Lightweight guidance for using the Upstash Workflow SDK to define, trigger, and manage workflows. Use this Skill whenever a user wants to create workflow endpoints, run steps, or interact with the Upstash Workflow client.
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。
1,283 件 ・ 関連度順
概要と使いどころ
Lightweight guidance for using the Upstash Workflow SDK to define, trigger, and manage workflows. Use this Skill whenever a user wants to create workflow endpoints, run steps, or interact with the Upstash Workflow client.
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 adding authentication, handling user input, working with secrets, creating API endpoints, or implementing payment/sensitive features. Provides comprehensive security checklist and 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。
Decide and implement how to support a new LLM provider or agent engine in AWF - either as a proxied provider (api-proxy adapter) or a direct-API engine (domain allowlist only), e.g. Cursor, Aider, or any tool that calls its own endpoint.
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。
Odoo 19 development knowledge base with 18 specialized guides covering Actions (ir.actions.*, cron jobs, server actions), Controllers (HTTP routing, endpoints, auth types), Data files (XML/CSV records, shortcuts, noupdate), API Decorators (@api.depends, @api.constrains, @api.ondelete, @api.onchange, @api.model, @api.private), SQL Constraints (models.Constraint replacing _sql_constraints), Database Indexes (models.Index), Module development (manifest, wizards, reports), Field types (Char, Text, Monetary, relational fields), Manifest configuration (__manifest__.py, dependencies, asset bundles), Mixins (mail.thread, mail.activity.mixin, mail.alias.mixin, utm.mixin), ORM Model methods (search, CRUD, domain filters, recordsets, CamelCase model naming), Migration scripts (pre/post/end hooks, data migration), OWL frontend components (hooks, services, lifecycle), Performance optimization (N+1 prevention, batch ops, _read_group), QWeb Reports (PDF/HTML, paper formats, barcodes, t-out), Security/ACL (record rules, field permissions, privilege-based groups, @api.private), Testing (TransactionCase, HttpCase, mocking, query count assertions), Transactions (savepoints, UniqueViolation, serialization failures), Translations (i18n, PO files, translatable fields), XML Views (list/form/search, kanban card templates, xpath inheritance, QWeb templates). Use when writing, reviewing, or debugging any Odoo 19 Python or XML code, creating or modifying modules, fixing performance issues, or looking up Odoo 19 API patterns and best practices. Includes CSS/SCSS asset authoring and review for Odoo addons.
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。
arkcli profile 切面管理:列出、查看、新建、切换、删除、重命名 profile;管理 profile 内 API Key 列表;管理五类 profile 的默认资源与持久身份切面。也负责判断 Token 额度包/资源包应继续使用 platform profile 与 `/api/v3`,不能因「套餐」或价格字样误判为 Agent Plan/Coding Plan。临时 API Key/Base URL/Endpoint 调用不写回 profile,按 arkcli-shared 的 execution-context 契约执行。旧 config 子命令已 deprecated。
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。
查询火山引擎 ARK 拆分账单明细(结算金额、Token 用量计费),支持按账期月、月范围、Endpoint、API Key、产品编码等维度过滤。当用户问账单、花了多少钱、对账、账期、按 EP / API Key 拆账、按产品拆账、月度账单、出账明细时使用。注意 billing 跟 usage stats 不同:stats 出推理量(近实时),billing 出结算金额(T+1 出账,财务口径)。
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 keyword cannibalization across blog posts by extracting primary keywords from titles and headings, clustering semantically similar targets, and flagging posts competing for the same search intent. Supports local-only mode (grep-based) and DataForSEO API mode (Page Intersection endpoint at ~$0.01/call). Outputs severity-scored report with merge or differentiate recommendations. Use when user says "cannibalization", "keyword overlap", "competing pages", "duplicate keywords", "cannibalize".
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。
Draft a reply or a value-add quote tweet for a specific X (Twitter) tweet from its URL. Use to reply in a thread, answer a creator, or quote-tweet with added value. Parses the tweet URL, reads pasted context, decides reply vs quote tweet, and drafts 1-3 variants in your voice. X has no LinkedIn-style 2-level thread flattening, so a reply is just a tweet. Publora has no reply endpoint, so the draft is returned as a copy-paste block to post yourself. Not for top-level posts (use x-post-writer).
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 the user wants to know if something works — the answer requires running code, not analyzing it. Output is a verdict backed by evidence: passed, failed, or broken. Primary triggers: 'run the tests', 'does X still work after my change?', 'did the merge break anything?', 'verify the fix worked', 'check if the endpoint returns X', 'confirm nothing regressed', 'run tests/unit/test_foo.py', 'let me know the results', 'make sure my changes didn't break anything'. Hard stops — do NOT use for: reviewing test code for quality/coverage gaps, debugging why test infrastructure/databases/seed scripts are misbehaving, writing or fixing tests, diagnosing root causes of unexpected behavior. The deciding question: is the user asking for the result of executing something, or asking for help understanding/analyzing/improving something? If it's the latter, use diagnose or review-code instead.
