「codebase」の検索結果

Build, refresh and query a deterministic code knowledge graph to cut orientation-token cost. Triggers: knowledge graph, graphify, code graph, god nodes, orientation cost, map the codebase, what connects, callers of, blast radius.

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 Sendsets to turn a software product into useful outbound campaigns, then operate mailboxes, warmup, campaigns, replies, and product integrations through the CLI. Use when the user asks to set up or run cold email with Sendsets or wants campaign ideas grounded in their codebase.

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。

Scaffold a one-command `dev-local` launcher for ANY codebase. Investigates the repo to find its services, ports, and infra dependencies, then generates a single `scripts/dev-local.sh` (up/down/status/logs/restart) that runs every dev server in one tmux session, plus a short skill doc describing it. Use when someone says "set up dev-local", "make a one-command dev launcher", "I want one script to start this repo", "scaffold dev-local for this project".

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 a repo's agent context — CLAUDE.md files, codebase docs, skills, and tool/MCP designs — against Anthropic's Claude 5 context-engineering guidance ("unhobbling": Anthropic cut ~80% of Claude Code's system prompt with no eval loss). Finds overconstraint, conflicting instructions, redundancy, stale facts, and missing "unknown knowns"; produces a scored findings report with concrete rewrites, then applies approved fixes. Use when someone says "audit my CLAUDE.md", "context audit", "unhobble this repo", "review our agent docs/skills/tools", or after upgrading to Claude 5-generation models.

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。

Scan a Kotlin or Compose Multiplatform diff for known footgun shapes and open the matching trap to confirm each hit. Use before committing, when reviewing a Kotlin change, or to audit a codebase.

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。

Guidelines for making .NET libraries and applications trimming-safe and Native AOT compatible. Covers the trimming/AOT model, the MSBuild properties that enable analysis (IsTrimmable, IsAotCompatible, PublishTrimmed, PublishAot), the trimming attributes (RequiresUnreferencedCode, RequiresDynamicCode, DynamicallyAccessedMembers, UnconditionalSuppressMessage), IL2xxx/IL3xxx warning codes, and a pattern playbook: source generators and UnsafeAccessor, generated-interception diagnostic suppressors, intentional runtime scanning boundaries, trimming-safe islands and feature switches, migration analyzers, and temporary warning-approval baselines. Use when introducing trimming/AOT support, resolving IL2xxx/IL3xxx warnings, or making reflection-heavy code trimming-safe in C# / .NET codebases. For System.Text.Json AOT scenarios, see also the serialization 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。

Provides guidance for implementing OpenTelemetry instrumentation in .NET codebases, covering tracing (Activities/Spans), metrics, logs, naming conventions, error handling, performance, SDK setup, resources, context propagation, and API design best practices.

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。

Configures and enforces SwiftLint in Swift projects using build tool plugins, run scripts, and CI. Covers .swiftlint.yml configuration, disabled_rules, opt_in_rules, only_rules, analyzer_rules, baselines, autocorrect, swiftlint:disable suppressions, reporter formats (sarif, json, checkstyle), strict and lenient modes, SwiftLintBuildToolPlugin via SimplyDanny/SwiftLintPlugins, swift package plugin swiftlint, Xcode run script phases, CI integration, multiple configuration files, and rollout strategies for existing codebases. Use when setting up SwiftLint, configuring lint rules, suppressing warnings, creating baselines, choosing between build tool plugin and run script, or integrating SwiftLint into CI.

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。

Deploys and operates a LiveKit agent in production: shipping a version to LiveKit Cloud and rolling it back, secrets and configuration, the worker process model and prewarming, safe async inside worker processes, provider timeouts and degradation, graceful shutdown, SDK upgrades, and observability. Use when the user says "deploy my agent", "roll back the deployment", "tail the agent logs", "the first call after a restart is slow", "attached to a different loop / event loop is closed", "prewarm the VAD", "shut down without dropping calls", "upgrade livekit-agents safely", "correlate logs by session", or is changing an agent codebase that is already live. Not for designing the agent (building-livekit-agents) or reproducing one bad conversation locally (debugging-livekit-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。

Write and debug ast-grep rules for structural code search and rewrite. Use when tasks require AST-aware matching (not plain text), such as finding specific syntax shapes, relational patterns (inside/has), composite logic (all/any/not), or precise code refactors across a codebase.

