「eval」の検索結果

Analyzing contact tracing data — network reconstruction, transmission chains, and evaluating tracing performance.

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 text data with NLP — preprocessing, embeddings, topic modeling, sentiment, classification, and evaluation. Use when turning unstructured text into structured insight.

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。

Manage LLM context windows deliberately — budgeting, prioritization, summarization, and retrieval instead of dumping everything in. Use when prompts grow long, costs rise, or the model loses track of key details.

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。

Build with Cohere's enterprise AI — Command models, Embed embeddings, and Rerank for retrieval pipelines.

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。

Build a bookmark system you'll actually use: capture, tagging, retrieval, and regular pruning. Use when bookmarks pile up unfindable or you keep losing useful links.

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。

BCI design and evaluation — signal decoding, calibration, closed-loop paradigms, and performance metrics.

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。

Build AI chatbots end to end — conversation design, persona, retrieval grounding, escalation, and deployment. Use when creating a chatbot for support, sales, or internal assistance.

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。

Design and build LLM agents: ReAct loops, tool schemas, planning, memory, guardrails, evals, and human-in-the-loop. Use when building autonomous multi-step AI systems.

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。

Ship AI features to production — model selection, evals, latency/cost optimization, guardrails, monitoring, and iteration loops. Use when turning an LLM prototype into a reliable product feature.

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。

Architect persistent, searchable memory for agents — episodic, semantic, and procedural stores with retrieval, consolidation, and forgetting policies. Use when designing how an agent remembers across sessions.

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。

Build LLM applications with chain-style orchestration frameworks — prompts, chains, tool-calling agents, memory, and retrieval pipelines. Use when structuring multi-step LLM programs, adding tools to a model, or composing RAG systems in code.

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。

AI agent guidance — agent architecture, tool design, planning loops, guardrails, evaluation, and production agents.

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。

Practice AI safety across the lifecycle — risk assessment, alignment concepts, evaluation, deployment safeguards, and governance. Use when building or deploying AI systems responsibly.

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 UI with AI tools effectively: prompt structure, design-system grounding, iteration technique, and evaluating output quality. Use when using AI to create interfaces.

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。

Design memory for AI agents — short-term context, long-term stores, retrieval strategies, and memory-augmented reasoning. Use when an agent must remember facts, learn preferences, or stay coherent across sessions.

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。

Build data-centric LLM applications with indexing and retrieval frameworks — document ingestion, indices, query engines, and RAG pipelines. Use when the core problem is getting the right data in front of 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。

Sales enablement, technical presales and deal acceleration for B2B SaaS revenue teams. Use this skill when planning outbound campaigns, running discovery calls, building deal strategy, creating battle cards, writing proposals, responding to RFPs, preparing a product demo, scoping a proof of concept or pilot, answering a security questionnaire or the AI annex buyers now attach to it, executing sales sequences, coaching qualification, or deciding what the website's AI chat agent is allowed to say. Also triggers on: outbound, cold outreach, reply handling, reply classification, out-of-office replies, auto-replies counted as replies, our reply rate is inflated, prospect replied remove me, opt-out by reply, is this list ready to send, launch readiness, CRM segment outbound, we emailed a current customer, outbound hit an open opportunity, ownerless leads, prospects engaging our competitors, competitor connections, displacement list, is this personalization creepy, can we mention they visited our site, signal freshness, deal strategy, pipeline, battle card, objection handling, common objections, why do we keep hearing this objection, mine call transcripts for objections, objection register, proposal, RFP, discovery call, MEDDPICC, sales sequence, qualification, sales engineer, solutions engineer, presales, demo plan, demo script, POC, proof of concept, pilot success criteria, technical evaluation, technical win, security questionnaire, vendor security review, SOC 2 questionnaire, AI security questionnaire, AI annex, AI vendor due diligence, the buyer is asking if we train on their data, do you train on customer data, which model do you use, model provider sub-processor, AI subprocessor disclosure, where does inference run, can the customer turn the AI feature off, AI-CAIQ, CSA AI Controls Matrix, ISO 42001, ISO/IEC 42001, NIST AI RMF, EU AI Act Article 50, are we a provider or a deployer, AI feature disclosure, our model vendor changed and nobody told the buyer, technical objection, mutual action plan, MAP, close plan, mutual close plan, buyer enablement, the deal is stalled, deal stalled after the demo, how do I get this deal to close, close date keeps slipping, JOLT, buyer indecision, no-decision loss, website chatbot, chat widget, AI chat agent, AI SDR, inbound AI SDR, conversational marketing, live chat, what should our chatbot be allowed to say, our chatbot quoted the wrong price, the bot promised a discount, do we have to disclose it is AI, EU AI Act chatbot disclosure, chatbot handoff to sales, chat transcript review, prompt injection on our chatbot, Drift, Qualified, Intercom.

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。

Public relations, corporate communications, and analyst relations for B2B SaaS. Use this skill for earned media and press strategy, announcements and press releases, executive and crisis communications, media relationships and briefings, and the Gartner/Forrester/IDC analyst program including Magic Quadrant and Wave evaluation submissions. Also triggers on: PR, public relations, press release, earned media, media relations, journalist, embargo, announcement, crisis comms, corporate communications, analyst relations, AR, Gartner, Forrester, IDC, Magic Quadrant, Forrester Wave, analyst briefing, inquiry, newsjacking, rapid response, should we comment on this news story, expert commentary, reactive comment, source request, Qwoted, is this newsworthy.

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。

Deep codebase exploration, architectural research, and solution discovery. Use when investigating problems, understanding complex flows, or evaluating technical approaches without jumping straight into code mutation or TDD.

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。

Quality review of test files and manual evidence documents. Goes beyond existence checks — evaluates assertion coverage, edge case handling, naming conventions, and evidence completeness. Produces ADEQUATE/INCOMPLETE/MISSING verdict per story. Run before QA sign-off or on demand.

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。

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

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 a comprehensive milestone progress review including feature completeness, quality metrics, risk assessment, and go/no-go recommendation. Use at milestone checkpoints or when evaluating readiness for a milestone deadline.

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。

Read all open bugs in production/qa/bugs/, re-evaluate priority vs. severity, assign to sprints, surface systemic trends, and produce a triage report. Run at sprint start or when the bug count grows enough to need re-prioritization.

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 creating editable technical diagrams with draw.io / diagrams.net sources, including architecture diagrams, ERD, UML, sequence diagrams, flowcharts, ML model diagrams, official shape lookup, brand symbols, Graphviz auto-layout, codebase structure maps, .drawio validation, or draw.io CLI export fallback. Do not use for ordinary raster image generation, freehand sketches, interactive canvas/Three.js scenes, or decorative SVG animation. Chinese triggers include draw.io, diagrams.net, editable architecture diagrams, .drawio, ER diagrams, UML, sequence diagrams, auto layout, shape retrieval, code structure diagrams.

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。