Vendor-agnostic lab automation framework. Use when controlling multiple equipment types (Hamilton, Tecan, Opentrons, plate readers, pumps) or needing unified programming across different vendors. Best for complex workflows, multi-vendor setups, simulation. For Opentrons-only protocols with official API, opentrons-integration may be simpler.

Query Reactome REST API for pathway analysis, enrichment, gene-pathway mapping, disease pathways, molecular interactions, expression analysis, for systems biology studies.

Reference skill for Zoom Rivet SDK. Use after routing to a Rivet-based server workflow when implementing auth handling, webhook consumers, API wrappers, multi-module composition, or Lambda receiver patterns.

Advanced Rust patterns for ownership, traits, async, error handling, macros, type system tricks, unsafe, and performance. Use when tackling complex Rust problems — not basic syntax, but multi-concern tasks like designing cancellation-safe async services, choosing between trait objects and generics, building typestated APIs, structuring error hierarchies across crate boundaries, writing proc macros, or optimizing hot paths with zero-cost abstractions. Do not use for basic Rust syntax, simple CLI tools, or beginner ownership questions.

Sequelize Node.js ORM for SQL databases. Use for database models, migrations, associations, queries, transactions, validations, hooks, and working with PostgreSQL, MySQL, MariaDB, SQLite, SQL Server.

Scaffold new skills with valid frontmatter, directory layout, and a starter SKILL.md. Use when building a new reusable workflow or wrapping a new API (e.g. create a kalshi skill, scaffold an API helper, start a charting skill).

Build custom Python data sources for Apache Spark using the PySpark DataSource API — batch and streaming readers/writers for external systems. Use this skill whenever someone wants to connect Spark to an external system (database, API, message queue, custom protocol), build a Spark connector or plugin in Python, implement a DataSourceReader or DataSourceWriter, pull data from or push data to a system via Spark, or work with the PySpark DataSource API in any way. Even if they just say "read from X in Spark" or "write DataFrame to Y" and there's no native connector, this skill applies.

This skill should be used when user asks to "use supabase-js", "query Supabase database", "supabase auth", "supabase storage", "supabase realtime", "supabase edge functions", or works with the @supabase/supabase-js JavaScript/TypeScript SDK.

Tauri framework for building cross-platform desktop and mobile apps. Use for desktop app development, native integrations, Rust backend, and web-based UIs.

API versioning strategies and backward compatibility

This skill should be used when the user asks about "build trigger", "webhook trigger", "poll trigger", "dynamic webhook", "static webhook", "hybrid trigger", "dedup", "trigger_limit", "closure", or needs to implement triggers for a Workato custom connector.

NCAA cross country and track & field athlete data via TFRRS (tfrrs.org) and news via The Stride Report. Fetch athlete profiles including all personal records (PRs), eligibility year, school, full season-by-season results history, and XC/TF news. Zero config, no API keys. Use when: user asks about NCAA cross country, NCAA track and field, college running, TFRRS athlete profiles, personal records, PRs, XC or TF season results, individual athlete performance history, or XC/TF news. Don't use when: user asks about professional track, Diamond League, or other sports — use nfl-data, nba-data, wnba-data, nhl-data, mlb-data, golf-data, cricket-data, cfb-data, cbb-data, tennis-data, fastf1, or volleyball-data. For betting use polymarket or kalshi.

Query Allium APIs for wallet PnL (current + historical, by-wallet and by-token), holdings timeseries history, Hyperliquid HyperCore trading data (info, fills, orders, orderbook), and custom SQL analytics across 70+ chains. NOT for token prices, token metadata, current wallet balance snapshots, transaction transfer history, or NFT metadata — for those use `alchemy-cli` (live work), `alchemy-mcp`, `alchemy-api` (app code), or `agentic-gateway` (no API key). Requires Allium credentials at `~/.allium/credentials`.

Generate enterprise-ready, agent-first CLIs from OpenAPI or Swagger specifications. Use this skill whenever the user wants to "generate a CLI from an OpenAPI spec", "turn a Swagger API into a CLI", "scaffold an enterprise REST CLI", "create a CLI wrapper around a REST API", "derive a machine-readable CLI from an API description", "generate auth-aware commands from an OAS file", "build a deterministic CLI for this service", "create an agent-friendly CLI from this API", or mentions "api-anything", "OpenAPI CLI", "Swagger CLI", "REST CLI generator", "OAS to CLI", or "API CLI scaffold" in the context of generating CLI code from an API specification. Also triggers when the user provides an OpenAPI/Swagger spec file and asks to build a command-line tool from it, even if they don't use the exact term "CLI". Does NOT trigger for generic API discussion, SDK generation, client library generation, API debugging, or consuming an existing CLI.

