データ・AIのスキル

Entry point for 9Router — local/remote AI gateway with OpenAI-compatible REST for chat, image, TTS, embeddings, web search, web fetch. Use when the user mentions 9Router, NINEROUTER_URL, or wants AI without writing provider boilerplate. This skill covers setup + indexes capability skills; fetch the relevant capability SKILL.md from the URLs below when needed.

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。

Chat / code generation via 9Router using OpenAI /v1/chat/completions or Anthropic /v1/messages format with streaming + auto-fallback combos. Use when the user wants to ask an LLM, generate code, summarize text, or run prompts through 9Router.

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。

Work on Composio documentation content, Fumadocs configuration, changelogs, docs automation prompts, docs decisions, ADR-style records, and docs review guidance. Use for files under docs/, documentation workflows, or requests to record or update a docs decision. Do not use for SDK runtime changes unless docs are the main deliverable.

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 an agent needs to drive a real Chrome window via opencli — inspect a page, fill forms, click through logged-in flows, or extract data ad-hoc. Covers the selector-first target contract, compound form fields, stale-ref handling, network capture, and the agent-native envelopes the CLI returns. Not for writing adapters — see opencli-adapter-author for that.

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 CSV files in /mnt/data and return concise numeric summaries.

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。

Expert prompt engineering skill that transforms Claude into "Alpha-Prompt" - a master prompt engineer who collaboratively crafts high-quality prompts through flexible dialogue. Activates when user asks to "optimize prompt", "improve system instruction", "enhance AI instruction", or mentions prompt engineering tasks.

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。

Zoom Virtual Agent Android integration via WebView. Use for Java/Kotlin bridge callbacks, native URL handling, support_handoff relay, and lifecycle-safe embedding.

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。

Runs the owner's Monday morning briefing as a two-link chain — business-pulse for the cross-connector snapshot of cash, sales, and pipeline, and report-builder for any saved KPI reports the owner has already defined — then reads the week ahead straight from Calendar and mail and merges all three parts into a single one-page Monday document, delivered per the owner's stored output preference. Requires no connectors and degrades gracefully, building from whatever of the ledger (MYOB, NetSuite, QuickBooks, Xero, or Zoho Books), Calendar, DocuSign, Expensify, Gmail or M365, HubSpot, PayPal, Ramp, RingEx Chat, Shopify, Slack, Stripe, and TikTok Ads is connected, or from pasted and uploaded data when none are. Trigger on "Monday brief," "start my week," "what do I need to know this week," "weekly briefing," "catch me up before Monday," or when the owner schedules a recurring start-of-week 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。

Finds grant and solicitation opportunities the organization actually qualifies for, runs a hard go/no-go before anyone starts writing, drafts the application or response from past submissions and real program data, and tracks every deadline and reporting obligation that follows an award. Built for nonprofits, government contractors, and education, and it filters daily feeds like SAM.gov or DIBBS down to the handful worth bidding. Runs on Google Drive or M365 with DocuSign and Calendar deepening it, and works from uploaded past submissions plus web research when nothing is connected. Use this whenever a funding or bidding opportunity is in play — including "find grants we qualify for," "should we bid this," "draft the response to this RFP," "we've got 50 solicitations to filter," "what's due on the federal grant," or "help me write the proposal narrative."

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。

Turns a plain-English description of a recurring report into a real, repeatable report — defines the metrics, pulls them from whatever data sources are connected, delivers a chat summary plus an XLSX workbook, and saves the definition so the same report reruns on demand or on a schedule. Handles anything from "sales by location versus last year" to AR aging to labor as a percentage of revenue. Works fully from an uploaded CSV or XLSX when no connector is available. Use this whenever the owner asks for a report, dashboard, KPI pack, metrics summary, or recurring numbers — including phrasings like "can you track this every week," "I need to see these numbers monthly," "build me a report on," "same report as last time," or "put together a KPI dashboard." Reach for it even when the owner names the metrics without using the word 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。

Delivers the owner's custom recurring report pack on a set cadence — runs the saved report definition from report-builder, wraps it in a business-pulse snapshot so the numbers have context, and hands over one chat summary plus the workbook. Defined once, then delivered on schedule without being asked again. Runs on any single connected data source, or entirely from an uploaded CSV or XLSX. Use it when the owner asks for their report pack, their weekly or monthly numbers, "send me the usual report," "run my report pack," "set this up to come every Monday," or "I want these numbers on a schedule."

