「coding」の検索結果

Prepare a Datagrok package so that Claude (or any coding agent) can work on it effectively from a naive prompt

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。

Find, describe, add, remove, rename, clone, or set metadata on columns of a Datagrok DataFrame via the datagrok_exec tool. Use whenever the user asks to locate "the X column", summarize a column, add a typed/empty/values-filled/virtual column, set semantic type / units / format / friendly name, apply linear or categorical or conditional color coding, drop or rename columns, or copy a DataFrame. Covers everything in DataFrame.columns and Column.meta — but not row filtering/selection (datagrok-filtering, datagrok-selection) and not formula-only columns (datagrok-calc-column).

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。

Comprehensive markdown planning methodology for software projects. Use when starting a new project, creating implementation plans, or refining architecture before coding.

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。

CASS Memory System - procedural memory for AI coding agents. Three-layer cognitive architecture with confidence decay, anti-pattern learning, cross-agent knowledge transfer, trauma guard safety system. Bun/TypeScript CLI.

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。

Manage AI coding CLI accounts with sub-100ms switching. Use when hitting rate limits on Claude Max, GPT Pro, or Gemini Ultra subscriptions and need instant account swapping without browser OAuth.

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。

FFmpeg media processing — video/audio conversion, trimming, encoding, filters, streaming. CLI and ffmpeg.wasm 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。

Design and analysis of combinational and sequential digital circuits using Boolean algebra, truth tables, K-maps, CMOS gate implementation, flip-flops, registers, counters, and finite state machines. Covers De Morgan's theorems, canonical sum-of-products and product-of-sums forms, minimization techniques, propagation delay, setup and hold times, metastability, synchronous design discipline, and FSM encoding. Use when designing, minimizing, verifying, or debugging any circuit whose signals take only discrete logic values.

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。

Distributed storage systems design and operation for cloud platforms. Covers the GFS/HDFS block-and-master pattern, object storage (Swift/S3) with consistent hashing and eventual consistency, block storage semantics, replication vs erasure coding, the CAP theorem in practice, read-repair and anti-entropy, snapshot chains, and the GFS/BigTable/Spanner evolution. Use when designing a storage subsystem, choosing between object/block/file, or reviewing a replication and consistency strategy.

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。

Produce animated source control visualizations using Gource. This skill handles installation of Gource and ffmpeg, detection of repository metrics, preset-based configuration, single and multi-repo log generation, ffmpeg video encoding pipeline, headless rendering for server environments, caption generation from git tags, GitHub avatar resolution, and GSD output delivery. Use this skill whenever the user wants to visualize repository history, create a code evolution video, see project timeline animations, generate Gource videos, combine multiple repos into one visualization, or produce any kind of source control visualization. Also trigger when the user mentions "Gource", "repo visualization", "code history video", "project evolution animation", or asks to "show me what we built".

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。

Audit code changes against Karpathy's 4 principles (Think Before Coding, Simplicity First, Surgical Changes, Goal-Driven Execution). Auto-called after Phase 5 IMPLEMENT; can also be invoked manually. Produces scored compliance report and blocks advancement if threshold not 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。

Survey the AI coding assistant and agentic tool ecosystem, assess skillsaw's competitive position, identify emerging patterns and missing capabilities, and produce a prioritized strategic report as a GitHub issue. Use when evaluating ecosystem trends and product gaps.

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。

Audits GitHub Actions workflows for security vulnerabilities in AI agent integrations including Claude Code Action, Gemini CLI, OpenAI Codex, and GitHub AI Inference. Detects attack vectors where attacker-controlled input reaches AI agents running in CI/CD pipelines, including env var intermediary patterns, direct expression injection, dangerous sandbox configurations, and wildcard user allowlists. Use when reviewing workflow files that invoke AI coding agents, auditing CI/CD pipeline security for prompt injection risks, or evaluating agentic action configurations.