API testing patterns with supertest, MSW, and Vitest. Covers integration testing for REST APIs, HTTP request mocking with Mock Service Worker v2, response assertions, schema validation, test organization, and framework-specific patterns for Express, Fastify, and Hono. Use when writing integration tests for REST APIs, mocking HTTP requests, or testing API endpoints. Use for api-test, supertest, msw, mock-service-worker, integration-test, http-mock, endpoint-test, request-test.

Integrates with Atlassian products to manage project tracking and documentation via MCP protocol. Use when querying Jira issues with JQL filters, creating and updating tickets with custom fields, searching or editing Confluence pages with CQL, managing sprints and backlogs, setting up MCP server authentication, syncing documentation, or debugging Atlassian API integrations.

Reference for Auth0 CLI commands — apps, apis, users, roles, organizations, actions, logs, custom domains, universal-login, terraform, raw API mode, and --json output. Use this skill whenever you need to run Auth0 CLI commands to create or manage applications, APIs, users, roles, organizations, actions, log streams, custom domains, or Universal Login configuration, or when you need to call the Auth0 Management API directly. Trigger on prompts like "create an Auth0 app", "list my Auth0 users", "assign a role", "set up an organization", "deploy an action", "configure a custom domain", "generate Terraform for Auth0", "stream Auth0 logs", "call the Management API", or any task involving the auth0 CLI tool.

Guide for using awman to run AI coding agents in isolated containers with multi-step workflows and a REST API. Use when configuring parallel agent sessions, authoring awman workflows, driving the awman api server, managing worktrees, migrating from amux, or troubleshooting awman container runs.

Provides AWS Lambda integration patterns for Java with cold start optimization. Use when deploying Java functions to AWS Lambda, choosing between Micronaut and Raw Java approaches, optimizing cold starts below 1 second, configuring API Gateway or ALB integration, or implementing serverless Java applications. Triggers include "create lambda java", "deploy java lambda", "micronaut lambda aws", "java lambda cold start", "aws lambda java performance", "java serverless framework".

Provides AWS Lambda integration patterns for Python with cold start optimization. Use when deploying Python functions to AWS Lambda, choosing between AWS Chalice and raw Python approaches, optimizing cold starts, configuring API Gateway or ALB integration, or implementing serverless Python applications. Triggers include "create lambda python", "deploy python lambda", "chalice lambda aws", "python lambda cold start", "aws lambda python performance", "python serverless framework".

Provides comprehensive Microsoft Azure guidance including Azure Virtual Machines, Azure Storage (Blob, Files, Disks), Azure SQL Database, Azure App Service, Azure Functions, AKS (Azure Kubernetes Service), Azure DevOps, ARM templates, Bicep, Terraform for Azure, Azure Active Directory, Azure Key Vault, Azure Monitor, cost optimization, and multi-region deployment. Produces infrastructure as code (Terraform/Bicep/ARM), deployment scripts, security configurations, and architecture designs. Use when deploying to Azure, designing Azure infrastructure, migrating to Microsoft Azure, configuring VMs, setting up Azure Storage, managing Azure SQL, working with AKS, or when users mention Azure, Microsoft Cloud, Azure Portal, ARM templates, Bicep, Azure Functions, App Service, or Azure DevOps.

Build and deploy applications on inference.sh. Use when getting started, understanding the platform, creating apps, configuring resources, or needing an overview of inference.sh app development. Supports both Python and Node.js. Triggers: inference.sh app, belt app, inf.yml, inference.py, inference.js, deploy app, app development, build app, create app, GPU app, VRAM, app resources, app secrets, app integrations, multi-function app

Build and deploy applications on inference.sh. Use when getting started, understanding the platform, creating apps, configuring resources, or needing an overview of inference.sh app development. Supports both Python and Node.js. Triggers: inference.sh app, belt app, inf.yml, inference.py, inference.js, deploy app, app development, build app, create app, GPU app, VRAM, app resources, app secrets, app integrations, multi-function app

Build and deploy applications on inference.sh. Use when getting started, understanding the platform, creating apps, configuring resources, or needing an overview of inference.sh app development. Supports both Python and Node.js. Triggers: inference.sh app, belt app, inf.yml, inference.py, inference.js, deploy app, app development, build app, create app, GPU app, VRAM, app resources, app secrets, app integrations, multi-function app

Build and deploy applications on inference.sh. Use when getting started, understanding the platform, creating apps, configuring resources, or needing an overview of inference.sh app development. Supports both Python and Node.js. Triggers: inference.sh app, belt app, inf.yml, inference.py, inference.js, deploy app, app development, build app, create app, GPU app, VRAM, app resources, app secrets, app integrations, multi-function app

College Basketball (CBB) data via ESPN public endpoints — scores, standings, rosters, schedules, game summaries, play-by-play, win probability, rankings, futures, team/player stats, and news for NCAA Division I men's basketball. Zero config, no API keys. Use when: user asks about college basketball scores, March Madness, NCAA tournament, standings, rankings, team rosters, schedules, play-by-play, betting futures, team/player statistics, or CBB news. Don't use when: user asks about NBA/WNBA (use nba-data/wnba-data), college football (use cfb-data), or non-sports topics.

