Records and evaluates event-specific probability forecasts for agent outputs. NOT for validation or automatic acceptance.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
1.5천건 · 관련도순
Records and evaluates event-specific probability forecasts for agent outputs. NOT for validation or automatic acceptance.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Conduct Critical Decision Method (CDM) interviews to elicit expert reasoning strategies (L3 knowledge) from practitioners about specific challenging past incidents. Use when capturing expertise for skill development, preserving knowledge before practitioner departure, building post-incident learning artifacts, or investigating decisions in complex sociotechnical systems. Outputs structured incident reconstructions with cues, decisions, alternatives considered, and counterfactual analysis suitable for distillation into skills or training material.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Facilitate idea generation sessions that actually produce diverse, useful options instead of degenerating into the first plausible answer. Use for product ideation, feature exploration, problem-reframing, naming, design alternatives, strategic option-generation, or any task where the failure mode is "we picked the obvious thing too fast." Covers solo and group sessions, divergence/convergence discipline, technique selection (SCAMPER, Crazy Eights, How Might We, 6-3-5 Brainwriting, Reverse Brainstorming, Worst Possible Idea, Random Stimulus), facilitation moves for handling dominant voices and groupthink, and structured convergence to a shortlist with rationale. Outputs a session artifact with options generated, evaluation, shortlist, and the rejected-but-interesting list.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
This skill should be used when the user asks to "implement LLM-as-judge", "compare model outputs", "create evaluation rubrics", "mitigate evaluation bias", or mentions direct scoring, pairwise comparison, position bias, evaluation pipelines, or automated quality assessment.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Runs the morning maintainer standup for NemoClaw. Triages the backlog, determines the day's target version, labels selected items, surfaces stragglers from previous versions, and outputs the daily plan. Use at the start of the workday. Trigger keywords - morning, standup, start of day, daily plan, what are we shipping today.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Provides bidirectional translation (Chinese/English), grammar checking, and sentence polishing. Supports specific tense constraints, context-aware tone adjustment, and natural expression optimization. Outputs direct text without formatting.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Formats plain text or markdown files with frontmatter, titles, summaries, headings, bold, lists, and code blocks. Use when user asks to "format markdown", "beautify article", "add formatting", or improve article layout. Outputs to {filename}-formatted.md.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production. Use when optimizing prompts, improving LLM outputs, or designing production prompt templates.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Build with OpenAI's stateless APIs - Chat Completions (GPT-5, GPT-4o), Embeddings, Images (DALL-E 3), Audio (Whisper + TTS), and Moderation. Includes Node.js SDK and fetch-based approaches for Cloudflare Workers. Use when: implementing chat completions with GPT-5/GPT-4o, streaming responses with SSE, using function calling/tools, creating structured outputs with JSON schemas, generating embeddings for RAG (text-embedding-3-small/large), generating images with DALL-E 3, editing images with GPT-Image-1, transcribing audio with Whisper, synthesizing speech with TTS (11 voices), moderating content (11 safety categories), or troubleshooting rate limits (429), invalid API keys (401), function calling failures, streaming parse errors, embeddings dimension mismatches, or token limit exceeded.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug development, clinical research, and evidence synthesis.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Your brand voice locked across AI outputs. 15 cinematic styles. Design that does not read as AI.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Generate Excalidraw diagrams from natural language descriptions. Use when asked to "create a diagram", "make a flowchart", "visualize a process", "draw a system architecture", "create a mind map", or "generate an Excalidraw file". Supports flowcharts, relationship diagrams, mind maps, and system architecture diagrams. Outputs .excalidraw JSON files that can be opened directly in Excalidraw.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Build auditable Excel workbooks headless with openpyxl — blue/black/green cell conventions, formulas over hardcodes, named ranges, balance checks, sensitivity tables. Use for financial models, audit outputs, reconciliations.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Batch-generate Dreamifly images/videos from prompt queues. Use when the user asks to batch-generate images, edit images with references, create text-to-video or image-to-video, validate or estimate Dreamifly job cost, retry failed media jobs, or summarize Dreamifly outputs.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
