1,331 件 ・ 関連度順
概要と使いどころ
Analyze a Coval accent testing report from runs across different speaker accents. Use when a user provides a Coval report URL, report export, run IDs, screenshots, or metric summary and wants evidence-backed next steps such as prompt changes, STT/confirmation adjustments, accent-robust routing, or expanded accent coverage.
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 Coval adversarial / red-team testing report and turn it into an agent-hardening plan. Use when a user provides a Coval report URL, report export, run IDs, screenshots, or a per-scenario scorecard from an adversarial sweep and wants evidence-backed next steps such as prompt/guardrail changes, refusal hardening, verification fixes, escalation routing, or expanded attack coverage.
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 Coval audio-quality testing report from runs across different voice, speaking-style, volume, interruption, and background-noise scenarios. Use when a user provides a Coval report URL, report export, run IDs, screenshots, or metric summary and wants evidence-backed next steps such as prompt changes, tool handling fixes, STT/TTS adjustments, trace setup, or expanded audio-scenario coverage.
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。
Run the pytest test suite with coverage. Accepts optional filter flags. Use after making changes to verify nothing broke.
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。
Profound LLM citation tracker (extension). Time-series brand citation rates across ChatGPT, Perplexity, and other LLMs. Pairs with seo-seranking for triangulated AI visibility coverage.
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 implementing features or fixing bugs with strict Test-Driven Development (TDD). Activate for coding tasks that require new functionality, refactoring, or comprehensive test coverage, especially when the user mentions TDD or Test Driven Development.
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。
Proves a Godot 4.x build is actually green and holds its project conventions. Trigger when a GUT or GDScript result needs believing (a suite green while a script failed to parse, drifted CI guard counts, a coverage claim, a gate figure, a failing check someone wants softened); to review scenes, signals, awaits, threads, determinism, saves, imports or .uid files, or the upgrade rule (not the migration); to prove a simulation or balance rule; for import settings and the pixel-art render precondition; or say godotsmith (check, guard, gate, review, intake). API reference is the Godot docs'; art reads pixelsmith's; audio direction soundsmith's.
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 adding or repairing Spark regression tests for asynchronous ownership, cancellation, persistence, restart recovery, or cross-surface projections. Not a coverage campaign, performance benchmark, source-text policy check, or full delivery 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。
[51] EXECUTE. Commitment to maximum quality work with 150% coverage. Use when you need the highest quality output for critical tasks, complex problems, important decisions, or when standard work isn't enough. Triggers on "maximum quality", "150% mode", "full quality", "critical task", or when you explicitly want AI to work at its best.
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。
[60] VALIDATE. Ensure new (staged and unstaged) changes are covered by tests at >70% and the full test suite is green. Use when asked to validate coverage for recent changes, add tests for modified code, or verify nothing else broke.
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。
Perl testing patterns using Test2::V0, Test::More, prove runner, mocking, coverage with Devel::Cover, and TDD methodology.
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。
Kotlin testing patterns with Kotest, MockK, coroutine testing, property-based testing, and Kover coverage. Follows TDD methodology with idiomatic Kotlin 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。
Use this skill when writing new features, fixing bugs, or refactoring code. Enforces test-driven development with 80%+ coverage including unit, integration, and E2E tests.
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。
Python testing strategies using pytest, TDD methodology, fixtures, mocking, parametrization, and coverage requirements.
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。
Verification loop for Spring Boot projects: build, static analysis, tests with coverage, security scans, and diff review before release or PR.
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 only when writing/updating/fixing C++ tests, configuring GoogleTest/CTest, diagnosing failing or flaky tests, or adding coverage/sanitizers.
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。
Django testing strategies with pytest-django, TDD methodology, factory_boy, mocking, coverage, and testing Django REST Framework APIs.
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。
Go testing patterns including table-driven tests, subtests, benchmarks, fuzzing, and test coverage. Follows TDD methodology with idiomatic Go 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。
Verification loop for Django projects: migrations, linting, tests with coverage, security scans, and deployment readiness checks before release or PR.
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 the user wants to review a pull request, understand what a PR changes, assess risk of merging, or check for missing test coverage. Examples: "Review this PR", "What does PR #42 change?", "Is this PR safe to 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。
Local-first insurance record organizer for tracking policies, renewals, claims logs, and related insurance records. Use when the user wants to store policy details, list recorded policies, track renewal dates, log claim events, or summarize insurance records. NEVER provides insurance advice, recommends coverage amounts, or facilitates policy purchases.
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。
Run a bounded, governed iteration — "loop", "iterate until", "keep going until", "sweep", "ratchet", "until it passes", "coverage to 100". Turns an open-ended autonomous run into a finite loop with checkpoints and explicit stopping conditions.
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 and assure quality — test plan, QA, coverage, unit test, integration test, end-to-end, performance, benchmark, regression. Applies TDD and FIRST principles for the CTO office's tester.
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。
Creates an integration testing plan for .NET data access artifacts during Oracle-to-PostgreSQL database migrations. Analyzes a single project to identify repositories, DAOs, and service layers that interact with the database, then produces a structured testing plan. Use when planning integration test coverage for a migrated project, identifying which data access methods need tests, or preparing for Oracle-to-PostgreSQL migration validation.
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。