: <notebook|service> [--service comfyui|forge|vllm] [--quant int4|fp8] [--validate] [--bg]
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 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。
Applies game theory to multi-agent coordination protocols with advisory claims, repeated interactions, daemon-mediated correlation, and deviation penalties. Use for Nash equilibrium checks, folk-theorem cooperation analysis, correlated-equilibrium routing, and price-of-anarchy audits in strategic agent systems. NOT for consumer pricing, card-game strategy, or general microeconomics outside agent coordination.
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 building Grafana dashboards backed by Prometheus, Loki, or Tempo, designing PromQL/LogQL queries, wiring template variables, setting alert rules, building SLO dashboards, or maintaining dashboards as code. Triggers: rate() vs increase() confusion, irate vs rate, label_replace, recording rules, alerting rule expressions, multi-dimensional template variables, ad-hoc filters, dashboard JSON model, provisioning via Terraform/grafonnet, p99 / histogram_quantile usage. NOT for Datadog/New Relic dashboards (vendor-specific), Grafana plugin development, or Loki ingestion pipeline tuning.
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。
Implementing distributed tracing with W3C Trace Context — the byte-precise `traceparent` and `tracestate` header formats, OpenTelemetry's W3CTraceContextPropagator as the modern default (replacing X-B3-* and X-Datadog-*), head vs tail sampling, and HTTP→SQL trace propagation via sqlcommenter. Grounded in the W3C REC and OpenTelemetry specs.
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。
Design and implement systematic checklists that reduce errors by 30-50% in complex, high-stakes domains (medicine, aviation, construction, finance). NOT for simple tasks or when comprehensive instruction is needed.
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。
Automatically intercepts and optimizes prompts using the prompt-learning MCP server. Learns from performance over time via embedding-indexed history. Uses APE, OPRO, DSPy patterns. Activate on "optimize prompt", "improve this prompt", "prompt engineering", or ANY complex task request. Requires prompt-learning MCP server. NOT for simple questions (just answer them), NOT for direct commands (just execute them), NOT for conversational responses (no optimization needed).
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 building content-heavy sites with Astro, deciding between SSG/SSR/hybrid, choosing client directives (idle/visible/load/media), structuring content collections with type-safe schemas, integrating React/Vue/Solid/Svelte components in the same project, or migrating from Next.js for marketing/docs. Triggers: client:idle vs client:load tradeoffs, content collections schema with zod, image optimization via @astrojs/image, view transitions, server islands, MDX layouts. NOT for SPA-style apps that need full interactivity (use Next/Remix), Astro internals/plugin authoring, or non-content sites where islands provide no benefit.
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。
Interact with the Binarly Transparency Platform (BTP) via CLI commands for uploading firmware, running scans, downloading BA2 archives, and pushing custom rules. Use when you need to interact with the Binarly Transparency Platform or working with BA2s.
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。
Persistent vector memory for Claude Code via LanceDB. Use when: remembering across sessions, storing lessons, recalling past decisions, maintaining context continuity. Tools: memory_store, memory_recall, memory_update, memory_forget, memory_merge.
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。
Deliberate system-improvement loop — audit your own Claude Code setup (rules / memory / skills / MCP / agents / registry), evaluate incoming tools via /vet, adopt the worthwhile ones with discipline (backup → verify), and record every decision. Use when bringing in a tool/idea/collection to improve the setup, or when doing a tooling-improvement pass. Triggers — "upgrade the workflow", "audit our setup", "let's improve the tooling", "evaluate this for us", when handed a post/repo/reel with a tool.
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。
Low-ceremony workflow for trivial, low-risk changes: typos, comments, CSS/styling tweaks, string changes, single-line fixes with no logic impact. Use to avoid the overhead of the full feature workflow when the change cannot break anything. If during the fix the change turns out to touch logic, security, config, or schema, stop and escalate to the feature-workflow 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。
Phased workflow for delivering a Drupal feature or non-trivial change: plan, implement, review, test, finalize. Use when building a new custom module, adding a route/form/plugin, changing entity structure or schema, or any task touching more than a couple of files. Do NOT use for typo fixes, CSS tweaks, or single-line changes — use the tiny-fix skill instead. Each phase has an exit condition; do not move to the next phase until it is met.
