Agent Skills

by hashicorp

Build Azure managed images and Azure Compute Gallery images with Packer. Use when creating custom images for Azure VMs.

🔥🔥🔥✓ VerifiedFree

new-terraform-provider

🔥🔥🔥🔥✓ VerifiedFreeAdvanced setup

by hashicorp

Use this when scaffolding a new Terraform provider.

provider-docs

by hashicorp

Create, update, and review Terraform provider documentation for Terraform Registry using HashiCorp-recommended patterns, tfplugindocs templates, and schema descriptions. Use when adding or changing provider configuration, resources, data sources, ephemeral resources, list resources, functions, or guides; when validating generated docs; and when troubleshooting missing or incorrect Registry documentation.

terraform-stacks

by hashicorp

Comprehensive guide for working with HashiCorp Terraform Stacks. Use when creating, modifying, or validating Terraform Stack configurations (.tfcomponent.hcl, .tfdeploy.hcl files), working with stack components and deployments from local modules, public registry, or private registry sources, managing multi-region or multi-environment infrastructure, or troubleshooting Terraform Stacks syntax and structure.

🔥🔥🔥🔥✓ VerifiedFree

windows-builder

by hashicorp

Build Windows images with Packer using WinRM communicator and PowerShell provisioners. Use when creating Windows AMIs, Azure images, or VMware templates.

provider-actions

by hashicorp

Implement Terraform Provider actions using the Plugin Framework. Use when developing imperative operations that execute at lifecycle events (before/after create, update, destroy).

terraform-test

🔥🔥🔥🔥✓ VerifiedFreeQuick setup

by hashicorp

Comprehensive guide for writing and running Terraform tests. Use when creating test files (.tftest.hcl), writing test scenarios with run blocks, validating infrastructure behavior with assertions, mocking providers and data sources, testing module outputs and resource configurations, or troubleshooting Terraform test syntax and execution.

claimable-postgres

✓★ 617

by neondatabase

Provision instant temporary Postgres databases via Claimable Postgres by Neon (pg.new) with no login, signup, or credit card. Use when users ask for a quick Postgres environment, a throwaway DATABASE_URL for prototyping/tests, or "just give me a DB now". Triggers include: "quick postgres", "temporary postgres", "no signup database", "no credit card database", "instant DATABASE_URL".

🔥🔥🔥🔥✓ VerifiedFreeQuick setup

logging-best-practices

✓★ 617

by neondatabase

Logging best practices focused on wide events (canonical log lines) for powerful debugging and analytics

auditing-skills

by dbt-labs

Use when checking skills for security or quality issues, reviewing audit results from skills.sh or Tessl, or remediating findings across published skills.

fetching-dbt-docs

by dbt-labs

Retrieves and searches dbt documentation pages in LLM-friendly markdown format. Use when fetching dbt documentation, looking up dbt features, or answering questions about dbt Cloud, dbt Core, or the dbt Semantic Layer.

creating-mermaid-dbt-dag

by dbt-labs

Generates a Mermaid flowchart diagram of dbt model lineage using MCP tools, manifest.json, or direct code parsing as fallbacks. Use when visualizing dbt model lineage and dependencies as a Mermaid diagram in markdown format.

using-dbt-state

by dbt-labs

Use when a user is enabling, configuring, optimizing, or debugging dbt State (the server-backed reuse mechanism that clones or skips nodes instead of rebuilding them). Use when they conflate dbt State with the `state:modified` selector or `--state` deferral. Use when asked about models rebuilding unexpectedly, views with `select *` rebuilding, volatile SQL (`current_timestamp()`, `random()`) rebuilding or not, cross-developer cloning, lag_tolerance.

configuring-dbt-mcp-server

by dbt-labs

Generates MCP server configuration JSON, resolves authentication setup, and validates server connectivity for dbt. Use when setting up, configuring, or troubleshooting the dbt MCP server for AI tools like Claude Desktop, Claude Code, Cursor, or VS Code.

running-dbt-commands

by dbt-labs

Formats and executes dbt CLI commands, selects the correct dbt executable, and structures command parameters. Use when running models, tests, builds, compiles, or show queries via dbt CLI. Use when unsure which dbt executable to use or how to format command parameters.

using-dbt-for-analytics-engineering

🔥🔥🔥🔥✓ VerifiedFreeQuick setup

by dbt-labs

Builds and modifies dbt models, writes SQL transformations using ref() and source(), creates tests, and validates results with dbt show. Use when doing any dbt work - building or modifying models, debugging errors, exploring unfamiliar data sources, writing tests, or evaluating impact of changes.

troubleshooting-dbt-job-errors

by dbt-labs

Diagnoses dbt Cloud/platform job failures by analyzing run logs, querying the Admin API, reviewing git history, and investigating data issues. Use when a dbt Cloud/platform job fails and you need to diagnose the root cause, especially when error messages are unclear or when intermittent failures occur. Do not use for local dbt development errors.

working-with-dbt-mesh

by dbt-labs

Use when changing a dbt model in a way that could break its consumers — renaming, removing, or retyping a column, or changing a model that downstream models, exposures, dashboards, or BI tools depend on — to judge whether the change is breaking and who it affects. Also use when versioning a model (model versions, latest_version, latest_version_pointer, deprecation_date, migration windows), enforcing contracts, setting access or groups, or doing multi-project dbt Mesh work (cross-project refs via dependencies.yml, disambiguating similarly-named models, splitting a monolith). Covers single- and multi-project, and planning or advising as well as implementing.

