「coding」の検索結果

Use for reusable tooling analysis recipes in software and coding-agent work.

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Use for reusable harness sdk protocol recipes in software and coding-agent work.

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Use for reusable build submit packaging recipes in software and coding-agent work.

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Use for reusable experiment discipline recipes in software and coding-agent work.

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Use when decoding a Crewrift replay for authoritative deaths, survival, movement, roles, tasks, or rewards.

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Use for reusable env toolchain recipes in software and coding-agent work.

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Use for reusable navigation pathfinding recipes in software and coding-agent work.

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Use for reusable suspicion belief recipes in software and coding-agent work.

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Use for reusable agent workflow collab recipes in software and coding-agent work.

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Create reproducible, cross-platform development environments with Flox — a declarative environment manager built on Nix. ALWAYS use this skill when the user needs to: set up a project with system-level dependencies (compilers, databases, native libraries like openssl, libvips, BLAS, LAPACK); configure reproducible toolchains for Python, Node.js, Rust, Go, C/C++, Java, Ruby, Elixir, PHP, or any language; manage environments that must work identically across macOS and Linux; pin exact package versions for a team; run local services (PostgreSQL, Redis, Kafka) alongside development tools; onboard new developers with a single command; or solve 'works on my machine' problems. Especially valuable for AI-assisted and vibe coding — Flox lets agents install tools into a project-scoped environment without sudo, system pollution, or sandbox restrictions, and the resulting environment is committed to the repo so anyone can reproduce it instantly. Use this skill even if the user doesn't mention Flox — if they describe needing reproducible, declarative, cross-platform dev environments with system packages, this is the right tool. Also use when the user mentions .flox/, manifest.toml, flox activate, or FloxHub.

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 coding tasks via Claude DevFleet — plan projects, dispatch parallel agents in isolated worktrees, monitor progress, and read structured reports.

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

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Session retrospective. Runs after a workflow, coding session, or multi-step task completes. Analyzes what shipped, what failed, patterns observed, and growth opportunities. Generates a retro summary with per-step breakdowns, shipping streaks, and test health trends. Use after any significant session (>3 steps or >15 min). Proactively suggest when the user finishes a workflow, completes a feature, or says "let's review what we did." Also supports global retro across all projects.

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Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files). Triggers include: any mention of 'Word doc', 'word document', '.docx', or requests to produce professional documents with formatting like tables of contents, headings, page numbers, or letterheads. Also use when extracting or reorganizing content from .docx files, inserting or replacing images in documents, performing find-and-replace in Word files, working with tracked changes or comments, or converting content into a polished Word document. If the user asks for a 'report', 'memo', 'letter', 'template', or similar deliverable as a Word or .docx file, use this skill. Do NOT use for PDFs, spreadsheets, Google Docs, or general coding tasks unrelated to document generation.

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Score a repository's agentic legibility from repo-visible evidence only. Use when Codex needs to audit how easy a codebase is for coding agents to discover, bootstrap, validate, and navigate, especially for harness-engineering reviews, developer-experience audits, repo cleanup, or before/after comparisons after improving docs, tooling, or architectural constraints.

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Manage Google Ads & Meta (Facebook) Ads from your AI coding tool. 99 MCP tools for auditing, creating, and optimizing ad accounts using natural language.

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Adversarial implementation review based on Block's g3 dialectical autocoding research. Use when validating implementation completeness against requirements with fresh objectivity.

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Broadcast agent activity status to Discord channel (thinking, tool use, web search, coding, done, error). Use for transparency so users know agent is working.

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Generate synthetic code context for LLM coding tasks. Automatically use this before making code changes, fixing bugs, refactoring, or answering questions about the codebase. Provides execution paths, relevant files, symbols, tests, and code snippets.

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Generate code context for coding tasks. Run before code changes, bug fixes, or refactoring to get execution paths, key files, symbols, tests, and snippets.

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Develop or review dygo metadata loading, YAML decoding, JSON Schemas, validation, naming, Field types, registries, routes, and persisted metadata contracts. Use for framework-level metadata behavior rather than authoring one Business App Entity.

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Clarify ambiguous requirements through focused dialogue before implementation. Use when requirements are unclear, features are complex (>2 days), or involve cross-team coordination. Ask two core questions - Why? (YAGNI check) and Simpler? (KISS check) - to ensure clarity before coding.

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Creates specs before coding. Use when starting a new project, feature, or significant change and no specification exists yet. Use when requirements are unclear, ambiguous, or only exist as a vague idea.

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Use when the user asks to run Gemini CLI for code review, plan review, or big context (>200k) processing. Ideal for comprehensive analysis requiring large context windows. Uses Gemini 3 Pro by default for state-of-the-art reasoning and 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。