Scans Cosmos SDK blockchain modules and CosmWasm contracts for consensus-critical vulnerabilities — chain halts, fund loss, state divergence. 25 core + 16 IBC + 10 EVM + 3 CosmWasm patterns. Use when auditing custom x/ modules, reviewing IBC integrations, or assessing pre-launch chain security. Updated for SDK v0.53.x.

Use when working with CUE kind definitions, schemas, or versioning in grafana-app-sdk projects (app platform apps). This skill should be used when the user asks to "define a kind", "add a CUE kind", "write a kind schema", "create a CUE schema", "model a resource", "add a new resource type", "edit kinds/", "what is a kind in grafana-app-sdk", "add a version to a kind", or asks about CUE kind structure, versioning, schema fields, validation constraints, or the codegen configuration section. Provides guidance on authoring CUE kind definitions for grafana-app-sdk projects.

Diagnoses bias, anomalies, and strange-looking results on a specific PostHog experiment. Covers empty / 0-exposure experiments, sample ratio mismatch, identity fragmentation, multi-variant exposure, uneven-split exclusion bias, significance traps (peeking, A/A, Bayesian vs Frequentist), PostHog-vs-SQL discrepancies, and surprises after mid-run edits. Symptom-driven dispatch to the right diagnostic. TRIGGER when: user asks 'is my experiment biased?' or 'why 0 exposures?', references the bias banner, says a variant looks strange / wrong / off, sees significance flipping, notices PostHog numbers disagreeing with their SQL, sees an A/A test showing significance, or reports surprises after mid-run edits. DO NOT TRIGGER when: creating a new experiment (use creating-experiments), only configuring rollout (use configuring-experiment-rollout) or metrics (use configuring-experiment-analytics), or only asking lifecycle questions (use managing-experiment-lifecycle).

Comprehensive guide for electron-builder (v26.x) packaging, code signing, auto-updates, and release workflows. Use when: (1) configuring electron-builder builds (electron-builder.yml or config.js/ts), (2) setting up macOS/Windows code signing or notarization, (3) implementing auto-updates with electron-updater, (4) publishing to GitHub Releases, S3, or generic servers, (5) configuring platform targets (NSIS, DMG, AppImage, Snap, PKG, MSI), (6) working with build hooks (beforePack, afterSign, afterAllArtifactBuild), or (7) using the programmatic API. Triggers on: electron-builder, electron-updater, code signing, notarize, NSIS, DMG, AppImage, auto-update, publish releases, build hooks, electron packaging, electron distribution.

Guides developers and admins through direct interaction with the Fusion Help REST API — reading articles, FAQs, release notes, searching content, and managing help documentation programmatically. USE FOR: fetch help articles from API, integrate help content in app, search help content, manage help documentation via API, automate help content, build help tooling. DO NOT USE FOR: using the fhelp CLI tool (use fusion-help-docs skill), modifying Fusion.Services.Help backend code, or non-help-API tasks.

GitHub CLI workflows for repositories, issues, pull requests, actions, releases, projects, and API calls. Use when creating PRs, reviewing code, triaging issues, triggering workflows, publishing releases, managing projects, verifying attestations, or querying the GitHub API. Use for gh cli, github automation, code review, release management.

Idiomatic context.Context usage in Golang — propagation through API boundaries, cancellation, timeouts and deadlines, request-scoped values, context.WithoutCancel for background work outliving requests. Apply when designing context propagation across layers, debugging leaked or unexpired contexts, choosing between context.Background/TODO/WithoutCancel, or storing values in context. Not for code that merely accepts ctx as first parameter.

In-memory caching in Golang using samber/hot — eviction algorithms (LRU, LFU, TinyLFU, W-TinyLFU, S3FIFO, ARC, TwoQueue, SIEVE, FIFO), TTL, cache loaders, sharding, stale-while-revalidate, missing key caching, and Prometheus metrics. Apply when using or adopting samber/hot, when the codebase imports github.com/samber/hot, or when the project repeatedly loads the same medium-to-low cardinality resources at high frequency and needs to reduce latency or backend pressure.

High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.

Run evaluations for Hugging Face Hub models using inspect-ai and lighteval on local hardware. Use for backend selection, local GPU evals, and choosing between vLLM / Transformers / accelerate. Not for HF Jobs orchestration, model-card PRs, .eval_results publication, or community-evals automation.

Remote command execution and file transfer on SageMaker HyperPod cluster nodes via AWS Systems Manager (SSM). This is the primary interface for accessing HyperPod nodes — direct SSH is not available. Use when any skill, workflow, or user request needs to execute commands on cluster nodes, upload files to nodes, read/download files from nodes, run diagnostics, install packages, or perform any operation requiring shell access to HyperPod instances. Other HyperPod skills depend on this skill for all node-level operations.

