Results for “query skill”

Query Etsy products with multi-dimensional filters (keyword/URL, price, sales, favorites, reviews, listing date, category, handmade/vintage types, Pick/Bestseller/Raving tags). Trigger when user mentions Etsy products, Etsy listings, Etsy product sourcing, Etsy bestsellers, Etsy handmade, Etsy vintage, Etsy items, or Etsy product query — even if the tool name is not mentioned, as long as the need is to search products, view sales/price/tags, or filter items on Etsy.

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Query patent family information from Nexscope (Nexscope) by patent ID or publication number. Triggered when users mention patent family, patent family search, simple family, INPADOC family, Nexscope family, family patent lookup, patent equivalents, family members, cross-border related patent lookup, patent family, family patents, patent equivalents, cross-border patents, Nexscope, or INPADOC family. Even if the user does not explicitly say "patent family," this skill should be triggered whenever their need involves querying family members, equivalent patents, or related cross-border applications for one or more patents.

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Use Nexscope data to reverse-lookup traffic keywords for any Amazon ASIN, including organic ranking, ad ranking, search volume, traffic share, organic/paid scores, ABA TOP3 click concentration, click conversion rate, year-over-year search volume changes, and weekly/monthly time windows. Trigger when the user mentions ASIN keyword analysis, ASIN reverse lookup, traffic keyword research, organic ranking query, ad ranking query, keyword position tracking, Nexscope keyword data, competitor keyword peeking, viewing which keywords drive traffic to a product, analyzing keyword performance for a specific ASIN, time windows by week/month/recent N days, ASIN reverse keyword lookup, traffic keywords, organic ranking, ad ranking, search volume, Nexscope keywords, competitor keyword reverse lookup, click concentration, click-to-purchase conversion, week-over-week search volume. Even if the user does not explicitly mention "Nexscope", if their need involves finding keywords associated with a specific Amazon product (ASIN), this skill should also be triggered.

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Query and analyze Nexscope data for Amazon niche market insights, including market metrics, buyer reviews, competitive landscape, price trends, and growth trends. Trigger when the user mentions niche market analysis, market insights, niche market data, market competition analysis, brand concentration, new product launch success rate, out-of-stock rate, price trends, review insights, market demand score, niche market insights, market metrics, competition analysis, price trends, growth trends, Nexscope data, market intelligence, out-of-stock rate. Even if the user does not explicitly mention "Nexscope" or "niche market", if their need involves querying market-level intelligence for a specific Amazon niche market by market ID, this skill should also be triggered.

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Expert guide for Monte Carlo's push ingestion model. Use this skill whenever a customer or engineer mentions: pushing data to Monte Carlo, the IngestionService, pycarlo push APIs, build me a collection script, push metadata/lineage/query logs, invocation_id tracing, custom lineage nodes or edges, deleting push tables, or any question about why pushed data is not showing up. Also trigger when they ask to generate code that collects metadata, table schema, row counts, freshness, lineage, or query history from any data warehouse or data source and sends it to Monte Carlo. If the user mentions any warehouse, database, or data platform alongside any Monte Carlo topic, this skill is almost certainly relevant.

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Query Codex banked reset credits from the local Codex Desktop login state and report available reset count plus expiration times. Use when the user asks to check Codex reset credits, reset opportunities, reset chances, reset count, rate-limit reset credits, or expiration times; also use when the user provides a codex-reset-credits-skill or codex-reset-credits runbook link and asks Codex to query the result directly.

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Manage and tag music libraries with beets, the Python-based CLI tool that auto-tags audio files using MusicBrainz metadata. Import, organize, deduplicate, and query your music collection with a powerful plugin system and flexible query language.

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A source-backed ASE skill for Beekeeper Studio, the SQL editor and database manager for Linux, macOS, and Windows. It fits workflows that need a real client for querying, browsing tables, and working across PostgreSQL, MySQL, SQLite, SQL Server, and other supported databases.

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Query Chinese A-share, ETF, index, financial statement, valuation, capital-flow, and technical-indicator data through the AShareHub Python SDK and hosted API. Use this skill when an agent needs structured China market data as pandas DataFrames.

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AgentQL is TinyFish's web automation and extraction toolkit that layers a natural-language query system on top of live sites. Its Python and JavaScript SDKs integrate with Playwright and let agents target data and interface elements without depending on brittle CSS selectors alone.

