「cstr」の検索結果

Implement, review, or improve localization and internationalization in iOS/macOS apps — String Catalogs (.xcstrings), generated localizable symbols, stable key naming, LocalizedStringKey, LocalizedStringResource, pluralization, FormatStyle for numbers/dates/measurements, right-to-left layout, Dynamic Type, and locale-aware formatting. Use when adding multi-language support, setting up String Catalogs, enabling generated symbols for compile-time-safe localization keys, handling plural forms, formatting dates/numbers/currencies for different locales, testing localizations, or making UI work correctly in RTL languages like Arabic and Hebrew.

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。

This skill should be used when writing, reviewing, or refactoring Python code. Covers code integration, idiomatic patterns, docstring formatting, anti-abstraction rules, and software engineering basics.

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。

Generates and validates technical documentation including docstrings, OpenAPI/Swagger specs, JSDoc annotations, doc portals, and user 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。

Generate internationalization (i18n) infrastructure for multi-language support in iOS/macOS apps. Use when localizing for multiple languages, adopting String Catalogs (xcstrings), or supporting RTL languages.

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。

One-shot efficiency audit of a file, diff, or whole repo across BOTH axes at once: over-engineered code (reinvented stdlib, needless abstractions, speculative config) AND bloated prose (verbose comments, padded docstrings, redundant doc sections). Neither a pure code-minimizer nor a pure prose compressor does both in one pass. That's the point. Ranked report, biggest saving first; changes nothing. Use when the user says "chisle audit", "/chisle-audit", "audit this for bloat", "what can I cut", "review this PR for over-engineering and verbosity".

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 effective code comments, READMEs, and technical documentation following intent-first principles. Use when adding comments, writing docstrings, creating READMEs, or updating any documentation.

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。

Updates documentation after code changes with quality gates, slop detection, and accuracy checks. Use when code changes require corresponding doc updates.

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 an ASD-STE100-derived register to operator and procedural text. Use when writing runbooks or steps. Do not use for docstrings, ADRs, or rationale.

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。

API reference: Swift Concurrency. async/await, Task, TaskGroup, actors, AsyncSequence, AsyncStream, continuations.

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。

Main app analytics tracking patterns (AnalyticsEvent enum, AnalyticsTrackerWrapper, KEY_*/VALUE_* constants). Use when writing, editing, exploring, debugging, or reviewing analytics tracking in the store management app. NOT for POS (WooPos*) code — use the `pos-analytics` skill instead.

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。

POS analytics tracking patterns (WooPosAnalyticsEvent sealed class, WooPosAnalyticsTracker, WooPosAnalyticsEventConstant). Use when writing, editing, exploring, debugging, or reviewing analytics tracking in POS (WooPos*) code. NOT for main store app — use the `store-analytics` skill instead.

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 comprehensive test case documentation from test code, test framework output, existing test docs, and source code context. Use when documenting test suites, creating test specifications, generating test coverage reports, onboarding developers to testing practices, or preparing QA documentation. Analyzes test functions (pytest, unittest) to extract test names, docstrings, assertions, and organization, then produces structured markdown with both overview-level summaries and detailed test case specifications including purpose, preconditions, steps, expected results, and test data. Triggers when users ask to document tests, generate test specifications, create test reports, summarize test coverage, or explain what tests do.

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。

Convert pseudocode, algorithm descriptions, or specifications into complete, executable Python code. Handles natural language descriptions, structured pseudocode, and formal algorithm specifications. Generates production-ready code with type hints, docstrings, error handling, and test cases. Use when users need to (1) convert pseudocode to Python, (2) implement algorithms from descriptions, (3) translate algorithm specifications to code, (4) generate Python implementations from textbook pseudocode, or (5) create executable code from high-level algorithm designs.

