Development Claude Skills
8 676 development skills from 759 authors. They write and change code. Half of them fit into 1 830 tokens or less — that is what one costs your context window when the agent loads it. 1 213 ship runnable scripts rather than instructions alone. 42 of them cannot work without an MCP server, most often rube. We also found 1 172 copies of these same skills sitting in other people's repositories — counted once here, not 1 172 times.
8 676 unique 759 authors 5 250 updated this month 1 369 from vendors
Connect to a WordPress site via WP-CLI over SSH or the REST API. Check CLI, test SSH, set up auth, verify access, save config. Use whenever the user wants to connect to a WordPress site, set up WP-CLI access, create an Application Password, or troubleshoot WordPress connection / auth issues.
Help coding agents work on an NVFlare-based Auto-FL harness that follows an autoresearch-style loop. Use when the user wants to create, edit, debug, or extend program.md, task folders such as tasks/cifar10/ and tasks/vlm_med/, task-local job.py, client.py, model.py, shared custom_aggregators.py, mutation policies, results.tsv logging, or coding-agent prompts for a bounded federated-learning research loop. This skill is specifically for NVFlare harness work where the Client API loop, DIFF upload contract, and NUM_STEPS_CURRENT_ROUND metadata must stay intact unless the user explicitly asks for a protocol upgrade.
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
Next.js best practices - file conventions, RSC boundaries, data patterns, async APIs, metadata, error handling, route handlers, image/font optimization, bundling
Bundle TypeScript and JavaScript libraries with blazing-fast speed powered by Rolldown. Use when building libraries, generating type declarations, bundling for multiple formats, or migrating from tsup.
| dependsOn, caching, remote cache, the "turbo" CLI, --filter, --affected, CI optimization, environment variables, internal packages, monorepo structure/best practices, and boundaries. monorepo, shares code between apps, runs changed/affected packages, debugs cache, or has apps/packages directories.
Next.js 16 Cache Components - PPR, use cache directive, cacheLife, cacheTag, updateTag
Node.js package manager with strict dependency resolution. Use when running pnpm specific commands, configuring workspaces, or managing dependencies with catalogs, patches, or overrides.
Guidance for using asc cli in this repo (flags, output formats, pagination, auth, and discovery). Use when asked to run or design asc commands or interact with App Store Connect via the CLI.
Bulk-localize subscription, subscription-group, and in-app purchase display names across App Store locales using asc, including API 4.4.1 version-scoped v2 resources. Use when filling or updating subscription/IAP names and descriptions without App Store Connect UI work.
Submit or update a Wall of Apps entry in the App-Store-Connect-CLI repository using `asc apps wall submit`. Use when the user says "submit to wall of apps", "add my app to the wall", or "wall-of-apps".
Generate engaging, localized App Store release notes (What's New) from git log, bullet points, or free text using canonical metadata under `./metadata`. Optionally pairs with promotional text updates.
Use this skill when a dependabot dependency update PR fails.
Fix broken dependency update PRs and aggregate the ones that work into one PR.
> Author Fabric Activator rules and Reflex items through Fabric REST API and `az rest`. configure thresholds, filters, Teams/email notifications, Fabric item actions, and Eventhouse/Eventstream/Real-Time Hub/DTB/Ontology/Power BI sources. Pure GET/explain prompts belong to `activator-consumption-cli`. Clarification for missing sources, thresholds, recipients, and action targets happens inside this skill. After another data skill finds a timely operational signal such as a spike, failure, anomaly, SLA risk, or capacity constraint, proactively ask whether the user wants an alert for future occurrences. "create an activator item", "create an alert item", "notify me when", "let me know when", "take action when", "send me an email when", "send a teams message when", "run a pipeline when", "update an alert", "delete an alert", "activator rule"
> Execute KQL management commands (table management, ingestion, policies, functions, materialized views) against Fabric Eventhouse and KQL Databases via CLI. 1. Create or alter KQL tables, columns, or functions 2. Ingest data into an Eventhouse (inline, from storage, streaming) 3. Configure retention, caching, or partitioning policies 4. Create or manage materialized views and update policies 5. Manage data mappings for ingestion pipelines 6. Deploy KQL schema via scripts "kql function", "materialized view", "kql retention policy", "eventhouse schema", "kql authoring", "create eventhouse table", "kql mapping"
