「quality」の検索結果

Systematically explore and test a web application to find bugs, UX issues, and other problems. Use when asked to "dogfood", "QA", "exploratory test", "find issues", "bug hunt", "test this app/site/platform", or review the quality of a web application. Produces a structured report with full reproduction evidence -- step-by-step screenshots, repro videos, and detailed repro steps for every issue -- so findings can be handed directly to the responsible teams.

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Review common AI slops of defensive programming patterns, avoid silent errors. TRIGGER when reviewing code for defensive anti-patterns, writing fail-fast code, or auditing error handling quality.

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。

Best practices for AI-driven English-to-Chinese translation. This skill should be used when the user asks to "translate to Chinese", "update the Chinese translation", "improve Chinese translation", "fix translation quality", "review Chinese translation", or when translating any English text into Chinese. Also applies when polishing an existing Chinese translation of English content.

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 traceability matrix and quality gate decision. Use when the user says "lets create traceability matrix" or "I want to analyze test 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。

Master Test Architect and Quality Advisor. Use when the user asks to talk to Murat or requests the Test Architect.

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。

S5 of see-it-ship-it: prove it works before saying so. Silent quality checks after every feature, a full review of every file before save and deploy, and the acceptance table (check / expected / actual / match) run on the local build and again on the live URL. Never 'tests passed'.

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。

Used to invoke the PXMeter tool for rigorous quality assessment of biomolecular structure prediction models (e.g., proteins, nucleic acids, small molecules). This skill covers single-sample CIF evaluations and large-scale dataset benchmarks, providing rich result parsing support. Trigger this skill when the user asks to "run PXMeter", "compare PDB/CIF evaluation results of different tools", "check benchmark scores", or asks "how accurate is the structure generated by the model".

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。

Directly generate design-oriented AI images with strong creative direction and prompt engineering. Use this skill for posters, product visuals, PPT illustrations, infographics, teaching/demo diagrams, campaign key visuals, cover art, or when the user wants design-quality image generation rather than generic AI art. This skill turns a loose brief into a design brief, assembles a structured prompt, routes to the right Volcengine Seedream settings, and can generate the image immediately.

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 auditing self-media videos, scripts, covers, subtitles, voiceover, product links, account copy, comments, articles, or publishing packages for platform violation risk; especially before final delivery or publishing after video production or clipping. Covers e-commerce product consistency, Qianchuan material quality, regulated qualifications, efficacy claims, prices, gifts, activities, and pre-selection risk across WeChat, Douyin, Kuaishou, Bilibili, Xiaohongshu, TikTok, and related platforms.

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Use this skill when visual quality and design identity matter for a PDF. CREATE (generate from scratch): "make a PDF", "generate a report", "write a proposal", "create a resume", "beautiful PDF", "professional document", "cover page", "polished PDF", "client-ready document". FILL (complete form fields): "fill in the form", "fill out this PDF", "complete the form fields", "write values into PDF", "what fields does this PDF have". REFORMAT (apply design to an existing doc): "reformat this document", "apply our style", "convert this Markdown/text to PDF", "make this doc look good", "re-style this PDF". This skill uses a token-based design system: color, typography, and spacing are derived from the document type and flow through every page. The output is print-ready. Prefer this skill when appearance matters, not just when any PDF output is needed.

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 and enforces documentation quality. Use when checking coverage, freshness, runbook validity, AI-instruction coverage, or cleaning stale/duplicate markdown after LLM edits.

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Builds analytics engineering layers for metrics, contracts, and BI-ready models. Use when shaping dbt or SQLMesh marts, metric governance, lineage, or data quality.

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Designs LLM, agent, responsible-AI, and multimodal evals. Use when measuring quality, fairness, grounding, safety, or judge reliability. Not for test harnesses (qa-agent-testing).

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。

Measures AI coding impact and extension robustness. Use when tracking delivery, quality trajectories, cost, experience, pilots, scorecards, or leadership reporting.

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。

Builds production voice bots and IVR with Python STT/TTS pipelines. Use when designing telephony, streaming audio, latency budgets, or voice quality monitoring.

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Designs and runs reproducible evaluations for AI agents, prompts, tools, skills, and model-backed workflows using realistic datasets, isolated baselines, objective assertions, rubric grading, trajectory analysis, cost/latency tracking, and regression comparison. Use when measuring agent quality, optimizing skill triggering, comparing prompts or models, or gating an AI feature release. Not for ordinary deterministic unit tests.

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Prepares and controls software releases with risk classification, CI quality gates, artifact provenance, feature flags, staged rollout, measurable promotion and rollback thresholds, post-deploy verification, and cleanup. Use for deployment pipelines, launch readiness, canaries, production rollout, release automation, or rollback planning. Not for merely merging a completed development branch or proving one local change.

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Executes an approved implementation plan through fresh implementer and reviewer agents for each task, with explicit handoffs, focused tests, and task-by-task integration. Use for multi-task work where independent agent context improves implementation and review quality. Not for a single small edit, an unresolved design, or a failure that still needs root-cause analysis.

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。

Validates a running application, CLI, API, service, or generated artifact as a user or operator against a prewritten observable behavior contract while remaining source-blind. Use for acceptance checks, runtime proof, anti-fake probes, release smoke tests, or an independent companion to code review. Not for source-quality findings, root-cause diagnosis, or visual design judgment outside the contract.

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 HitKeep ecommerce and conversion data. Use for revenue, orders, average order value, products, sources, ecommerce funnels, conversion changes, UTM performance, acquisition quality, or aggregate city, provider, and ASN context.

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Plan, execute, investigate, and report HitKeep quality gates through hk. Use while iterating, before calling contributor work complete, when choosing change-aware versus PR-parity versus exhaustive validation, when CI parity matters, or when investigating a failed or asynchronous gate.

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。

Web design reference for building production-grade interfaces. Covers layout, typography, color, spacing, shadows, animation, accessibility, responsive design, components, performance, and UX psychology. Use when building UI, reviewing design quality, choosing design tokens, or making any visual design decision.

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Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

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Run a self-refinement loop when a Blender result is subpar, user expectations are not met, validation fails, or repeated issues reveal missing skill depth. The loop diagnoses the gap, decides whether to repair the artifact or acquire/refine a generic skill, sanitizes lessons for reusable publication, updates docs/versioning, validates, and prepares stage/commit/push when explicitly requested.

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。