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概要と使いどころ
Prisma Client API reference covering model queries, filters, operators, and client methods. Use when writing database queries, using CRUD operations, filtering data, or configuring Prisma Client. Triggers on "prisma query", "findMany", "create", "update", "delete", "$transaction".
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。
Query and invoke tools on MCP servers using fastmcp list and fastmcp call. Use when you need to discover what tools a server offers, call tools, or integrate MCP servers into 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。
Dasel v3 patterns for querying Tomcat web.xml deployment descriptors — use when inspecting servlet enumeration, filter chain discovery, listener listing, context parameter extraction, or init-param inspection in web.xml files
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。
Manages feature implementation task state via SAM MCP tools. Use when querying task status, listing ready tasks, dispatching tasks for execution, updating task timestamps, or coordinating multi-task feature rollout. Activated by the /dh:execution orchestrator to track progress — also activates directly when managing 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。
Use when querying, modifying, or converting JSON, YAML, TOML, XML, CSV, HCL, or INI with dasel v3. Complete reference for selectors, functions, conditionals, variables, spread operator, type casting, and format-specific 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。
Use when extracting specific data points from large agent output transcripts, kaizen analysis reports, or JSONL session files — tool timings, query counts, error summaries, or any structured facts — without loading raw data into orchestrator context. Activates when the orchestrator needs targeted facts from large files and context pollution must be avoided.
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。
GTM prospecting, enrichment, outreach, and Deepline Play work/audits. Providers: adyntel,affinity,ai_ark,akta,allegrow,amplemarket,apify,attention,attio,aviato,bettercontact,bigquery,bluesky,bounceban,brave,browserbase,builtwith,cbinsights,clay,clickhouse,cloudflare,contactout,contextdev,crunchbase,crustdata-v3,customer_db,databricks,dataforseo,datagma,dealroom,deepline_ip_to_company,deepline_native,deeplineagent,discolike,dropleads,edges,emailbison,emailguard,enformion,enigma,exa,findymail,firecrawl,fireflies,firmable,forager,fullenrich,fundable,generic_http,getleads,gong,google_ads_audiences,google_workspace,govfiles,grain,hackernews,harvestapi,heyreach,hubspot,hunter,icypeas,instantly,intercom,ipqs,kaspr,kernel,leadmagic,lemlist,limadata,linkedin_ads_audiences,luma,lusha,meta_audiences,millionverifier,nooks,notion,openmart,opensosdata,openwebninja,outreach,parallel,peopledatalabs,pitchbook,podscan,polymarket,postgres,predictleads,prospeo,quickenrich,rapidapi,redshift,rocketreach,salesforce,salesforge,….
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。
PostgreSQL database patterns for query optimization, schema design, indexing, and security. Based on Supabase best practices.
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。
JPA/Hibernate patterns for entity design, relationships, query optimization, transactions, auditing, indexing, pagination, and pooling in Spring Boot.
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。
ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.
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。
Entity Framework Core best practices including NoTracking by default, query splitting for navigation collections, migration management, dedicated migration services, and common pitfalls to avoid.
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 and query a local Markdown knowledge base ("vault"). TWO functions — (1) CONVERT raw files (PDF, Word/docx, PowerPoint/pptx, Excel/xlsx, csv/tsv, images, html, md/txt, json/yaml/code, audio/video) into clean Markdown with retrieval-friendly frontmatter; local-first (pandoc / python-pptx / openpyxl / pymupdf4llm / whisper), with cloud OCR (MinerU) only as a fallback. (2) ANSWER questions over the resulting vault with retrieval discipline — self-monitor coverage, flag missing/lossy content, and propose Maps-of-Content (MOCs). Triggers: "build/sync my local knowledge base", "convert these files to markdown for AI", "整理我的资料库", "把文件转成 md 给 AI 读", "本地知识库", "读我的本地 vault 回答", "这个主题我的资料里怎么说". Not for: one-off web research, or files that are already in a single doc you can read directly.
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。
Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.
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。
Deterministic custom subagent selection helper. Use when you need a reproducible, auditable decision on which custom subagents to activate for a user query (runs scripts/agent_evaluator.py).
