본문으로 건너뛰기
cccskills

'quality-control' 검색 결과

23건 · 관련도순

Study verified medical guidelines through section summaries linked to their original locations. The skill explains confusing points, summarizes selected topics, and builds learning sequences with estimated study time and signs of understanding.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Study a guideline chapter with references to the original text
  • Summarize screening, follow-up, or quality-control learning points
  • Build a learning sequence that fits available study time
TencentCloud/Octop1만2026년 10월 19일 업데이트

Build or review quality control workflows for single-cell and single-nucleus RNA sequencing data. Select filters from observed data, detect doublets, assign cell types, and create UMAP plots that summarize cell relationships, while recording analysis decisions and outputs.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Choosing quality filters from dataset distributions
  • Detecting doublets and checking ambient RNA
  • Assigning cell types using references or marker genes
openai/plugins7.5천2026년 10월 8일 업데이트

Adversarial verification of AI-generated legal content with systematic fact-checking, source validation, and quality control. Use when a user asks to verify, fact-check, red-team, validate sources, or quality-control a legal document, briefing, compliance summary, or regulatory analysis before it is distributed to clients, stakeholders, or published. Trigger phrases include "verify", "fact-check", "red team", "red-flag", "check accuracy", "validate sources", "quality control", "is this correct", and "review for errors". Produces a structured verification report with severity-categorized errors, verified sources, unsupported claim list, missing disclaimers, and an explicit distribution-readiness assessment.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

lawve-ai/awesome-legal-skills8742026년 10월 3일 업데이트

Evaluate completed mediation-competition problems consisting of general information and confidential packets for both sides. Use when asked to validate, audit, score, quality-control, or assess competition readiness; identify factual, numerical, chronological, authority, commercial-logic, or confidentiality defects; test mediation usefulness, BATNAs, settlement corridors, information asymmetry, and opportunities for firmness, cooperation, imagination, and clarification; or produce an author-only validation report. Perform a qualified partial review when packets are missing. Diagnose by default; do not generate a new problem or edit source packets unless repairs are expressly requested. Requires access to all supplied files and a host capable of reading their formats; otherwise disclose the unreviewed material and resulting limits.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

lawve-ai/awesome-legal-skills8742026년 10월 3일 업데이트

Construction quality control workflow automation. Manage QC inspections, track defects, generate NCRs, and ensure specification compliance throughout the project.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction3582026년 8월 22일 업데이트

Delegates execution to eight CLIs (Gemini, Qwen, MiniMax, GLM, Muse, Codex, OpenCode, Glimmer). Use for execution tasks. Do not use for secrets.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

athola/claude-night-market3422026년 10월 17일 업데이트

Use for ElevenLabs provider-specific dubbing, localization, voice changer, speech-to-speech, and voice isolation/enhancement workflows. Applies when an agent must prepare source media, choose ElevenLabs dubbing versus voice conversion, manage language/speaker/timing decisions, handle voice identity and consent, call or plan against documented ElevenLabs APIs, export dubs/transcripts, estimate cost/limits, or quality-control localized speech while avoiding generic text-to-speech guidance.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

calesthio/generative-media-skills2062026년 7월 14일 업데이트

Produce, direct, integrate, and quality-control ElevenLabs text-to-speech for narration, character performance, multilingual media, long-form voiceover, and streamed or batch AI-content audio. Use when selecting ElevenLabs models or voices; preparing spoken text; controlling pronunciation, pacing, emotion, and code-switching; using TTS APIs; cloning or designing a voice with consent; repairing artifacts; mastering deliverables; or evaluating generated speech. Excludes music, sound-effect generation, conversational-agent design, and general speech recognition except transcription used to verify TTS.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

calesthio/generative-media-skills2062026년 7월 14일 업데이트

Plan, prompt, execute, troubleshoot, and quality-control Black Forest Labs FLUX image generation and editing across the BFL direct API and licensed local/open-weight deployments. Use for FLUX.2 model selection, text-to-image, single- or multi-reference editing, typography, exact-color work, mask-based erase/inpainting, outpainting, API integration, reproducibility, deployment licensing, and production rights or safety decisions; also use when migrating or maintaining legacy FLUX.1/FLUX1.1 workflows.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

calesthio/generative-media-skills2062026년 7월 14일 업데이트

Plan, generate, edit, reference, and quality-control still images with Kling AI's hosted IMAGE surfaces or Kuaishou's open Kolors checkpoints. Use for Kling IMAGE 3.0/3.0 Omni/O1/2.1 web, official Kling CLI/MCP or Open Platform integration, and local Kolors text-to-image, image-to-image, IP-Adapter, ControlNet, inpainting, or LoRA work. Do not use for Kling video, avatars, lip-sync, unofficial gateway APIs, or for assuming that current hosted Kling Image models are identical to the 2024 open Kolors weights.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