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 for any Python backend work in this project: building FastAPI endpoints, writing service functions, defining Pydantic/SQLModel schemas, running Alembic migrations, or debugging 422 errors. Essential for authentication and authorization patterns — setting up get_current_user, is_superuser checks, admin-only guards, role-based access, and dependency injection chains like Depends(). Also covers middleware, background tasks, async SQLAlchemy sessions, ORM relationship loading, and request/response design. Activate whenever the question involves Python API code, FastAPI patterns, or backend architecture in this codebase. Not for frontend, Docker, CI/CD, or infrastructure.
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。
Authoritative reference for the neo4j-agent-memory Python package — a graph-native memory system for AI agents built on Neo4j — and for the hosted service (NAMS) at memory.neo4jlabs.com. Use this skill whenever the user mentions neo4j-agent-memory, agent memory with Neo4j, context graphs, the POLE+O model, MemoryClient/MemorySettings, the memory MCP server, or any of the framework integrations (LangChain, PydanticAI, CrewAI, AWS Strands, Google ADK, Microsoft Agent Framework, OpenAI Agents, LlamaIndex). Also use when the user mentions the hosted service at memory.neo4jlabs.com, NAMS, the Neo4j Agent Memory Service, the `nams_` API key prefix, or the hosted MCP endpoint. Also use when writing documentation, blog posts, tutorials, PRDs, or code samples for the project, when comparing agent memory approaches, or when positioning graph-native memory against vector-only approaches — even if the user doesn't explicitly name the package.
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 Neo4j Aura Agents via the v2beta1 REST API — create, list, get, update, delete, and invoke Aura agents backed by an AuraDB instance. Use when configuring Aura Agent tools (CypherTemplate, SimilaritySearch, Text2Cypher), setting system prompts, deploying agents to REST or MCP endpoints, invoking agents with natural language queries, or generating evaluation datasets (max 50 questions) for the Aura Agent evaluation feature. Covers OAuth2 auth, organization/project scoping, tool parameter schemas, and InvokeAgentResponse format. Does NOT cover AuraDB instance provisioning — use neo4j-aura-provisioning-skill. Does NOT cover vector index creation — use neo4j-vector-index-skill.
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。
Neo4j Graph Data Science (GDS) embedded plugin via Python client or Cypher — covers graphdatascience client 2.x, GraphDataScience, gds.graph.project.native, gds.graph.project.cypher, snake_case endpoints, graph catalog operations, stream/stats/mutate/write modes, memory estimation, PageRank, Louvain, WCC, FastRP, KNN, Node Similarity, ML pipelines, and cleanup. Use for Aura Pro, self-managed, local, or offline Neo4j DBMS with the GDS plugin installed. Does NOT cover Aura Graph Analytics GDS Sessions, AuraGraphDataScience, GdsSessions, gds.graph.project.remote, or AuraDB Cypher API projection/session management — use neo4j-aura-graph-analytics-skill. Does NOT handle Cypher authoring — use neo4j-cypher-skill. Does NOT cover driver setup — use neo4j-driver-python-skill or other driver skill.
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。
Serverless Aura Graph Analytics (AGA) GDS Sessions — covers GdsSessions, AuraGraphDataScience, AuraAPICredentials, DbmsConnectionInfo, SessionMemory, get_or_create, remote graph projection with gds.graph.project.cypher and gds.graph.project.remote, gds.graph.project.native, gds.graph.construct, graphdatascience client 2.0 session endpoints, async compute and gds.jobs, AuraDB Cypher API memory/sessionId projection, algorithms, write-back, and session lifecycle. Use for AuraDB-connected, self-managed Neo4j, or standalone DataFrame/Spark session workloads. Does NOT cover the embedded GDS plugin on Aura Pro or self-managed Neo4j — use neo4j-gds-skill. Does NOT handle Cypher authoring — use neo4j-cypher-skill. Does NOT cover Snowflake Graph Analytics — use neo4j-snowflake-graph-analytics-skill.
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。
Guide for Kimix opencode-style HTTP server (FastAPI + SSE), including route definitions, builtin endpoints, and app.post usage.
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。
Guide for the Kimix HTTP serve system — FastAPI backend + TypeScript/Vite frontend. Use when adding new backend endpoints, modifying the session manager, changing the frontend API client, or understanding how data flows from backend to UI. Covers dummy_app.py, dummy_session_manager.py, sse_cli.py, and src/app/.
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 the diff adds or changes an endpoint, resolver, RPC, job or query that takes an object id, a role check, a request binding or a tenant filter - BOLA/IDOR, function-level authorization, mass assignment and tenant scoping
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 diff or design adds or changes a DB migration, an endpoint or DTO, an event payload, or a shared type with consumers
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 in code_review when the diff touches input handling, auth, queries, files, outbound requests, secrets, dependencies or LLM calls, and in analysis for any new endpoint or data flow
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 building cases for any input, form, endpoint or state change - boundary values, invalid and hostile data, authz and concurrency cases with a worked example
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 adds or changes an HTTP endpoint, its request/response shape, status codes, auth or error format - the request matrix, curl templates and what counts as a contract break
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 criterion mentions speed or limits, or the change touches a list, query, endpoint or page that could get slower - timing loops, the N-vs-10N data check and Lighthouse on a production build
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 you design or change an endpoint's errors, status codes, pagination, idempotency or concurrency behaviour — one error shape, the status-code table, bounded lists, safe retries
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 before handing off any change to an endpoint, job or migration — start the service from the task branch and exercise the change with real requests, real logs and real DB side effects
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。