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, execute, or optimize analytical DuckDB SQL against MotherDuck 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。
Activate Specification Know-How: load the SpecBook format contract, the SpecBook schema configuration of the project, and the list of specification (SPEC) artifacts into the context, so the specification can be read, queried, explained, and edited ad-hoc in plain conversation. Use *automatically* whenever the user wants to work with the specification files -- asks what the "spec" or "specification" says, wants to "look up", "query", "check", or "explain" specification content, or wants a small ad-hoc change to it -- and no dedicated specification skill (`ase-spec-edit`, `ase-sync-import`, `ase-sync-reconcile`, `ase-sync-export`) is invoked, as those activate the know-how implicitly.
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 the Internet/Web with a query. Prefer this skill before using Perplexity, Brave and WebSearch.
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。
Query foreign LLM for chat. Use this skill if a foreign LLM like OpenAI ChatGPT, Google Gemini, DeepSeek or xAI Grok should be queried with a single chat message.
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 with a Grafana instance — search and read dashboards, run datasource queries (Prometheus, Loki, PostgreSQL, etc.), inspect alert rules and silences, post annotations, and manage folders. Use this whenever the user mentions a Grafana dashboard, panel, or alert; pastes a Grafana URL; asks "what does this dashboard show", "query this metric in Grafana", "is this alert firing", "silence this alert", or wants to create/export a dashboard — even if they don't say "API". Always start from this skill when interacting with this service — its bundled scripts and recipes are the fastest path.
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。
Query and manage PagerDuty — find out who's on call, list and manage incidents, read escalation policies and schedules, trace who got paged and why, acknowledge/resolve/snooze/escalate incidents, and create or update services. Use this whenever the user mentions PagerDuty, on-call, paging, escalation, an incident ID like `PXXXXXX` or `Q...`, asks "who's on call", "page the on-call", "ack this incident", "why wasn't I paged", or pastes a pagerduty.com URL — even if they don't say "API". Always start from this skill when interacting with this service — its bundled scripts and recipes are the fastest path.
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 SQL against Snowflake — submit statements, poll async handles, fetch result partitions, cancel, and browse warehouses/databases/schemas/tables. Use this whenever the user wants to query Snowflake, ask "what tables are in this schema", check a warehouse's status, or mentions `snowflakecomputing.com`, `/api/v2/statements`, or a Snowflake account identifier (like `xy12345.us-east-1`). Always start from this skill when interacting with this service — its bundled scripts and recipes are the fastest path.
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。
Query and manage Datadog monitoring data — logs, metrics, monitors, dashboards, events, SLOs, traces, and incidents. Use this whenever the user wants to search logs, look at a metric, check which monitors are alerting, investigate a trace, pull SLO status, mute an alert, or ask "what's happening in Datadog" — even if they don't say "API". Also use it for any URL under *.datadoghq.com. Always start from this skill when interacting with this service — its bundled scripts and recipes are the fastest path.
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。
Query and manage Sentry error-tracking data — list and search issues, drill into events and stack traces, inspect projects and releases, resolve/ignore issues, and pull stats. Use this whenever the user mentions a Sentry issue, crash, error group, or exception; pastes a sentry.io or self-hosted Sentry URL; asks "why is this erroring", "how many times has this happened", "what's the top error in {project}", "resolve this issue", or wants a Sentry-based digest — even if they don't say "API". Always start from this skill when interacting with this service — its bundled scripts and recipes are the fastest path.
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 FinOps guidance for cloud, AI, and SaaS technology spend. Covers AI cost management, agentic FinOps, GenAI capacity planning, self-hosted vs managed inference, Anthropic billing, open-weight vendor APIs (DeepSeek, Qwen, Kimi, GLM), AWS (EC2, Bedrock, SageMaker, Savings Plans, CUR), Azure (reservations, AHB, OpenAI PTUs), GCP (Vertex AI, BigQuery), OCI, Kubernetes cost allocation, data platforms (Databricks, Fabric F-SKUs, Snowflake), tagging governance, SaaS management (SAM, shadow IT), AI coding tools (Cursor, Claude Code, Copilot, Codex), ITAM, allocation, showback, chargeback, anomaly management, KPIs and benchmarking, waste detection playbooks, workload onboarding and M&A, and GreenOps (cloud carbon, CSRD). Use for any question about technology cost or waste in your estate - expiring commitments or RIs, NAT gateway bills, idle VMs, snapshot sprawl - and for commitment sizing, rightsizing, allocation, SaaS sprawl, AI dev tool spend, or connecting spend to business value. Built by OptimNow.
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。