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。

Atlas of Agent Client Protocol (ACP) clients, agents, and OCapN/CapTP-grounded actors. Use when picking a coding agent surface, threading ACP over CapTP, locating the local Zoad implementation, or navigating the Hermes-as-OCapN-actor 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。

Bridge active inference theory with robot control using K-Scale's JAX/MuJoCo stack. Use when connecting predictive coding to locomotion policies, mapping KL divergence minimization to RL training, applying mean field approximation to robotics state estimation, or implementing sim2real as inference about future observations.

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。

Cross-platform hooks reference for AI coding assistants — Claude Code, OpenAI Codex, GitHub Copilot, Cursor, Windsurf, and Amp. Covers hook authoring in Node.js (ESM and CJS) and Python, per-platform event schemas, inline-agent hooks and MCP in agent frontmatter, common JSON I/O, exit codes, best practices, and a fetch script to refresh docs from official sources. Use when writing, reviewing, or debugging hooks for any AI assistant.

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, validate, and diagnose Claude Code output styles — the file that sets Claude's role, tone, and response format for every turn. Use when asked to write, bundle, or force an output style for a plugin, to set keep-coding-instructions or force-for-plugin, when a style is not taking effect or the wrong one applies, or when choosing between an output style, CLAUDE.md, a skill, and an agent for a persistent behavior change.

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。

Local codebase analysis research angle — derives behavioral contracts, coding conventions, SKILL.md flow insertion points, and agent data availability maps from actual source files. Use when the blocking question is answered by reading the repository: what does this function actually do, what pattern does the codebase use for X, where in this workflow does a new step go, or what data does this agent already have.

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。

Badge design and selection knowledge base for shields.io badges in README files. Use when writing or updating READMEs, choosing badge layouts, selecting badge styles, adding project health indicators, or picking Simple Icons logo slugs. Covers shields.io URL encoding rules, static vs dynamic badge selection, style variants (flat/flat-square/for-the-badge/social/plastic), layout patterns (two-tier/inline/centered), project-type badge sets for Python/JS/Rust/Claude plugins, color reference, non-obvious logo slugs, and common anti-patterns to avoid.

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。

IOTA blockchain MCP server providing wallet management with human-in-the-loop signing, Move smart contract build/test/publish, and on-chain queries via JSON-RPC and GraphQL. Use when interacting with IOTA network from AI coding agents, managing IOTA wallets, building or publishing Move packages, querying on-chain objects or transactions, or checking epoch and network statistics.

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。

Advises on setting up and validating topic models for survey and experimental text. Covers the discovery-versus-measurement question, choosing STM, LDA, or BERTopic, preprocessing consequences, prevalence and content formulas, topic-count selection across coherence, exclusivity and FREX, held-out likelihood, and residuals, validation of topics against human judgment, robustness, and DA-RT-compliant reporting. Use when the user has open-ended responses or another corpus and asks what topics are present, how many topics to use, about STM, searchK, coherence, or FREX, or wants topic prevalence compared across treatment arms or countries. Fixed-codebook coding goes to text-classification.

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。

Advises on setting up LLM-based text classification as a validated measurement design. Covers codebook construction, learning-regime and model choice, prompt construction, validation against human coding with kappa and F1, hybrid human-LLM review, downstream measurement error, and reporting, plus a short resumable batch pattern with a rule-based baseline for repeated free text against a closed codebook. Use when the user wants to classify, code, or label text at scale. Category discovery goes to topic-modeling.

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。

Advises on setting up and validating LLM text classification: codebook, learning regime and model choice, prompts, validation against human coding (kappa, F1), hybrid review, measurement error, and reporting, plus a short resumable batch pattern with a rule-based baseline. Use to classify, code, or label text at scale; category discovery goes to topic-modeling.

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-before-coding workflow. Search for existing tools, libraries, and patterns before writing custom code. Invokes the researcher agent.

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。

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics

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。