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。

Writing effective code documentation - API docs, README files, inline comments, and technical guides. Use for documenting codebases, APIs, or writing developer guides.

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。

Adversarial senior review of the spec before any code is written. Constructs a skeptical reviewer whose authority comes from the codebase, §R research, and live best-practice — then tries to REFUTE the spec, not rubber-stamp it. Every finding cites evidence (file:line or source); unverifiable ones are flagged. Survivors harden §V; the run ends in an explicit go / no-go gate. Triggers before building anything high-blast-radius, when the user says "review the spec", "red-team this", "is this plan sound", "senior review", or invokes /ck:review.

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。

Interactive harness setup for any project. Detects stack, scaffolds process dirs, deep-scans the codebase, populates context. Works on fresh and existing projects — always asks before reorganizing.

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。

Fast codebase scouting using shell search and optional parallel research agents. Use for file discovery, task context gathering, and quick scoped searches across directories.

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。

Code learning and audit framework. Analyze any codebase — new, legacy, or AI-generated — and produce educational explanations or architectural audits. Use when the user wants to understand WHAT and WHY behind any code, not just accept it.

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。

Generate project documentation from codebase analysis — ARCHITECTURE.md, API_ENDPOINTS.md, DATABASE_SCHEMA.md. Reads source code, schema files, routes, and config to produce accurate, structured docs. Use when starting a project, onboarding contributors, or when docs are missing or stale. Triggers: 'generate docs', 'document architecture', 'create api docs', 'document schema', 'project documentation', 'write architecture doc'.

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。

Keeps the engagement record for client work. Use when they name a client or stakeholder. Use when they debrief a meeting or paste notes. Use when they ask what was agreed. Use when they run a POC, change the client's codebase, prove it on their staging, go live, or need evals before a model acts. Use when they prep a readout, when trust shifts, or they say @fde. Route and run the local fde CLI (or npx --yes fdeops). Never ask them to type commands. Not for ordinary code edits in an unbound repo.

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。

Cavekit specification-driven development methodology — the Hunt lifecycle (Draft → Architect → Build → Inspect → Monitor) and how to apply it. Use when starting a Cavekit project, structuring an existing codebase as kits/plans, or routing between sub-skills.

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。

Reverse-engineers specifications from existing codebases, maps code dependencies, generates API documentation from source, and identifies undocumented business logic.

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。

Designs incremental migration strategies using strangler fig pattern, identifies service boundaries, produces dependency maps, and generates API facade designs for aging codebases.

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 codebase health metrics including complexity and dependencies

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。

Generate validated AWS architecture diagrams as draw.io XML using official AWS4 icon libraries. Use this skill whenever the user wants to create, generate, or design AWS architecture diagrams, cloud infrastructure diagrams, or system design visuals. Also triggers for requests to visualize existing infrastructure from CloudFormation, CDK, or Terraform code. Supports two modes: analyze an existing codebase to auto-generate diagrams, or brainstorm interactively from scratch. Exports .drawio files with optional PNG/SVG/PDF export via draw.io desktop 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。

Deploy applications to AWS. Triggers on phrases like: deploy to AWS, host on AWS, run this on AWS, AWS architecture, estimate AWS cost, generate infrastructure. Analyzes any codebase and deploys to optimal AWS services.

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 a software codebase for algorithmic complexity and performance hotspots, then propose or implement safe optimizations without breaking behavior. Use when Codex is asked to scan many files, find inefficient loops, nested iteration, repeated scans, costly rendering/recomputation, N+1 queries, avoidable O(n^2) or O(n) operations, or reduce complexity such as O(n^2) to O(n log n) / O(n), while preserving tests, APIs, outputs, and maintainability.

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。