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。

Detect semantic-level bugs by analyzing whether code behavior matches its intended purpose inferred from function/variable names, comments, docstrings, and documentation. Use when users need to: (1) Find logic errors where implementation contradicts stated intent, (2) Identify off-by-one errors and boundary mismatches, (3) Detect inverted logic or wrong operators, (4) Catch missing edge case handling, (5) Verify code matches its documentation. Highlights mismatches between intent and implementation across multiple programming languages.

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。

Generates meaningful comments and documentation for code to improve maintenance and readability. Use when adding documentation to Python or Java code, including function/method docstrings, class documentation, inline explanations for complex logic, and code annotations (TODO, FIXME). Analyzes existing comment style in the codebase to match conventions. Produces clear, concise comments that explain the "why" not just the "what", following best practices for each language.

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 comprehensive API documentation from repository sources including OpenAPI specs, code comments, docstrings, and existing documentation. Use when documenting APIs, creating API reference guides, or summarizing API functionality from codebases. Extracts endpoint details, request/response schemas, authentication methods, and generates code examples. Triggers when users ask to document APIs, generate API docs, create API reference, or summarize API endpoints from a repository.

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。

Inspect and edit Xcode String Catalogs (.xcstrings) via bundled l10n.sh and find_unused_keys.sh scripts, and apply Apple localization 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。

Automatically generate clear, comprehensive documentation for codebases — including API references, inline docstrings, README files, and usage guides. Use when the user requests code documentation or provides relevant inputs for this workflow.

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。

Check that a document's claims about code are actually true by reading the prose, the code, and the tests and reporting (or fixing) where they disagree. Use whenever the user wants to verify a README, guide, spec, or docstring still matches the code; whenever they mention documentation drift, doc-code sync, "is this still accurate", stale docs, or keeping docs/tests/code consistent; before publishing or merging a docs change; or as a periodic doc-accuracy sweep. The agent reads the prose's meaning directly — there is no claim-comment DSL to maintain. Pairs with TDD — the test suite is the deterministic behavioral gate, this skill is the semantic prose-vs-reality 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。

Generate and maintain AI-readable markdown documentation for a codebase in docs/. Use this skill whenever the user asks to document their codebase, generate project docs, create architecture docs, update documentation after code changes, build a knowledge base for AI agents, create onboarding docs, map out a codebase, or explain a project structure. Also trigger when users say things like "document this repo", "create docs for my project", "update the docs", "write architecture documentation", "help AI understand my code", "generate a codebase overview", or "maintain docs". This skill is specifically about creating structured markdown files in a docs/ directory that serve as a knowledge base — NOT about writing inline code comments, README files, or API reference docs from docstrings.

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。

ALWAYS start here when the user wants a page OR a doc: page, living page, doc, document, living doc, bongo or bongo doc (the old name; new ones are made here, not by a Bongo connector), shared or collaborative doc, write-up, one-pager, memo, brief, proposal, plan, spec, report, meeting notes, notes, checklist, tracker, or anything to read, edit, comment on and share together — 'write this up', 'put this in a doc', 'draft a brief', 'jot this down somewhere we can share and edit', 'turn this file into a page' — the DEFAULT for any of these when no file format is named; a Word/.docx, PDF, .pptx or .xlsx FILE asked for by name goes to that format's skill instead. Also whenever the pages connector is about to be used to create a page. Not for READMEs, code or docstrings. A lowercase /pages as its own word anywhere in the message (not in a URL, path or longer name) invokes this skill whatever else is asked — a summary, an answer, a comparison, a plan: the page is the reply.

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 this when creating, editing, or reviewing Python code — including type hints, docstrings, naming conventions, imports, error handling, and code structure.

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。

Detect AI-generated writing patterns in developer text — docs, docstrings, commit messages, PR descriptions, and code comments. Use when reviewing any text artifact for authenticity and clarity, or when the user mentions ai writing, ai-generated or robotic writing, text that sounds like AI or ChatGPT, or writing quality. Builds on the docs-style core writing principles.

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。

Register and implement PydanticAI tools with proper context handling, type annotations, and docstrings. Use when adding tool capabilities to agents, implementing function calling, or creating agent 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。