🔥🔥🔥✓ VerifiedFree

building-dbt-semantic-layer

by dbt-labs

Use when creating or modifying dbt Semantic Layer components — semantic models, metrics, dimensions, entities, measures, or time spines. Covers MetricFlow configuration, metric types (simple, derived, cumulative, ratio, conversion), and validation for both latest and legacy YAML specs.

answering-natural-language-questions-with-dbt

by dbt-labs

Writes and executes SQL queries against the data warehouse using dbt's Semantic Layer or ad-hoc SQL to answer business questions. Use when a user asks about analytics, metrics, KPIs, or data (e.g., "What were total sales last quarter?", "Show me top customers by revenue"). NOT for validating, testing, or building dbt models during development.

adding-dbt-unit-test

by dbt-labs

Creates unit test YAML definitions that mock upstream model inputs and validate expected outputs. Use when adding unit tests for a dbt model or practicing test-driven development (TDD) in dbt.

migrating-dbt-project-across-platforms

by dbt-labs

Use when migrating a dbt project from one data platform or data warehouse to another (e.g., Snowflake to Databricks, Databricks to Snowflake) using dbt Fusion's real-time compilation to identify and fix SQL dialect differences.

video-ad-specs

by qu-skills

Video ad creation with exact platform-specific specs for TikTok, Instagram, YouTube, Facebook, LinkedIn. Covers dimensions, duration limits, AIDA framework, and caption requirements. Use for: video ads, social media ads, paid media creative, video marketing, ad production. Triggers: video ad, social media ad, tiktok ad, instagram ad, youtube ad, facebook ad, linkedin ad, video creative, ad specs, paid media, video marketing, ad production, reels ad, stories ad, pre roll, bumper ad

🔥🔥🔥🔥✓ VerifiedFree

ai-automation-workflows

by inference-sh

Build automated AI workflows combining multiple models and services. Patterns: batch processing, scheduled tasks, event-driven pipelines, agent loops. Tools: inference.sh CLI, bash scripting, Python SDK, webhook integration. Use for: content automation, data processing, monitoring, scheduled generation. Triggers: ai automation, workflow automation, batch processing, ai pipeline, automated content, scheduled ai, ai cron, ai batch job, automated generation, ai workflow, content at scale, automation script, ai orchestration

ai-music-generation

by inference-sh

Generate AI music and songs with ElevenLabs, Diffrythm, Tencent Song Generation via inference.sh CLI. Models: ElevenLabs Music (up to 10 min, commercial license), Diffrythm (fast song generation), Tencent Song Generation (full songs with vocals). Capabilities: text-to-music, song generation, instrumental, lyrics to song, soundtrack creation. Use for: background music, social media content, game soundtracks, podcasts, royalty-free music. Triggers: music generation, ai music, generate song, ai composer, text to music, song generator, create music with ai, suno alternative, udio alternative, ai song, ai soundtrack, generate soundtrack, ai jingle, music ai, beat generator, elevenlabs music, eleven labs music

ai-product-photography

by inference-sh

Generate professional AI product photography and commercial images. Models: FLUX, Imagen 3, Grok, Seedream for product shots, lifestyle images, mockups. Capabilities: studio lighting, lifestyle scenes, packaging, e-commerce photos. Use for: e-commerce, Amazon listings, Shopify, marketing, advertising, mockups. Triggers: product photography, product shot, commercial photography, e-commerce images, amazon product photo, shopify images, product mockup, studio product shot, lifestyle product image, advertising photo, packshot, product render, product image ai

dialogue-audio

by inference-sh

Multi-speaker dialogue audio creation with ElevenLabs and Dia TTS. Covers speaker tags, emotion control, pacing, conversation flow, and post-production. Use for: podcasts, audiobooks, explainers, character dialogue, conversational content. Triggers: dialogue audio, multi speaker, conversation audio, dia tts, two speakers, podcast audio, character voices, voice acting, dialogue generation, conversation tts, multi voice, speaker tags, dialogue recording, elevenlabs dialogue, eleven labs conversation

elevenlabs-dialogue

by inference-sh

ElevenLabs multi-speaker dialogue generation - create conversations with different voices in a single audio file via inference.sh CLI. Capabilities: multi-voice dialogue, script-based generation, voice direction, conversation audio. Use for: podcasts, audiobooks, explainers, tutorials, character dialogue, video scripts. Triggers: elevenlabs dialogue, eleven labs dialogue, multi speaker, conversation audio, dialogue generation, text to dialogue, multi voice, voice acting, podcast dialogue, character voices, script to audio, elevenlabs conversation, two speakers

elevenlabs-dubbing

by inference-sh

ElevenLabs automatic dubbing - translate and dub audio/video into 29 languages while preserving speaker voice via inference.sh CLI. Capabilities: auto speaker detection, voice-preserving translation, video dubbing, audio localization. Use for: content localization, video translation, multilingual content, international distribution. Triggers: dubbing, dub video, translate audio, video translation, audio translation, localize content, elevenlabs dubbing, eleven labs dub, multilingual dub, voice translation, auto dub, language dub, content localization

elevenlabs-music