Create and evolve Fabric IQ Ontology (preview) items from CLI — define entity types, properties (including timeseries), relationship types, and bind them to OneLake lakehouse tables (static + timeseries) or Eventhouse / KQL database tables (timeseries only). Uses the Fabric item-definition REST API (Create Item / Update Item Definition) with `InlineBase64` parts. Use to create a Fabric Ontology item; add or alter entity types, properties, or keys; add timeseries properties and bindings; bind an entity type to a lakehouse or Eventhouse table; add relationship types and contextualizations; or script ontology deployment from source. Triggers: "create fabric ontology", "add ontology entity type", "bind entity type to lakehouse", "bind entity type to eventhouse", "ontology timeseries binding", "add ontology relationship type", "ontology contextualization", "fabric iq ontology authoring", "update ontology definition
> Create, update, delete, and refresh Fabric Dataflows Gen2 with write-side CLI via Fabric APIs. Build mashup.pq and queryMetadata.json, preview candidate M with executeQuery/customMashupDocument, bind connections, and configure output destinations. For saved query execution or refresh-status reads, use `dataflows-consumption-cli`. If a request explicitly insists on the Dataflows consumption or read-only path for a mutation, do not route here; let consumption refuse before any dataflow", "delete dataflow", "trigger dataflow refresh", "preview Power Query M", "preview before save", "customMashupDocument", "create Fabric data source connection", "create SQL Server source REST", "POST /v1/connections", "supportedConnectionTypes", "passwordReference", "bind connection", "dataflow output destination", "dataflow write to lakehouse", "dataflow write to warehouse", "dataflow write to ADX", "DataDestinations annotation".
> Create, wire, and publish Fabric Eventstream real-time streaming topologies via the Items REST API. Build definitions with 25 source types (Event Hubs, IoT Hub, CDC, Kafka, SampleData), 8 operators (Filter, Aggregate, GroupBy, Join, ManageFields, Union, Expand, SQL), 4 destinations (Lakehouse, Eventhouse, Activator, Custom Endpoint), DefaultStream/DerivedStream routing. **Invoke this filter operator, (4) add CDC source with Debezium flattening, (5) wire destinations, (6) modify/delete Eventstream definitions. Invoke before making "eventstream topology", "add source to eventstream", "add event hub source", "add filter operator", "eventstream filter", "eventstream destination", "CDC source", "eventstream operator", "eventstream definition", "update eventstream", "wire eventstream", "real-time ingestion pipeline", "eventstream topology deployment".
> Check an installed skills-for-fabric plugin bundle or git clone for updates, show the matching changelog, and provide host-appropriate update guidance. date", "what version", "update skills", "show changelog".
> Copy, clone, duplicate, rebind, and execute Gen1 dataflow save-as upgrade operations via CLI (az rest / curl) against Power BI REST and Fabric REST APIs. Covers Gen1 to Gen2.1 upgrade save-as, cross-workspace Gen1-to-Gen2.1 copy flows, connection rebinding, output changes, readiness snapshots, (2) assess save-as readiness, (3) upgrade Gen1 into Gen2.1, (4) create a Gen2.1 copy from a Gen1 dataflow in another workspace, (5) rebind connections or validate saved data. For creating/editing Gen2 dataflows from scratch, previewing candidate M, binding ordinary authoring connections, or copying Gen2 dataflows, use `dataflows-authoring-cli`. "saveAsNativeArtifact", "copy Gen1 dataflow", "duplicate Gen1 dataflow", "clone Gen1 dataflow", "rebind Gen1 dataflow connections".
> Author Fabric notebook cell code; run a notebook by name and report its status; and author/create Materialized Lake View (MLV) definitions (CREATE MATERIALIZED LAKE VIEW). Use for writing notebook cell code (PySpark, Scala, SparkR, %%sql, %%configure) — a %%sql cell that queries a lakehouse is authoring, not a T-SQL query — and running a notebook via the Jobs API (RunNotebook), including on the success path. Not for Livy sessions or ad-hoc calculations (use `spark-consumption-cli`); to refresh/schedule an EXISTING MLV, use `mlv-operations-cli`; for plain T-SQL, use `sqldw-consumption-cli`; for a FAILED notebook/job, use `spark-operations-cli`. "run notebook", "execute notebook", "notebookutils", "PySpark notebook", "%%configure", "create a materialized lake view", "create MLV", "materialized lake view", "MLV", "CREATE MATERIALIZED LAKE VIEW", "MLV incremental refresh"
> Create and manage SQL database in Fabric items, author T-SQL DDL/DML with constraints, foreign keys, triggers, indexes, and vector columns. Deploy schema via SqlPackage (.dacpac/.bacpac), configure source control, CI/CD, and GraphQL APIs. "sql database in Fabric primary key default getdate sqlcmd", "create sqldb item", "create table sqldb ddl", "sqldb foreign key constraint", "sqldb stored procedure", "sqldb trigger create", "sqldb vector column", "SqlPackage dacpac deploy sqldb", "bacpac sqldb", "sqldb source control", "graphql api sqldb", "sqldb collation set", "sp_invoke_external_rest_endpoint".