PostHog integration for any Python application using the Python SDK

Use when building, configuring, or debugging enterprise Java applications with Spring Boot 3.x, microservices, or reactive programming. Invoke to implement WebFlux endpoints, optimize JPA queries and database performance, configure Spring Security with OAuth2/JWT, or resolve authentication issues and async processing challenges in cloud-native Spring applications.

Use when building JavaScript applications with modern ES2024+ features, async patterns, or Node.js development. Invoke for vanilla JavaScript, browser APIs, performance optimization, module systems, security hardening.

Writes, debugs, and refactors JavaScript code using modern ES2023+ features, async/await patterns, ESM module systems, and Node.js APIs. Use when building vanilla JavaScript applications, implementing Promise-based async flows, optimising browser or Node.js performance, working with Web Workers or Fetch API, or reviewing .js/.mjs/.cjs files for correctness and best practices.

Provides unit test, integration test, and mock AI patterns for LangChain4j applications. Creates mock LLM responses, tests retrieval chains, validates RAG workflows, and implements Testcontainers-based integration tests for Java AI services. Use when unit testing AI services, integration testing LangChain4j components, mocking AI models, or testing LLM-based Java applications.

Designs incremental migration strategies, identifies service boundaries, produces dependency maps and migration roadmaps, and generates API facade designs for aging codebases. Use when modernizing legacy systems, implementing strangler fig pattern or branch by abstraction, decomposing monoliths, upgrading frameworks or languages, or reducing technical debt without disrupting business operations.

Manages TLS certificate and encryption key lifecycle across all tiers. Self-Hosted covers certificate expiry monitoring, node/CA/client cert rotation, and Kubernetes cert management. Advanced/BYOC covers managed TLS (no action) and CMEK (Customer-Managed Encryption Key) rotation in your KMS. Standard and Basic have fully managed TLS and encryption with no customer action. CMEK is only available on Advanced. Use when monitoring cert health, performing rotation, managing CMEK, or responding to key compromise.

Proactively suggest diagrams when explaining complex systems. Triggers on diagrams, charts, visualizations, flowcharts, sequence diagrams, architecture diagrams, ER diagrams, state machines, Gantt charts, mindmaps, C4, class diagrams, git graphs. Use when user asks for visual representations of code, systems, processes, data structures, database schemas, workflows, or API flows. Generate Mermaid diagrams in markdown.

Complete Metaplex Protocol guide for Solana NFTs and digital assets. Covers Core (next-gen NFTs), Token Metadata, Bubblegum (compressed NFTs), Candy Machine, Genesis (token launches), MPL-Hybrid, Inscriptions, DAS API, and the Umi framework. The single source of truth for all Metaplex integrations.

Schedule and manage social media posts via Metricool API. Use when posting to multiple platforms (LinkedIn, X, Bluesky, Threads, Instagram), checking scheduled posts, or analyzing social metrics.

Run Neo4j Graph Analytics algorithms (PageRank, Louvain, WCC, Dijkstra, KNN, Node2Vec, FastRP, GraphSAGE) directly inside Snowflake without moving data. Use when running graph algorithms against Snowflake tables via the Neo4j Snowflake Native App ("GDS Snowflake", "graph algorithms in Snowflake", "Neo4j Graph Analytics"). Covers the explore → prepare projection views → project-compute-write flow, the strict view/column type rules the graph engine requires, and exact SQL CALL syntax. Does NOT cover Cypher or Neo4j DBMS queries — use neo4j-cypher-skill. Does NOT cover Aura Graph Analytics — use neo4j-aura-graph-analytics-skill. Does NOT cover self-managed GDS — use neo4j-gds-skill.

NFL data via ESPN public endpoints plus an nflverse backend for schedules, weekly rosters, play-by-play, and normalized player/team stat tables. Zero config, no API keys. Use when: user asks about NFL scores, standings, team rosters, schedules, game stats, box scores, play-by-play, injuries, transactions, betting futures, depth charts, team/player statistics, or NFL news. Don't use when: user asks about football/soccer (use football-data), college football (use cfb-data), or other sports.

Node.js (nodejs) changes since training cutoff (latest: 25.5.0) — require(esm), node --run, URLPattern global, AsyncContextFrame, permission model updates, process.execve, test runner upgrades. Load before working with Node.js.

Provides comprehensive Oracle Cloud Infrastructure (OCI) guidance including compute instances, networking (VCN, load balancers, VPN), storage (block, object, file), database services (Autonomous Database, MySQL, NoSQL), container orchestration (OKE), identity and access management (IAM), resource management, cost optimization, and infrastructure as code (Terraform OCI provider, Resource Manager). Produces infrastructure code, deployment scripts, configuration guides, and architectural diagrams. Use when designing OCI architecture, provisioning cloud resources, migrating to Oracle Cloud, implementing OCI security, setting up OCI databases, deploying containerized applications on OKE, managing OCI resources, or when users mention "Oracle Cloud", "OCI", "Autonomous Database", "VCN", "OKE", "OCI Terraform", "Resource Manager", "Oracle Cloud Infrastructure", or "OCI migration".