calesthio/generative-media-skills2062026년 7월 14일 업데이트

Create, edit, guide, upscale, and quality-control still images with Leonardo.Ai's official Production API, including native Lucid and Phoenix models, uploaded or generated references, image-to-image, ControlNet guidance, realtime-canvas inpainting, Pro and Universal upscalers, and custom Elements or models. Use for Leonardo image API implementation, async polling or webhooks, dry-run and cost governance, secure artifact handling, prompt iteration, or production troubleshooting. Do not use for Leonardo video, 3D generation, unofficial wrappers, or third-party gateway APIs.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

calesthio/generative-media-skills2062026년 7월 14일 업데이트

Diagnose, design, script, produce, adapt, and quality-control product video advertisements from evidence-backed briefs. Use for physical-product, software, app, service, ecommerce, direct-response, brand-response, demonstration, testimonial, launch, and variant ad work where product truth, legibility, claims, platform delivery, and measurable iteration matter.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

calesthio/generative-media-skills2062026년 7월 14일 업데이트

The orchestration layer for AI-native creative production. This skill coordinates multiple AI tools—video, image, audio, digital humans, effects—into cohesive campaigns, productions, and creative systems. As AI tools proliferate, the challenge shifts from "can we create this?" to "how do we orchestrate these capabilities into something coherent?" The AI Creative Director thinks in systems, not tools. In pipelines, not one-offs. In brand consistency across AI-generated assets. This is where creative vision meets technical orchestration. The AI Creative Director doesn't just use AI tools—they compose them into creative instruments that produce at scales and speeds previously impossible. Use when "AI creative director, orchestrate AI, AI campaign, multi-tool, AI workflow, AI pipeline, coordinate AI, AI production, AI creative system, full AI production, AI at scale, orchestration, creative-direction, ai-production, workflow, pipeline, multi-tool, scale, quality-control" mentioned.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

omer-metin/skills-for-antigravity1682026년 1월 22일 업데이트

Peer review checklist and quality standards for intelligence products, plus schema validation for graded evidence items and claim tables from /quality-of-information-check and /claim-extraction. Rejects outputs that break the evidence schema or the grading caps. Loaded by the quality-reviewer agent.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Liberty91LTD/cti-skills272026년 9월 30일 업데이트

Prevent common AI report pitfalls — bug blending, inflated threat models, and generic language. Train Claude with your best past reports for concise, technical submissions. Based on Critical Thinking Bug Bounty Podcast Episode 166.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

ShulkwiSEC/bb-huge232026년 7월 11일 업데이트

Use when a task needs the judgment of a Data Entry Keyer — resolving an illegible or ambiguous source-document field before keying it, running key-verification (double-key) reconciliation on a batch, deciding whether a production-speed quota is compromising accuracy, or sampling a completed batch for a quality-control audit.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

wonsukchoi/domain-experts222026년 10월 19일 업데이트

Audit pharmaceutical QC laboratory operations -- OOS/OOT investigations, stability program trending, analytical method validation status, release testing optimization, and specification compliance..

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

tinh2/skills-hub-registry202026년 9월 5일 업데이트

Automatic quality control, linting, and static analysis after code modifications. Triggers on: lint, format, check, validate, types, static analysis. NOT for full build verification (see mk:verify); NOT for test coverage (see mk:testing).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

ngocsangyem/MeowKit152026년 7월 28일 업데이트

Comprehensive quality control for U.S. patent application filing documents. Use when the user asks to QC, check, validate, or review patent filing documents before submission to the USPTO. Performs 70+ automated and manual checks across specification, drawings, ADS, declaration, assignment, and power of attorney documents. Detects cross-document inconsistencies, formatting issues, missing required fields, and common errors.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

LeonardHope/Claude-Skill-for-Patent-Filing-Quality-Control122026년 7월 24일 업데이트

Data Labeling Specialist IA — Expert en annotation de données (outils, contrôle qualité, agreement inter-annotateurs, active learning)

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

ziri22/agency-roster62026년 7월 1일 업데이트

Strict SMILES validation, structural comparison, and modification verification. Catches invalid LLM-generated molecules.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

huang-sh/DeepScience42026년 7월 15일 업데이트

Draft and quality-check pages for the IPA Knowledge Hub in the site's house style. Use when creating a new .qmd Hub page from source material, adapting outside content into a Hub page, or reviewing an existing page for structure, tone, frontmatter, references, and Diátaxis fit. Replicates the quality-control workflow of IPA's Knowledge Hub Generator assistant.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

PovertyAction/ipa-research-data-science-hub32026년 10월 19일 업데이트

Build and run multi-agent content production teams on OpenClaw with single-repo architecture, symlink-based file sharing, role-specialized AGENTS.md, and automated review-fix-score loops. Use when: (1) Setting up a team of 3+ agents with writer/reviewer/scorer/fixer roles for content creation, (2) Creating a quality-controlled publishing pipeline, (3) Bootstrapping agent workspaces with symlinks and tool configs from scratch, (4) Running multi-round review→fix→score cycles until a quality threshold is met, (5) Debugging agent spawn permissions, tool-call loops, or symlink issues. Based on real production experience building a 6-agent content team (2026-03-30).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

aAAaqwq/openclaw-team22026년 6월 18일 업데이트