「teams」の検索結果

Use when frontend work needs to communicate data, action, state, permission, validation, or business-rule needs to backend teams without dictating endpoint design, field names, database shape, or implementation details; Chinese triggers include front-end and back-end requirements handover, back-end requirements, API requirements clarification, data requirements description.

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。

Use when a task needs the judgment of a systems engineer/architect working at the whole-program level — decomposing requirements across hardware/software/network subsystems, writing or reviewing an interface control document (ICD), making a build-vs-buy tradeoff for a subsystem, or tracing a verification failure back through the requirements baseline. Distinct from a software engineer (owns one service's code) or DevOps/SRE (owns operational reliability) — this role owns the technical baseline for a whole system-of-systems and is accountable when subsystems built by different teams or vendors don't fit together.

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 a task needs the judgment of a Chief Technology Officer — deciding build vs buy for a core system, choosing whether an architecture bet is worth a full rewrite, sizing an SLA/uptime commitment against engineering cost, structuring engineering teams around a product roadmap, or writing the technical risk section of a board update.

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 professional Discord servers — community structure, moderation, events, bots, and engagement for teams and audiences.

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 role-based agent teams with CrewAI — agents, tasks, crews, and collaboration patterns for complex workflows.

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。

Integrate headless CMSs: content modeling, APIs, previews, webhooks, and editorial workflows. Use when content teams need to publish without developers.

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。

Coordinate teams of role-based agents — role definitions, task delegation, sequential and hierarchical workflows, and shared memory. Use when a job naturally splits into specialist roles collaborating.

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。

Plan and track team projects and tasks in Asana. Use to assign work to owners, update due dates and status, set task dependencies, and review project progress, comments, teams, and workspaces through Asana's official MCP server.

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 cybersecurity threat intelligence, triage security alerts, classify IOCs, map attacks to MITRE ATT&CK kill chain, reduce false positives, and attribute threat actors. Covers SIEM tuning, threat feed quality, detection coverage gaps, Diamond Model analysis, and strategic threat assessments for SOC and incident response teams.

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。

Audit ML experiment tracking infrastructure for reproducibility gaps, parameter logging completeness, metric capture, artifact management, and pipeline orchestration. Covers MLflow, Weights and Biases, DVC, Sacred, Neptune, Hydra configs, model registries, and produces a reproducibility scorecard (0-30) with actionable fixes for data science teams.

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。

Surface and visualize hidden dependencies blocking delivery. Use when the user says "map our dependencies", "what's blocking what", "dependency audit", "why are teams blocked", "we have a bottleneck", "draw out the dependencies", or asks to identify cross-team blockers - even if they don't explicitly say "dependency mapping". Based on "Making Work Visible" by Dominica DeGrandis (time theft, invisible work, flow blockers).

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。

Navigate a new leadership role using Michael Watkins' First 90 Days 30/60/90 framework. Use when someone says "I just started a new role", "I'm starting as a new manager", "I joined a new company as a leader", "I was just promoted", "how do I onboard as a leader", "what should I do in my first 30 days", "I inherited a team", "I need a 90 day plan", or "I'm new to this team". Also trigger when someone describes feeling overwhelmed in a new leadership role, unsure where to start, or tempted to make changes too quickly before they've listened. Applies to first-time managers, leaders joining new companies, and leaders moving into new functions or teams within the same company.

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。

Identify expansion signals and structure upsell or cross-sell conversations using land-and-expand and Net Revenue Retention principles. Use when user says "upsell", "expansion", "cross-sell", "grow the account", "increase ARR", "find expansion opportunities", "NRR improvement", "upgrade conversation", "add-on", "renewal and expand", or "land and expand" - even if they don't say "expansion discovery" explicitly. Applies to CSMs managing account growth or CS teams building expansion playbooks.

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。

Delegate tasks to ANY CLI agent (claude, codex, aider, ...) running in a detached tmux session, with a race-safe done-signal protocol and multi-turn iteration. Use when delegating work to a non-Claude CLI agent, when the user says "tmux delegate", "run agent in tmux", "delegate to codex/aider", or when executor work should run in an observable background terminal instead of the Agent tool.

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。

Professional finance research toolkit — backtesting (11 engines + benchmark comparison panel), factor analysis, Alpha Zoo (478 pre-built alphas across qlib158/alpha101/gtja191/academic/fundamental), options pricing, 90 finance skills, 30 multi-agent swarm teams, Trade Journal analyzer, and Shadow Account (extract → backtest → render) across 29 market-data sources (tushare, yfinance, okx, binance, akshare, baostock, tencent, mootdx, ccxt, futu, mt5, tickerall, local, eastmoney, sina, stooq, yahoo, pykrx, india_broker, qveris, longbridge, nobitex, wallex, plus optional-key finnhub/alphavantage/tiingo/fmp/gildata).

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 designing, generating an MVP blueprint for, auditing, troubleshooting, refactoring, or explaining an agentic harness for any domain. Covers provider-neutral agent architecture for OpenAI, Anthropic, and OpenAI-compatible APIs: agent loops, tool design, record provenance, interactive presentation, user-memory lifecycles, environment-adaptive tools, speculative tool execution, late-bound capabilities, permissions, system prompts, planning, goals, always-on agents and durable runtime, adaptive agent teams, context compaction, memory, skills, MCP/external connectors, public-board communications, hardware agents and board deployment, self-refining recursive harnesses, programmable context, continual refinement, observability, evals, prompt caching, agent-legible environments, feedback loops, and safety.

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。

Configuring Salesforce Email-to-Case: Standard vs On-Demand mode selection, routing address setup, email threading via Lightning tokens, auto-response rules, attachment limits, and per-address case field defaults. Trigger keywords: email-to-case, routing address, on-demand email-to-case, email threading, case from email, email agent, routing address setup, Case.settings-meta.xml, EmailToCaseRoutingAddress, emailServicesAddress, isVerified, caseOrigin, enableThreadTokenInBody, useEmailHeadersForThreading, overEmailLimitAction, unauthorizedSenderAction, enableE2CAttachmentAsFile, saveEmailHeaders, newEntityRecordType, casePriority, EmailMessage.EmailRoutingAddressId, auto-response loop. NOT for the wider case layer (queues, escalation rules, case teams, entitlements) - use admin/case-management-setup. NOT for routing case work items to agents after creation - use admin/omni-channel-routing-setup. NOT for the email templates or letterheads themselves - use admin/email-templates-and-alerts.

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。

Declarative setup of Compliant Data Sharing (CDS) in Financial Services Cloud: enabling CDS per-object in IndustriesSettings, configuring OWDs, creating CDS permissions, adding the Financial Deal Participants related list, and defining Participant Roles. Trigger keywords: ethical walls, compliant data sharing setup, FSC sharing model, isolate banking teams, participant roles. NOT for participant record DML from Apex — use apex/fsc-compliant-sharing-api. NOT for the FSC sharing design decision — use architect/fsc-architecture-patterns.

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。

Git workflow patterns including branching strategies, commit conventions, merge vs rebase, conflict resolution, and collaborative development best practices for teams of all sizes.

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。

Engineering operating model for teams where AI agents generate a large share of implementation output.

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。

Score, monitor, and troubleshoot AI agent fleets in production. Built for ops teams running 1-100+ 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。

Design, build, deploy, and operate production AI agent systems — single agents, multi-agent teams, and autonomous swarms. Complete methodology from agent architecture through orchestration, memory systems, safety guardrails, and operational excellence.

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。

You are the Accessibility Engineering Engine — a complete WCAG compliance, inclusive design, and digital accessibility system. You help teams build products that work for everyone, pass audits, and...

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。