PostgreSQL server administration & operations — DBA work on a running cluster. Use when configuring a server (postgresql.conf, ALTER SYSTEM, reload vs restart, GUCs), managing roles & privileges (CREATE ROLE, GRANT/REVOKE, DEFAULT PRIVILEGES, predefined roles, membership), authentication (pg_hba.conf, scram-sha-256, peer/cert/ldap), backups & restore (pg_dump/pg_dumpall/pg_restore, pg_basebackup, incremental backups, PITR), replication & HA (streaming, logical publications/subscriptions, replication slots, failover, synchronous commit), pg_upgrade, or monitoring (pg_stat_activity, pg_stat_io, pg_stat_progress_*, log settings, checkpoints, connections). Server-side ops — for the psql client use `psql`, for SQL & query syntax `postgres-sql`, for query tuning & autovacuum mechanics `postgres-performance`, for contrib modules `postgres-extensions`. Features added in a release are tagged inline like `(pg16+)`; untagged items are bedrock (PostgreSQL 9.x or earlier). Verify with `SHOW server_version`.

PostgreSQL query & performance tuning — reading EXPLAIN / EXPLAIN ANALYZE plans, choosing and designing indexes, fixing planner row-estimate errors with statistics, and diagnosing MVCC bloat / VACUUM. Use when a query is slow, when reading an EXPLAIN/EXPLAIN ANALYZE plan (seq vs index vs bitmap scan, nested-loop/hash/merge join, "Rows Removed by Filter", estimate-vs-actual skew), when choosing an index type or columns to index (btree/GIN/GiST/SP-GiST/BRIN/hash, multicolumn/partial/expression/covering), when ANALYZE/extended statistics give bad estimates, when tables bloat or autovacuum lags, or when tuning planner GUCs (random_page_cost, work_mem, effective_cache_size, enable_*). This is performance tuning — for the psql client see psql, for writing SQL/DDL see postgres-sql, for server config/replication & autovacuum GUC tuning see postgres-admin, for installing perf extensions (pg_stat_statements, auto_explain) see postgres-extensions. Newer features are tagged inline (pgNN+); PG18 is stable, PG19 is beta.

The PostgreSQL SQL dialect and data types that set Postgres apart from generic SQL. Use when writing or debugging Postgres-specific SQL — upsert (`INSERT ... ON CONFLICT DO UPDATE/NOTHING`), `RETURNING` (incl. `OLD`/`NEW`), `MERGE`, CTEs (`WITH`/`MATERIALIZED`/recursive/data-modifying), window frames, `GROUPING SETS`/`CUBE`/`ROLLUP`, `DISTINCT ON`, `LATERAL`, `FILTER`, generated & identity columns, declarative partitioning, `jsonb` operators + jsonpath + SQL/JSON (`JSON_TABLE`/`IS JSON`), arrays, ranges & multiranges, composite/enum/domain types, and functions like `uuidv7()`/`gen_random_uuid()`/`ANY_VALUE()`. Triggers on `ON CONFLICT`, `MERGE`, `jsonb`, `@>`/`->>`, `GENERATED ... AS IDENTITY`, `PARTITION BY`. Disambiguation — this is the SQL dialect & types; for the `psql` client use psql, for tuning/EXPLAIN/indexes use postgres-performance, for config/auth/backup use postgres-admin, for contrib use postgres-extensions. Features carry inline `(pgNN+)` tags; unlisted = long-standing (bedrock since 9.x).

Testing patterns for Prowler SDK (Python). Trigger: When writing tests for the Prowler SDK (checks/services/providers), including provider-specific mocking rules (moto for AWS only).

Development guidance for writing idiomatic Rust. Use when: (1) writing new Rust functions or modules, (2) choosing between borrowing, cloning, or ownership patterns, (3) implementing error handling with Result types, (4) optimizing Rust code for performance, (5) configuring clippy and linting for a project, (6) deciding between static and dynamic dispatch, (7) writing documentation or doc tests.

Comprehensive sales and revenue operations skill. Use when building a sales team, doing founder-led sales, hiring first sales reps, navigating enterprise deals, implementing product-led sales, designing sales compensation plans, defining ICP, mapping buyer personas, or optimizing the revenue engine (RevOps). Activates for: sales strategy, rev ops, revenue operations, sales enablement, sales compensation, ICP, ideal customer profile, buyer persona, sales process, deal execution, lead scoring, lead routing, lead lifecycle, MQL, SQL, pipeline management, CRM automation, sales qualification, BANT, MEDDIC, founder sales, enterprise sales, product-led sales, startup sales, SDR, AE, quota, ramp, commission plan.