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This skill should be used when the user asks to "buy token", "sell token", "swap token", "trade crypto", "check trade status", "query transaction", "scan tokens", "feed", "monitor chain", "query token", "token details", "check token safety", "list wallets", "show wallets", "my wallets", "AI scan", "AI扫链", "auto scan", "smart scan", "tweet scan", "推文扫链", "twitter scan", "onboarding", "get started", "check IP", "get IP", "IP whitelist", "查IP", "IP白名单", "launch token", "create token", "发币", "创建代币", "auto sell", "stop loss", "take profit", "trailing stop", "止盈止损", "移动止损", "holders", "top holders", "kol holders", "insider", "持仓", "持仓列表", or mentions trading on Solana/ETH/BSC/Base chains via XXYY. Enables on-chain token trading and data queries through the XXYY Open API.

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Query the Open Targets Platform GraphQL API for target-disease associations, genetic and clinical evidence, tractability and safety liabilities, target prioritisation metrics, known drugs and mechanisms of action, and disease ontology. Use this skill for target identification and validation, target-disease evidence review, druggability assessment, drug repurposing, and resolving gene, disease, and drug names to Ensembl, MONDO, and ChEMBL identifiers. Also trigger when a query mentions Open Targets, platform.opentargets.org, association scores, tractability buckets, or api.platform.opentargets.org.

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Query the ChEMBL database web services for measured bioactivity data, compound records and calculated properties, targets, assays, mechanisms of action, drug indications and warnings. Use this skill to build curated SAR or QSAR datasets for a target, look compounds up by SMILES, InChIKey, name, or ChEMBL id, run similarity and substructure searches, and check what chemistry is already known against a protein. Also trigger when a query mentions ChEMBL ids (CHEMBL...), pChEMBL values, IC50/Ki/Kd/EC50 retrieval, assay confidence scores, or ebi.ac.uk/chembl.

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State management decision tree for Vue 3 SPAs: ref/reactive locally, composables for shared logic, Pinia for app-wide state, provide/inject for DI, TanStack Query Vue for server state. Vuex pointer for Vue 2 legacy. Use this skill to: - Pick the right state tool for the data shape (local / shared / server / form). - Implement a Pinia store (Setup syntax preferred). - Use provide/inject correctly with InjectionKey<T>. - Set up TanStack Query Vue for server state. - Migrate from Vuex (with caution; only if BA asks). Do NOT use this skill for: - General SFC conventions (see vue-conventions). - Form state (see vue-forms — vee-validate handles that). - Routing state (see vue-routing — use vue-router useRoute). - Testing stores (see vue-testing).

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Flask-specific delta on top of python-foundation:sqlalchemy-patterns: Flask-SQLAlchemy extension setup, db.Model declarative models (3.x Mapped style and 2.x legacy db.Column), synchronous db.session lifecycle bound to the app context, Flask-Migrate integration. Used by flask-architect (model definitions) and flask-migrate-specialist (column finalization and migration). Activated automatically by flask-plugin/stack.md. Use this skill to: - Set up the SQLAlchemy and Migrate extensions with the app-factory pattern. - Write Flask-SQLAlchemy models with the db.Model base. - Query with db.session and manage the request-scoped session lifecycle. - Integrate Flask-Migrate for Alembic-based migrations managed via flask db commands. Do NOT use this skill for: - Framework-agnostic model, column, relationship, and querying rules — see python-foundation:sqlalchemy-patterns (load it first). - Flask routing and template/API patterns — see flask-plugin:flask-conventions. - Migration execution (flask db migrate, flask db upgrade) — that's flask-migrate-specialist's job.

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FastAPI-specific delta on top of python-foundation:sqlalchemy-patterns: async engine and AsyncSession lifecycle, get_db dependency injection, async-safe lazy loading rules, async Alembic env.py wiring. Used by fastapi-architect (model definitions) and alembic-specialist (column type finalization and migration generation). Activated automatically by fastapi-plugin/stack.md. Use this skill to: - Manage async database sessions with AsyncSession and async_sessionmaker. - Inject sessions into routes via the get_db() dependency. - Apply async-safe lazy loading (lazy="selectin" or "raise"; never sync lazy loads). - Integrate async Alembic env.py for migration autogeneration. Do NOT use this skill for: - Framework-agnostic model, column, relationship, and querying rules — see python-foundation:sqlalchemy-patterns (load it first). - FastAPI routing and Pydantic schemas — see fastapi-plugin:fastapi-conventions. - Alembic migration execution (that's alembic-specialist's job) — this skill covers definitions.