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。
Search, read, create, edit, and maintain knowledge in a Memex KB via the `mx` CLI. Use when the user asks to search the KB, find documentation, check project or organizational docs, add or update knowledge-base entries, audit KB quality, or when reusable knowledge should be captured for future agents.
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。
Trigger when: (1) the user mentions "manim", "scene", "video", "EN/KO render", "GEODE_HERO_LANG", "1080p60", or (2) editing files under `scripts/visualizations/` ending in `.py`, or (3) the user asks to render, re-render, or extend any of the four validated scenes (`geode_hero.py`, `autoresearch_filewalk.py`, `autoresearch_compare.py`, `critical_floor.py`). GEODE Manim Scene authoring standard. Locks the patterns the four validated scenes already share — Anthropic-style palette, Helvetica Neue + Pretendard font pairing with weight=NORMAL, EN/KO multilingual lang via `GEODE_HERO_LANG` env, `_dashed_arrow_with_head` stage-coupled tinting, `verify_hero_layout.py` ratchet — so the next scene does not re-discover the kerning / padding / transition regressions catalogued in [[viz-frame-audit]].
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。
Trigger when: (1) the user mentions "noise", "slop", "frame audit", "video review", "letter spacing", "padding intrusion", "frame extract", "naive arrow", or Korean equivalents (노이즈, slop, 프레임 검수, 글자 깨짐), or (2) after rendering a new or modified Manim scene, or (3) the user asks to review an mp4 in `media/videos/` or `~/Downloads/`. Post-render audit workflow for Manim 1080p60 videos. Extracts keyframes via ffmpeg, inspects them through Claude Code's Read tool, and classifies any defects into four standing categories (naive arrow / padding intrusion / glyph kerning drift / frame-order error). Catalogues 12+ verified incidents across the four GEODE scenes so each is caught the first time, not rediscovered. The companion authoring skill is [[manim-scene-craft]].
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。
Test-Driven Development workflow for Software Metrics Machine. Covers test frameworks (Vitest 4.x for CLI/REST/core/utils, Jest 30.x for webapp), test patterns (describe/it, builder pattern, mocks via vi.fn), test commands, coverage requirements, and the Red-Green-Refactor cycle. USE FOR: write tests, run tests, test this, add tests, testing, coverage, TDD, test-driven development, vitest, jest, test pattern, test convention. DO NOT USE FOR: linting (use lint skill), building (use build commands directly), debugging production 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。
Decompose an approved implementation plan into self-contained Linear issues with zero guesswork. Use when breaking down a plan into actionable Linear tasks via the MCP server.
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。
GitLab workflow automation with the glab CLI — merge requests, issues, CI, releases, and safe message escaping. Auth via GITLAB_TOKEN (set in global settings, attached to the sandbox env).
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。
Deterministic AI development workflow orchestrator. Manages task boards (.jonggrang/jonggrang-tasks.json), runs 16-phase pipelines (BUGFIX/SMALL/MEDIUM/LARGE), installs lifecycle hooks for Claude Code and OpenCode, and coordinates five specialist roles (Lead/Developer/Reviewer/TestLead/Tester). Use when planning features, executing multi-step development workflows, or orchestrating AI coding agents. Run via npx jonggrang.
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。
GitHub workflow automation with the gh CLI — pull requests, issues, releases, the REST/GraphQL API, and safe message escaping. Auth via GH_TOKEN (set in global settings, attached to the sandbox env).
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。
Corrects fluorophore spillover (conventional compensation) or spectral overlap (spectral unmixing) and applies variance-stabilizing transforms (logicle/biexponential, arcsinh, log) for flow and mass cytometry. Covers spillover-matrix estimation from single-stain controls, AutoSpill, the spillover spreading matrix and why panel design (not compensation) bounds resolution, compensate-then-transform ordering, and arcsinh cofactor choice (5 for CyTOF, ~150 for fluorescence, per-channel via flowVS). Use when correcting spectral overlap, preparing data for gating/clustering, choosing logicle vs arcsinh, deciding a cofactor, or distinguishing compensation from spectral unmixing.
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。