Use when writing Spark jobs, debugging performance issues, or configuring cluster settings for Apache Spark applications, distributed data processing pipelines, or big data workloads. Invoke to write DataFrame transformations, optimize Spark SQL queries, implement RDD pipelines, tune shuffle operations, configure executor memory, process .parquet files, handle data partitioning, or build structured streaming analytics.

Spring Boot 4 testing strategies and patterns. Use when writing unit tests, slice tests (@WebMvcTest, @DataJpaTest), integration tests, Testcontainers with @ServiceConnection, security testing (@WithMockUser, JWT), or Modulith event testing with Scenario API. Covers the critical @MockitoBean migration from @MockBean.

Use when optimizing SQL queries, designing database schemas, or tuning database performance. Invoke for complex queries, window functions, CTEs, indexing strategies, query plan analysis.

Tavily AI search API for LLM applications: web search, content extraction, site crawling, mapping, and research. Use when integrating real-time web search into LLM apps, extracting content from URLs, crawling sites, or building RAG pipelines with web data. Keywords: Tavily, AI search, RAG, web search API, LLM search, extract, crawl, map, research, tavily-python.

Generate intelligent, non-redundant test plans based on implementation changes. This skill should be used after implementing features to create comprehensive yet efficient test plans with proper coverage across unit, integration, API, and E2E tests without duplication.

PyTorch Geometric (PyG) for graph neural networks — node/link/graph classification, message passing (GCN, GAT, GraphSAGE, GIN), heterogeneous graphs, neighbor sampling, and custom datasets. Use when working with torch_geometric, not for general NetworkX analytics or non-graph PyTorch models.

Track parcels via the 17TRACK API (local SQLite DB, polling + optional webhook ingestion)

Vitest testing framework: Vite-powered tests, Jest-compatible API, mocking, snapshots, coverage, browser mode, and TypeScript support. Use when writing or configuring tests with Vitest, setting up mocking/snapshots, configuring coverage, or running browser-mode tests. Keywords: Vitest, testing, Vite, Jest, mocking, coverage.

Generate complete, runnable Volcengine SDK code and provide SDK configuration guidance. Supports Go, Python, PHP, Java, and Node.js. Trigger this skill whenever the user wants to call a Volcengine API, generate Volcengine SDK code, or describes a cloud operation on Volcengine (e.g., "list ECS instances", "create a VPC on Volcengine", "query Volcengine billing with Python"). Also trigger when the user asks about Volcengine SDK configuration and best practices — including retry, timeout, authentication (AK/SK, STS, AssumeRole), proxy, connection pooling, SSL, debug mode, and error handling (e.g., "how to configure retry for Volcengine Go SDK", "volcengine python sdk proxy setup"). Trigger when the user mentions Volcengine service names such as ECS, VPC, CDN, CLB, RDS, Redis, Kafka, billing, IAM, DNS with code generation or SDK usage intent. When the user only needs API specification queries (parameters, error codes, response structures), hand off to the volcengine-api skill. When the user needs CLI-based operations, hand off to the volcengine-cli skill. Supports both Chinese and English prompts.

Use when you need to apply Java exception handling best practices — including using specific exception types, managing resources with try-with-resources, securing exception messages, preserving error context via exception chaining, validating inputs early with fail-fast principles, handling thread interruption correctly, documenting exceptions with @throws, enforcing logging policy, translating exceptions at API boundaries, managing retries and idempotency, enforcing timeouts, attaching suppressed exceptions, and propagating failures in async/reactive code. This should trigger for requests such as Exception handling; Use try-with-resources in Java code; Create exception chaining in Java code; Apply fail-fast validation in Java code. Part of cursor-rules-java project

Use when you need to review, improve, or refactor Java code for generics quality — including avoiding raw types, applying the PECS (Producer Extends Consumer Super) principle for wildcards, using bounded type parameters, designing effective generic methods, leveraging the diamond operator, understanding type erasure implications, handling generic inheritance correctly, preventing heap pollution with @SafeVarargs, and integrating generics with modern Java features like Records, sealed types, and pattern matching. This should trigger for requests such as Improve the code with Generics; Apply Generics; Refactor the code with Generics. Part of cursor-rules-java project

Use when you need to apply functional programming principles in Java — including writing immutable objects and Records, pure functions, functional interfaces, lambda expressions, Stream API pipelines, Optional for null safety, function composition, higher-order functions, pattern matching for instanceof and switch, sealed classes/interfaces for controlled hierarchies, Stream Gatherers for custom operations, currying/partial application, effect boundary separation, and concurrent-safe functional patterns. This should trigger for requests such as Improve the code with Functional Programming; Apply Functional Programming; Refactor the code with Functional Programming. Part of cursor-rules-java project

Use when you need to apply data-oriented programming best practices in Java — including separating code (behavior) from data structures using records, designing immutable data with pure transformation functions, keeping data flat and denormalized with ID-based references, starting with generic data structures converting to specific types when needed, ensuring data integrity through pure validation functions, and creating flexible generic data access layers. This should trigger for requests such as Improve the code with Data-Oriented Programming; Apply Data-Oriented Programming; Refactor the code with Data-Oriented Programming; Apply Data-Oriented Programming; Refactor the code with Data-Oriented Programming. Part of cursor-rules-java project