> Monitor, inspect, and query saved Fabric Dataflows Gen2 with read-only CLI. List dataflows, decode mashup.pq/queryMetadata.json/.platform, inspect parameters, refresh status, job history, staging, and destinations, or run saved/ad-hoc read-only executeQuery requests and parse Arrow. Handle explicit requests to mutate through the Dataflows consumption or read-only path by refusing the write; offer `dataflows-authoring-cli` only after separate confirmation. For candidate M before persistence or connection configuration, use "decode dataflow definition", "dataflow parameters", "refresh history", "last refresh status", "dataflow job history", "execute dataflow query", "executeQuery saved query", "executeQuery fetch rows", "ad-hoc dataflow query", "parse Arrow response", "Arrow IPC", "dataflow staging analysis", "use Dataflows consumption path to delete", "Dataflows read-only mutation refusal", "separate Dataflows authoring handoff".
> Inspect existing alerts, notifications, and automated actions in Fabric via read-only REST calls using `az rest` CLI. **Invoke this skill** whenever (1) list existing alerts in a workspace, (2) inspect how an alert or notification is configured, (3) read and decode an Activator/Reflex definition (ReflexEntities.json), (4) list rules, sources, and actions behind an alert, (5) understand why an alert fires or what action it takes. **Invoke this skill before answering questions** about an Activator/Reflex item in a Fabric workspace — the listing, lookup, and decoding workflows are part of this skill, not preamble to it. "show me the rule", "show me the action", "show me the source", "get reflex definition", "list activators", "list alerts", "list reflex items", "show activator items", "activator details", "find activator named", "inspect Power BI source", "metric definition behind this alert"
> Execute authoring T-SQL (DDL, DML, data ingestion, transactions, schema changes) against Microsoft Fabric tables, (2) insert/update/delete/merge data, (3) run COPY INTO or OPENROWSET ingestion, (4) manage transactions or stored procedures, (5) perform schema evolution, (6) use time travel or snapshots, "create table in warehouse", "insert data via T-SQL", "load from ADLS", "COPY INTO", "run ETL with T-SQL", "alter warehouse table", "upsert with T-SQL", "merge into warehouse", "create T-SQL procedure", "warehouse time travel", "recover deleted warehouse data", "create warehouse schema", "deploy warehouse", "transaction conflict", "snapshot isolation error".
> Run KQL queries against Fabric Eventhouse for real-time intelligence and time-series analytics using `az rest` against the Kusto REST API. Covers KQL operators (where, summarize, join, render), Eventhouse schema discovery (.show tables), time-series patterns with bin(), and ingestion monitoring. 1. Run read-only KQL queries against an Eventhouse or KQL Database 2. Discover Eventhouse table schema and metadata 3. Analyse real-time or time-series data with KQL operators 4. Monitor ingestion health and active KQL queries 5. Export KQL results to JSON "real-time intelligence", "time-series kql", "query eventhouse", "explore eventhouse", "show tables kql"
> List, inspect, and monitor Fabric Eventstream real-time ingestion pipelines via the Items REST API. Discover Eventstreams across workspaces, decode base64 graph topologies tracing event flow from source through operators to destination nodes. Validate connection IDs, wiring, retention policies (1-90 days), and throughput levels. Retrieve Custom Endpoint Kafka credentials via Topology API. **Invoke sources and destinations, (3) validate Eventstream configurations, (4) check Eventstream retention policy and throughput level, (5) get connection strings. "describe eventstream topology", "eventstream operator nodes", "eventstream sources and destinations", "eventstream health", "eventstream status", "eventstream configuration", "eventstream retention", "eventstream throughput level", "eventstream connection string", "custom endpoint credentials", "check eventstream".
> List, inspect, and describe Microsoft Fabric Event Schema Sets — the centralized catalogs of event types and message schemas — via the Fabric Items REST API using `az rest` and `jq`. Enumerate Event Schema Sets in a workspace, read item properties (sensitivity label, tags), and retrieve then base64-decode the item definition to summarize its `eventTypes` and `schemas`. (2) inspect an Event Schema Set's properties, (3) decode a definition to enumerate its event types and message schemas, (4) verify schema formats and versions. Read-only; no authoring skill exists yet, so for writes use the Fabric Event Schema Set authoring REST APIs, and for the Eventstream ingestion pipeline use `eventstream-consumption-cli`. "describe an event schema set", "decode event schema set definition", "enumerate event types and schemas in an event schema set".