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Entity Framework Core patterns for ASP.NET Core projects: DbContext design, code-first entity configuration (Fluent API via IEntityTypeConfiguration<T>), relations (HasOne/HasMany, cascade/restrict/set-null), indexes and unique constraints, projection to DTOs (Select + AsNoTracking), avoiding N+1 (Include, AsSplitQuery), transactions, parameterized raw SQL (FromSql with FormattableString), and connection string from IConfiguration. Works alongside aspnet-core-plugin:aspnet-conventions. Use this skill to: - Design a clean DbContext with ApplyConfigurationsFromAssembly for scalable entity registration. - Configure entity properties (column types, max length, precision, nullability) via Fluent API. - Avoid N+1 query problems with explicit Include / projection to DTOs. - Use transactions correctly for multi-entity operations. - Write parameterized raw SQL safely when LINQ is not expressive enough. Do NOT use this skill for: - Migration generation commands (that is efcore-specialist's job in the database extra phase). - ASP.NET Core middleware, DI, or validation — see aspnet-core-plugin:aspnet-conventions. - C# language idioms — see csharp-foundation:csharp-conventions.

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Connect to and query ClickHouse (a local server or a ClickHouse Cloud service) from the terminal. For ClickHouse Cloud analytics, use the configured direct ClickHouse Query API endpoint with per-user CH_API_KEY and CH_API_SECRET credentials; do not use clickhousectl cloud service query. For local or host/port servers, use clickhousectl local client. Use when the user wants to run SQL against ClickHouse, explore schemas and tables, inspect Cloud services, or authenticate. For building a local dev environment or deploying to Cloud, defer to the official ClickHouse skills (see Scope).

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Build with Aurora DSQL — manage schemas, execute queries, handle migrations, diagnose query plans, load data, and develop applications with a serverless, distributed SQL database. Covers IAM auth, multi-tenant patterns, MySQL-to-DSQL and PostgreSQL-to-DSQL schema conversion, FK replacement code generation, OCC retry patterns, ORM migration (Django/Hibernate/Rails), DDL operations, query plan explainability, SQL compatibility validation, and bulk data loading. Triggers on phrases like: DSQL, Aurora DSQL, distributed SQL database, serverless PostgreSQL-compatible database, migrate to DSQL, DSQL query plan, DSQL EXPLAIN ANALYZE, DSQL ENUM, DSQL foreign key, DSQL OCC retry, DSQL multi-region, DSQL JSONB, DSQL GIN index, load into DSQL, load CSV into DSQL, bulk load DSQL, aurora-dsql-loader.

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Operate Railway infrastructure: sign up for or sign in to a Railway account, create projects, provision services and databases, manage object storage buckets, deploy code, configure environments and variables, manage domains, troubleshoot failures, check status and metrics, set up Railway agent tooling, and query Railway docs. Use this skill whenever the user mentions Railway, signing up, creating an account, registering, logging in, deployments, services, environments, buckets, object storage, build failures, agent setup, MCP, or infrastructure operations, even if they don't say "Railway" explicitly. Also invoke this skill when the user asks to be signed up, registered, or onboarded to Railway: do not refuse — drive them through the unauthed `railway up` flow (deploys + signs up on the fly) or `railway login` (which creates new accounts on the fly).

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Datadog provider for obz. Supports metrics (Datadog Query Language), logs (Datadog Log Query), and traces. Requires api-key and app-key configured under auth in config.yaml. Does not support metric labels, label-values, or series commands. This skill should be used when the user mentions "Datadog", "DD", "obz -p dd", Datadog Query Language, or needs to configure Datadog provider instances with regional endpoints.

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后首值福帮手服务跟进链路。定义了 skill_whoami → fbs_scene_pack_query → skill_consume 的完整服务链执行逻辑。

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Use the hyalo CLI instead of read/edit/grep/write when working with markdown (.md) files that have YAML frontmatter. This skill MUST be consulted whenever pi is working with markdown documentation directories, knowledgebases, wikis, notes, Obsidian-compatible collections, Zettelkasten systems, iteration plans, or any collection of .md files with frontmatter. Trigger this skill when: searching or filtering markdown files by content, tags, or properties; reading or modifying YAML frontmatter; managing tags or metadata across documents; toggling task checkboxes in markdown; getting an overview of a documentation directory; querying document properties or status fields; bulk-updating metadata across many markdown files; or when you find yourself repeatedly using read/edit/grep/write on .md files. Even if the user does not mention "hyalo" by name, use this skill whenever the task involves structured markdown documents with frontmatter. For pi sessions, ALWAYS use `--format text` for compact, LLM-friendly output.

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"Optimize SQL query performance using EXPLAIN analysis, indexing strategies, and common anti-pattern fixes. Use this skill when the user needs to speed up slow queries, design indexes, fix N+1 problems, or optimize database performance — even if they say 'this query is slow', 'optimize our database', 'which indexes do we need', or 'our dashboard takes 30 seconds to load'.".

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