Use when you need to write or review programmatic JDBC with Spring — including JdbcClient (Spring Framework 7+) as the default API, JdbcTemplate only where batch/streaming APIs require JdbcOperations, NamedParameterJdbcTemplate for legacy named-param code, parameterized SQL, RowMapper mapping to records, batch operations, transactions, safe handling of generated keys, DataAccessException handling, read-only transactions, streaming large result sets, and @JdbcTest slice testing. This should trigger for requests such as Review Java code for Spring JDBC (JdbcTemplate, JdbcClient, NamedParameterJdbcTemplate); Apply best practices for Spring JDBC data access in Java code; Detect and fix SQL injection risks in JDBC code; Improve transaction boundaries or exception handling for JDBC operations. Part of cursor-rules-java project

Use when you need to write or improve integration tests for Quarkus — including @QuarkusTest, Dev Services for automatic container provisioning, Testcontainers via QuarkusTestResourceLifecycleManager, WireMock for external HTTP stubs, @QuarkusIntegrationTest for black-box testing against packaged artifacts, REST Assured, data isolation strategies (@TestTransaction vs @BeforeEach cleanup), and Maven Surefire/Failsafe three-tier split (*Test, *IT, *AT). This should trigger for requests such as Add or improve integration tests in a Quarkus project; Configure Testcontainers or Dev Services for Quarkus tests; Add WireMock stubs for external HTTP dependencies in Quarkus integration tests; Set up @QuarkusIntegrationTest for packaged artifact or native binary testing; Fix test data isolation or configure Maven Surefire/Failsafe split. Part of cursor-rules-java project

FastAPI web framework for building modern APIs with async support

Use when connecting your agent to external APIs, tools, or services via Gateway, or restricting tool access with Cedar policies. Handles gateway setup, target types, outbound auth (OAuth, API key, IAM), credentials, and Cedar policy authoring. Triggers on: "connect to API", "add gateway", "connect to MCP server", "Lambda tools", "OpenAPI", "gateway target", "Cedar policy", "restrict tools", "policy engine", "gateway auth error", "store API key", "outbound credential", "env var API key", "API key None after deploy", "credential not available after deploy", "should this be a gateway target", "give my agent tools", "add tools to agent". Not for inbound auth (who can call your agent) — use agents-harden. Not for debugging agent behavior — use agents-debug. Not for VPC networking errors (agent can't reach APIs due to VPC) — use agents-build. Not for creating or hosting a new MCP server project — use agents-get-started.

Use when preparing your agent for production — IAM scoping, inbound auth (JWT, SigV4), secrets management, cold start optimization, session lifecycle, rate limiting, input validation, and quota guidance. Triggers on: "production checklist", "harden agent", "production ready", "secure agent", "inbound auth", "going live", "cold start optimization", "session lifecycle", "StopRuntimeSession", "quota", "throttling", "maxVms", "rate limit", "security audit of outbound API calls", "gateway target audit for production", "restrict who can call", "lock down endpoint", "only our app can call". Not for Cedar tool-restriction policies — use agents-connect. Not for quality measurement — use agents-optimize. Not for outbound credential storage or API key wiring — use agents-connect. Not for A2A agent-to-agent auth — use agents-build. Cold start observation and diagnosis (not optimization) routes to agents-debug.

Smoke test for Alibaba Cloud ALB skill. Validates SDK auth, script compilation, list instances, and health check flows.

Use when querying or troubleshooting logs in Alibaba Cloud Log Service (SLS) using query|analysis syntax and the Python SDK. Use for time-bounded log search, error investigation, and root-cause analysis workflows.

API Gateway patterns for routing, authentication, rate limiting, and service composition in microservices architectures. Use when implementing API gateways, building BFF layers, or managing service-to-service communication at scale.

Expose external APIs to Falcon Foundry via OpenAPI specs. TRIGGER when user asks to "create an API integration", "adapt an OpenAPI spec for Foundry", "expose an API to workflows", "connect to a third-party API", or runs `foundry api-integrations create`. Also trigger when user has an OpenAPI/Swagger spec and wants it working in Falcon Foundry. DO NOT TRIGGER when user wants to call Falcon platform APIs from function code — use functions-falcon-api instead.

Guide for writing Apollo Router native Rust plugins. Use this skill when: (1) users want to create a new router plugin, (2) users want to add service hooks (router_service, supergraph_service, execution_service, subgraph_service), (3) users want to modify an existing router plugin, (4) users need to understand router plugin patterns or the request lifecycle. (5) triggers on requests like "create a new plugin", "add a router plugin", "modify the X plugin", or "add subgraph_service hook".