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。

Gets Claude talking to a tool nobody built an official connector for. Works out what the system is, checks the Claude connector directory for an existing connector first, and when there isn't one connects the tool through Zapier — never by hand-building against a raw API — with credentials handled safely and approval gates on anything that writes. This is what turns "my ERP isn't supported" into an afternoon. Use this whenever the owner names a tool that isn't connected — including phrasings like "can you connect to my," "make my tools talk to each other," "there's no API for this," "pull data out of my field service software," "I use ServiceTrade and it's not on the list," or "is there any way to get at this data." Reach for it whenever an unsupported system is blocking something else.

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 customer deck, one-pager or leave-behind from your account data, call notes and approved materials, with no made-up numbers. Use when the user asks for a sales asset, one-pager, deck, leave-behind, "create an asset for [prospect]", or "make something for [account]".

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。

360-degree view of an account - CRM data, recent email threads, docs, transcripts, and internal chat chatter, synthesized into one brief. Use when the user asks "tell me about [account]" (an existing customer; for a prospect, account-research), "account context for [name]", "what's going on with [account]", or "catch me up on [account]".

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。

Stage-by-stage pipeline health check - coverage, aging, conversion, and at-risk deals - from CRM opportunity data. Use when the user asks "review my pipeline", "pipeline health", "where's my pipeline stuck", "weekly pipeline review", "which deals should I focus on this week", "any stale or stuck deals", "which deals have past close dates", "which deals are single-threaded", or "check my pipeline coverage against my number".

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 marketing performance report with key metrics, trend analysis, wins and misses, and prioritized optimization recommendations. Use when wrapping a campaign, when preparing weekly, monthly, or quarterly channel summaries for stakeholders, or when you need data translated into an executive summary with next-period priorities.

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 contextual briefings for legal work — daily summary, topic research, or incident response. Use when starting your day and need a scan of legal-relevant items across email, calendar, and contracts, when researching a specific legal question across internal sources, or when a developing situation (data breach, litigation threat, regulatory inquiry) needs rapid context.

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 compensation — benchmarking, band placement, and equity modeling. Trigger with "what should we pay a [role]", "is this offer competitive", "model this equity grant", or when uploading comp data to find outliers and retention risks.

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 a compliance check on a proposed action, product feature, or business initiative, surfacing applicable regulations, required approvals, and risk areas. Use when launching a feature that touches personal data, when marketing or product proposes something with regulatory implications, or when you need to know which approvals and jurisdictional requirements apply before proceeding.

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。

Reconcile accounts by comparing GL balances to subledgers, bank statements, or third-party data. Use when performing bank reconciliations, GL-to-subledger recs, intercompany reconciliations, or identifying and categorizing reconciling items.

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。

Write correct, performant SQL across all major data warehouse dialects (Snowflake, BigQuery, Databricks, PostgreSQL, etc.). Use when writing queries, optimizing slow SQL, translating between dialects, or building complex analytical queries with CTEs, window functions, or aggregations.

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。

Apply statistical methods including descriptive stats, trend analysis, outlier detection, and hypothesis testing. Use when analyzing distributions, testing for significance, detecting anomalies, computing correlations, or interpreting statistical 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。

QA an analysis before sharing -- methodology, accuracy, and bias checks. Use when reviewing an analysis before a stakeholder presentation, spot-checking calculations and aggregation logic, verifying a SQL query's results look right, or assessing whether conclusions are actually supported by the 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。

Deep learning for single-cell analysis using scvi-tools. This skill should be used when users need (1) data integration and batch correction with scVI/scANVI, (2) ATAC-seq analysis with PeakVI, (3) CITE-seq multi-modal analysis with totalVI, (4) multiome RNA+ATAC analysis with MultiVI, (5) spatial transcriptomics deconvolution with DestVI, (6) label transfer and reference mapping with scANVI/scArches, (7) RNA velocity with veloVI, or (8) any deep learning-based single-cell method. Triggers include mentions of scVI, scANVI, totalVI, PeakVI, MultiVI, DestVI, veloVI, sysVI, scArches, variational autoencoder, VAE, batch correction, data integration, multi-modal, CITE-seq, multiome, reference mapping, latent space.

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。