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概要と使いどころ
Create, manage, and query Databricks Genie Agents — curated, per-data natural-language agents (formerly Genie Spaces): build, export/import, migrate across workspaces, and ask questions of a *specific* Agent via the Conversation API. For general data questions or finding data across your workspace, use databricks-data-discovery (Genie One) instead.
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Discover, explore, and query Databricks data via Genie — the CLI equivalent of the Genie One MCP. MUST be invoked whenever the user asks to find or locate data ('what tables are in X', 'where does X live', 'which catalog/schema has Y'), answer a natural-language question about the data, or write a SQL query.
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。
Search multiple free stock photo sites simultaneously. Filter by license type, orientation, and color scheme.
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 to run real static analysis over a diff or repo before shipping — Semgrep, CodeQL, secret scanning, dependency CVEs — and triage the findings into what must be fixed now versus noise. Trigger before a release or PR merge, during a security review, or when the user asks to scan the code for vulnerabilities.
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 business spreadsheet models (.xlsx, .xlsm, or Google Sheets exported to .xlsx) for structural integrity errors and explains each fix -- budgets, forecasts, pricing models, commission calculators, FP&A packs, ops trackers, not only banking models. A bundled openpyxl script finds hardcoded numbers inside formulas, typed values pasted over formulas, inconsistent formulas across a row or column,
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 test coverage gaps and generate tests to improve coverage. Use when improving test coverage, finding untested code, or writing missing tests.
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。
Find out which clients and jobs actually make money -- allocate real costs (labor hours, materials, subs, overhead) against what each job billed, and rank every client by true margin. Most service businesses discover their biggest client is their least profitable.
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 targeted prospect lists by analyzing LinkedIn profiles, extracting job titles, companies, locations, and recent activity. Identifies decision-makers, tracks job changes for warm outreach, and enriches contact data. Use when users need to find prospects, build lead lists, or track decision-maker movements.
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。
Identifies upsell and cross-sell opportunities within existing customer accounts. Analyzes product usage, feature gaps, team growth, industry benchmarks, and competitive pressure to surface revenue expansion plays scored by potential, effort, and likelihood. Generates an expansion-playbook.md with account-by-account opportunities, recommended pitch, timing, and approach.
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 and sync design tokens between the source of truth (tokens.json, Figma variables export) and the code that should consume them (Tailwind config, CSS custom properties, theme files). Finds drift -- hardcoded values, orphan tokens, out-of-date copies -- and fixes it in the right direction.
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。
Cowork-style sweep of a folder of receipts, statements, and expense exports -- categorizes every transaction, matches receipts to statement lines, flags policy violations and anomalies, and outputs a clean expense report plus a findings memo.
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Point Cowork at a folder of medical bills and insurance EOBs -- matches every bill to its explanation of benefits, catches duplicate charges, balance-billing, and bills that ignore your insurance, then drafts the dispute letters and phone scripts. Most medical bills contain errors; this finds them.
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。
Uses Cowork-style multi-step analysis to process deal room documents -- contracts, financials, org charts. Outputs risk assessment, term comparison, key findings, and negotiation recommendations.
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 spending patterns and find savings. 50/30/20 rule, subscription audit, debt payoff strategies, emergency fund roadmap.
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 a codebase or business process for regulatory compliance across GDPR, HIPAA, SOC2, CCPA, and PCI-DSS. Scans for PII handling, data retention, encryption, access controls, audit logging, consent management, and data transfer issues. Generates a structured compliance report with findings, gap analysis, remediation steps, and evidence requirements.
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 LinkedIn profiles in target accounts to identify potential internal champions. Evaluates role, career path, mutual connections, interests, and suggests personalization approach. Use when you need to find who will champion your solution internally.
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 a website or UI and de-AI it — find the patterns that make it look template-generated (in both design and copy) and return specific, prioritized fixes that push it toward editorial, premium, human-crafted. Reviews layout, color, type, spacing, motion, accessibility, AND the words. Use after building or generating any frontend, or when a site looks "fine but generic" and you can't say why.
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。
Search and extract contact information for people or companies including names, phone numbers, emails, job titles, and LinkedIn profiles. Aggregates data from multiple sources and provides enriched contact details. Use when users need to find contact information, build prospect lists, or enrich existing contact data.
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。
Match bank transactions to invoices and surface unpaid / unmatched items in a Well workspace. Use when the user asks what's paid vs unpaid, to reconcile the bank, to find missing payments, or to match transactions to invoices.
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。
Detect domain from context and find appropriate team member
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。
Check agent-produced plans, tests, or code against the owner's actual intent. Find missing meaning, unrequested work, stale truth, unreachable decisions, unsupported completion claims, and implementation debt. Use before approval or merge.
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Report how many problems the two brains found: mutual review (the other model checks the work, from the peer-review records) and self-check (an agent finds its own error in its own conversation, judged by that agent's own model), side by side. Use when the owner asks whether the second agent or the reviews are worth it, or wants the week's review results.
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。
Export a research session into knowledge-intake compatible markdown. Use after a research session to hand findings to memory-palace.
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。
Merges, dedupes, ranks, and formats research findings into a report. Use after research agents return results from multiple channels to produce a ranked report.
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。