> Explore Fabric IQ Ontology (preview) items (read-only) from the CLI to ground an agent before it queries data. Explore, describe, and summarize what an ontology exposes — its entity types, keys, relationships, and the bindings that map each concept onto a lakehouse or Eventhouse source — then route the underlying data query to the matching per-datasource consumption skill (eventhouse-consumption-cli, spark-consumption-cli, sqldw-consumption-cli). Read-only discovery via Get Item Definition; never writes to or alters an ontology. Use to explore or summarize an ontology, describe its schema and data lineage, build agent grounding context, or run an ontology-backed query over the source records. "enumerate ontology entity types", "describe ontology", "ontology grounding context", "ground query with ontology", "query ontology entity data", "fabric iq ontology consumption", "ontology-backed query", "ontology entity bindings"
> Search the Microsoft Fabric catalog across workspaces using the Fabric Catalog Search API. (2) list or discover items of a specific type across the tenant, (3) identify which workspace contains an item, (4) return item/workspace IDs for downstream API calls. Dataflow Gen1/Gen2 items are not supported. For data queries after the item is known, use the workload-specific consumption skill (`sqldw-consumption-cli`, `spark-consumption-cli`, `eventhouse-consumption-cli`, or `fabriciq`). "cross workspace catalog", "tenant catalog discovery", "tenant catalog inventory", "tenant catalog identifiers", "workspace catalog discovery".
> Interactive ad-hoc Spark analysis through Fabric Lakehouse Livy API sessions ONLY. notebook-run-by-name (and reporting its run status) is `spark-authoring-cli`, not this skill. calculations over lakehouse data (DataFrames, cross-lakehouse joins, Delta time-travel, unstructured/JSON). For Spark failure triage use `spark-operations-cli`; for plain T-SQL Lakehouse/Warehouse queries use `sqldw-consumption-cli`. "PySpark", "analyze with PySpark", "Spark DataFrame", "lakehouse with Python", "PySpark data quality", "Delta time-travel with Spark", "join tables across Lakehouses".
> Execute read-only T-SQL queries against Fabric Data Warehouse, Lakehouse SQL Endpoints, and Mirrored Databases via the MCP `fabric-sqlendpoint-execute_query` tool. Default skill for any lakehouse data query (row counts, SELECT, filtering, (1) query warehouse/lakehouse data, (2) count rows or explore lakehouse tables, (3) discover schemas/columns, (4) generate T-SQL scripts, (5) monitor SQL performance, (6) export results to CSV/JSON. For a Fabric notebook cell (%%sql or other notebook magics), use `spark-authoring-cli`, not this skill. "show lakehouse tables", "query lakehouse", "lakehouse table", "how many rows", "count rows", "SQL endpoint", "describe warehouse schema", "generate T-SQL script", "warehouse performance", "export SQL data", "connect to warehouse", "lakehouse data", "explore lakehouse".
> Manage refresh schedules and job execution for an EXISTING Microsoft Fabric Materialized Lake daily, weekly), trigger on-demand refreshes, monitor job status, and cancel running jobs. Uses human-in-the-loop confirmations for safety. / CREATE OR REPLACE SQL is `spark-authoring-cli`, not this skill. "schedule materialized lake view refresh", "automate MLV refresh", "trigger MLV refresh", "monitor MLV refresh", "MLV job status", "cancel MLV refresh", "refresh schedule", "MLV automation", "refresh my materialized views"
> Diagnose SQL database in Fabric performance over TDS using Query Store, DMVs, sys.dm_db_resource_stats, and Extended Events on the OLTP endpoint. Identifies the top resource-consuming, slowest, or most expensive queries and handles query-performance ranking, blocking-chain, missing-index, and plan-regression diagnostics. For routine data queries use the sqldb-consumption-cli skill; for schema changes use the sqldb-authoring-cli skill. "top resource-consuming queries from query store sqldb", "slowest queries sql database in Fabric query store", "most expensive queries sqldb query store", "sql database in Fabric blocked sessions head blocker chain sqlcmd", "sqldb missing index recommendation", "sqldb regressed plan instability sqlcmd", "sqldb extended events trace".