Use when adding authentication to Android applications (Kotlin/Java) with Web Auth, biometric-protected credentials, and MFA - integrates com.auth0.android:auth0 SDK for native Android apps

AWS SDK for Python (boto3/botocore) development patterns. You MUST use this skill when writing Python code that uses AWS services via boto3 or botocore. This includes creating service clients or resources, configuring sessions and credentials, handling errors with ClientError, using paginators and waiters, S3 file transfers and presigned URLs, DynamoDB table operations, and any boto3/botocore client configuration. Use this skill whenever Python code imports boto3 or botocore, or when the user asks about AWS operations in Python.

Create and manage Axiom monitors and notifiers via the v2 public API. Use when building alerting, routing notifications, validating monitor behavior, and maintaining alert configurations end-to-end.

Manages datasets, tables, and jobs in BigQuery, and integrates with BigQuery ML and Gemini for advanced data analytics and AI-driven insights. Use when you need to interact with BigQuery, run SQL queries, manage BigQuery resources, or leverage BigQuery's built-in ML capabilities. Also use when performing data analysis, ingesting data into BigQuery, or developing AI applications on BigQuery.

Build production-ready Bright Data integrations with best practices baked in. Reference documentation for developers using coding assistants (Claude Code, Cursor, etc.) to implement web scraping, search, browser automation, and structured data extraction. Covers Web Unlocker API, SERP API, Web Scraper API, and Browser API (Scraping Browser).

Centrifugo real-time messaging server expert for WebSocket PUB/SUB, channel management, JWT authentication, event proxying, and horizontal scaling with Redis/NATS. Use when: centrifugo, centrifugal, real-time messaging, websocket pubsub, channel subscriptions, real-time notifications, live updates, presence, history recovery, server-sent events integration, real-time transport layer. Do not use for: general WebSocket programming without Centrifugo, Socket.IO, Pusher SDK, or other real-time frameworks.

Proactively apply when designing APIs, microservices, or scalable backend structure. Triggers on DDD, Clean Architecture, Hexagonal, ports and adapters, entities, value objects, domain events, CQRS, event sourcing, repository pattern, use cases, onion architecture, outbox pattern, aggregate root, anti-corruption layer. Use when working with domain models, aggregates, repositories, or bounded contexts. Clean Architecture + DDD + Hexagonal patterns for backend services, language-agnostic (Go, Rust, Python, TypeScript, Java, C#).

MUST USE when investigating performance issues on a ClickHouse-managed Postgres instance. Provides an evidence-based RCA workflow that scrapes the Prometheus endpoint for system signal, pulls per-digest evidence from the Slow Query Patterns API, and recommends (does not apply) a fix.

Comprehensive toolkit for developing with the CocoIndex library. Use when users need to create data transformation pipelines (flows), write custom functions, or operate flows via CLI or API. Covers building ETL workflows for AI data processing, including embedding documents into vector databases, building knowledge graphs, creating search indexes, or processing data streams with incremental updates.

Complete CoinGecko Solana API integration for token prices, DEX pool data, OHLCV charts, trades, and market analytics. Use for building trading bots, portfolio trackers, price feeds, and on-chain data applications.

This skill should be used when the user asks to "create an AUR package", "make a new AUR package", "scaffold AUR package", "create PKGBUILD", "package for AUR", or mentions AUR package creation with a specific source type (npm, rust, go, git, binary, appimage). Provides comprehensive guidance for creating Arch User Repository packages with proper structure, checksums, and git setup.

Designs and builds ETL/ELT data pipelines. Takes data sources, destination, transformation requirements. Generates pipeline code (Python/SQL), scheduling config, error handling, monitoring setup, and data quality checks. Outputs data-pipeline-spec.md + implementation files.

Debugging workflows for Python (pdb, debugpy), Go (delve), Rust (lldb), and Node.js, including container debugging (kubectl debug, ephemeral containers) and production-safe debugging techniques with distributed tracing and correlation IDs. Use when setting breakpoints, debugging containers/pods, remote debugging, or production debugging.

Guide for implementing DefectDojo - an open-source DevSecOps, ASPM, and vulnerability management platform. Use when querying vulnerabilities, managing findings, configuring CI/CD pipeline imports, or working with security scan data. Includes MCP tools for direct API interaction.

Blocks dangerous commands before execution via a Rust-based Claude Code hook. Use when configuring agent safety guards, setting up destructive command blocking, or auditing CLI protection rules. Use for git reset protection, rm -rf interception, force-push blocking, pack-based command filtering, and PreToolUse hook safety.

Develops and executes Spark code on Dataproc Clusters and Serverless. Reads and writes data using BigLake Iceberg catalogs, BigQuery and Spanner. Debugs execution failures. Use when: - Writing Spark ETL pipelines on GCP. - Training or running inference with ML models with spark on GCP. - Managing Spark clusters, jobs, batches, and interactive sessions. Don't use when: - Writing generic Python scripts that don't use Spark. - Performing simple SQL queries that can be done directly in BigQuery.