批量调用 Dreamifly 生成并下载图片或视频。Use when the user asks to batch-generate images, edit images with references, create text-to-video or image-to-video, queue prompts, validate or estimate generation cost, retry failed media jobs, or summarize Dreamifly outputs.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Verifies complex outputs with Verify. API responses, scrubbing non-deterministic values.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Patterns and techniques for evaluating and improving AI agent outputs.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Automates the enrichment of raw indicators of compromise with multi-source threat intelligence context using SOAR platforms, Python pipelines, or TIP playbooks to reduce analyst triage time and standardize enrichment outputs. Use when building automated enrichment workflows integrated with SIEM alerts, email submission pipelines, or bulk IOC processing from threat feeds. Activates for requests involving SOAR enrichment, Cortex XSOAR, Splunk SOAR, TheHive, Python enrichment pipelines, or automated IOC processing.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
[BETA] Implement custom AEM Workflow Java components on AEM as a Cloud Service. This skill is in beta. Verify all outputs before applying them to production projects. Use when writing WorkflowProcess steps, ParticipantStepChooser implementations, registering services via OSGi DS R6 annotations, reading step arguments from MetaDataMap, accessing JCR payload via WorkflowSession adapter, reading and writing workflow metadata and variables, and handling errors with WorkflowException for retry behavior.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
[BETA] AEM Cloud Service expert skill — handle an explicitly-unbounded query (`p.limit=-1` predicate or JCR `setLimit(-1)`): bound it when capping is provably safe, otherwise flag it for human pagination. Use for "bound my query", "unbounded query", "query causing OOM", or a scan that flags `p.limit=-1`. Top CSO OOM cause: an unbounded result set traversed in a loop fills the heap and saturates the instance. The analyzer locates the explicit markers; the recipe triages each by how the result is consumed — single-result → 1, already-bounded list → N, iterate-all on the request path → escalate. Never silently cap a result the caller reads in full. This skill is in beta. Verify all outputs before applying them to production projects.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
[BETA] AEM Cloud Service expert skill — migrate javax.inject.@Inject fields in Sling Model (@Model) classes to injector-specific annotations (@ValueMapValue / @OSGiService / @SlingObject). Self-discoverable (scan for @Model classes with field-level @Inject); the replacement is chosen deterministically from each field's declared type. Use for "fix @Inject in HeroModel.java", "modernize my Sling Models", or when scanning an AEM project for @Inject misuse. Detailed decision table, companion-annotation handling, import management, and file-level skip policy are in recipe.md. This skill is in beta. Verify all outputs before applying them to production projects.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
[BETA] AEM Cloud Service expert skill — add explicit connect/read/socket timeouts to outbound HTTP clients constructed without one (Apache HttpClient 4.x/5.x, OkHttp, JDK java.net.http.HttpClient), including the JDK per-request read timeout on HttpRequest. Use for "add HTTP timeouts", "this external/outbound call has no timeout", or a scan that flags a timeout-less client. Highest-frequency CSO outage cause: a client on default (effectively infinite) timeouts holds request threads on a slow upstream until the Jetty pool saturates and the site goes down. The analyzer locates timeout-less construction sites; mechanical per-library remediation applies CSO-backed default timeouts (recipe.md). This skill is in beta. Verify all outputs before applying them to production projects.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
[BETA] AEM Cloud Service expert skill — upgrade outdated Maven dependencies in pom.xml, both literal <version> and same-pom ${property} shapes. Use for "update my aem-sdk-api", "upgrade mockito", or scanning a project for stale dependency versions. Discovery can find <dependency> blocks but "outdated" needs a target version, which the user supplies. Pattern A/B locators and editing strategy are in recipe.md. This skill is in beta. Verify all outputs before applying them to production projects.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Bulk-retouch a folder of portrait photos using Adobe tools — designed for wedding photographers and event photographers who need fast, walk-away batch processing. Use this skill when the user says "retouch my photos", "batch process these portraits", "process my wedding photos", "clean up this folder of images", "run my headshots through Adobe", or uploads/selects a folder of photos and wants them polished and ready to review. Automatically applies auto-straighten, auto-tone, and auto-light to every image. Outputs a preview grid and download folder. Access: 🔐 Signed-In required | Gen AI: ❌
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.