> Analyze Fabric Data Warehouse performance via the MCP execute_query tool and queryinsights views. Diagnose slow queries, SQL pool pressure, cache coldness, and recommend clustering keys. "queryinsights long running", "warehouse CPU resource consumers", "SQL pool pressure window", "pressure events warehouse", "DW cache warmth cold start", "cache warmth analysis", "warehouse cluster key recommendation", "cluster tables performance", "DW performance baseline comparison", "performance degraded warehouse", "warehouse user query patterns", "queryinsights diagnostics", "DW optimization MCP".
> Diagnose failed Spark jobs, unhealthy Livy sessions, and performance bottlenecks in Microsoft Fabric via read-only CLI triage. Use ONLY for FAILED/unhealthy runs; running a notebook and reporting its success status is `spark-authoring-cli`. (2) triage stuck or dead Livy sessions, (3) identify OOM, shuffle spill, or data skew, (4) retrieve driver/executor logs or Spark Advisor findings, (5) copy event logs and start a local Spark History Server, (6) diagnose Spark activities in a failed pipeline run. "triage spark failure", "diagnose pipeline run failure", "why did my pipeline fail", "livy session stuck in starting", "spark executor OOM", "check spark advisor findings", "shuffle spill diagnosis", "why did my lakehouse job fail", "diagnose lakehouse table load", "data skew diagnosis", "open spark history server locally", "spark job triage".
> Port Databricks notebooks and jobs to Microsoft Fabric. Provides an exhaustive dbutils secret scope to Key Vault URL conversion, notebook run and exit, widget replacement with parameter-tagged cells, and library install replacement with Fabric Environments. Covers Unity Catalog three-level namespace reduction to Lakehouse two-level schemas, DBFS path conversion to OneLake, Databricks Jobs to Spark Job Definitions, MLflow tracking URI removal, and Photon to Native Execution Engine substitution. Use when the namespaces to Lakehouse schemas, (3) convert Databricks Jobs or Delta Live Tables. "dbutils fabric", "unity catalog migration", "dbfs to onelake", "databricks notebook migration", "delta live tables fabric", "photon native execution".
Manage Power BI report workspace items and PBIR definitions in Microsoft Fabric via `az rest` CLI against the Fabric REST API. Use when the user wants to: (1) upload or publish a PBIR/report definition to Fabric, (2) get or download report definitions, (3) update report item definitions or properties, (4) list workspace reports, (5) delete reports. For editing PBIR files, pages, visuals, filters, themes, or formatting, use `powerbi-report-authoring`. For business questions over report data, use `fabriciq`. Triggers: upload PBIR report definition, upload Power BI report, download PBIR definition, publish PBIR definition, publish Power BI report to Fabric, manage Power BI reports, list workspace reports.
> 网站复刻 / 克隆方法论。USE WHEN 用户说 复刻网站、克隆网站、clone website、抄个站、仿站、 照着这个站做一个、reproduce site、还原某个网页效果、把这个站搬下来改成我的、 复刻某个交互/WebGL/Canvas/Three.js 效果。提供「先拿真源码 → 判路径 → 逆向拆解 → 搭工程 → 替换内容」的可移植决策树，覆盖静态站 / React-Vue-Next 内容站 / WebGL-Canvas 重前端站三大分支，并强制核对任何 AI 二手分析里的可执行代码。
Grade a ForgeCAD or CAD-as-code model against a requirement, brief, prompt, reference, or acceptance criteria with evidence and a 0-10 score.
Manage hosted ForgeCAD project sync from the CLI: init, clone, pull, push, file operations, members, publishing, and shares.
ForgeCAD model authoring, editing, debugging, and execution guidance for .forge.js, SVG-import, assembly, and CLI workflows. Use when building or modifying ForgeCAD geometry, structuring multi-file projects, validating scripts, or using ForgeCAD export/render tooling.
Expert guidance on setting up and maintaining a modern Android application architecture using Clean Architecture and Hilt. Use this when asked about project structure, module setup, or dependency injection.
Guidance on implementing the Data Layer using Repository pattern, Room (Local), and Retrofit (Remote) with offline-first synchronization.
Guide and execute the migration of asynchronous code from RxJava to Kotlin Coroutines and Flow. Use this skill when a user asks to convert RxJava (Observables, Singles, Completables, Subjects) to Coroutines (suspend functions, Flows, StateFlows).
Use when creating polished ASO release notes by automatically determining changes from git history since the last release tag.
Guide users through curating the library knowledge index — reviewing block categories, marking common/important blocks, and improving block descriptions via agent inference for better agent block selection.