Claude Skills by agentskillexchange

Danger JS automates pull request review chores by running programmable checks inside CI and posting structured feedback back to GitHub, GitLab, and other code hosts. It is a strong fit for teams that want to turn review conventions into repeatable checks instead of relying on humans to catch the same issues every time.

Dasel (Data-Select) is a command-line tool and Go library for querying, modifying, and transforming structured data across JSON, YAML, TOML, XML, CSV, HCL, and INI formats using a unified selector syntax. It supports format conversion between all supported types.

Validates SQL database migrations for safety using pg_stat_statements analysis and pt-online-schema-change dry-run mode. Checks for long-running locks, missing indexes on foreign keys, and backward-incompatible column changes.

Routes Datadog anomaly detection alerts to appropriate response channels using the Datadog Events API v2 and Monitors API. Applies severity-based escalation rules with PagerDuty and Slack webhook integration.

Monitors Datadog metric streams using the Datadog API v2 and applies ML-based anomaly detection to alert on infrastructure drift. Integrates with PagerDuty and Slack webhooks for multi-channel incident routing.

Leverages the Datadog API v2 metrics and events endpoints to detect anomalous patterns. Uses the Datadog Monitors API to create dynamic thresholds and sends escalations via OpsGenie REST API.

Detects performance anomalies in Datadog APM traces using the Datadog API v2 metrics endpoint. Applies DBSCAN clustering on latency distributions to identify outlier service behaviors.

Queries Datadog APM trace data via the Datadog Tracing API v2 to identify latency bottlenecks and error hotspots. Generates flame graph summaries and service dependency impact reports.

Queries distributed traces from Datadog APM using the Trace Search API with faceted filtering. Analyzes p99 latency breakdowns across service spans and identifies slow database queries via db.statement tags.

Fetches an active Datadog incident, retrieves associated monitors and dashboards, pulls the last 30 minutes of metric data, and walks through a runbook checklist with automated triage steps. Reduces mean time to diagnosis by surfacing signal without dashboard navigation.

Connects applications to Datadog monitoring using the Datadog API v2 for metrics submission, log forwarding, APM trace ingestion, and dashboard JSON template management.

Node.js, npm

Exports custom metrics and traces to Datadog using the DogStatsD protocol and Datadog API v2. Supports histogram aggregation, tag-based filtering, and SLO tracking.

Creates Datadog monitor definitions using the Datadog API v2 with metric, log, APM trace, and composite monitor types. Generates Terraform datadog_monitor resources with threshold and anomaly detection.

Creates and manages Datadog monitors using the datadog-api-client SDK. Configures metric, log, APM trace, and composite monitors with proper threshold types and notification routing.

Interfaces with the Datadog API v2 monitors and dashboards endpoints to programmatically create and manage monitors. Uses DogStatsD protocol for custom metric submission and Datadog Terraform provider for IaC.

Manages Datadog monitors and dashboards via the Datadog REST API v2. Creates metric, log, and APM monitors with composite conditions and configures notification routing through @-mention integrations.

Synchronizes Datadog monitor definitions between environments using the Datadog API v2 monitors endpoint. Supports diff-based updates, tag filtering, and Terraform state reconciliation.

Manages Datadog monitors and dashboards via the Datadog API v2. Lists triggered monitors, mutes/unmutes alert groups, and queries metric timeseries. Supports composite monitors and SLO tracking.

Monitors Datadog Service Level Objectives and burn rate alerts via the Datadog API v2. Generates SLO compliance reports and triggers remediation workflows when error budgets are exhausted.

Investigates broken checks with the Datadog Synthetics API, Monitors API, and Logs Search API to connect failed browser or API tests with the signals that explain them. Handy for turning a red synthetic check into an actionable diagnosis instead of a vague outage alarm.

Automates alert triage using the Datadog Monitors API v2 and Notebooks API. Correlates metrics with traces via the Datadog APM Trace Search API and generates RCA timelines from the Events Stream API.

Datasette is an open-source Python tool for exploring and publishing data. It turns any SQLite database into an interactive web interface with a JSON API, enabling data journalists, researchers, and developers to share datasets without writing application code.

dbmate is a standalone, framework-agnostic database migration tool that uses plain SQL files. It supports PostgreSQL, MySQL, SQLite, ClickHouse, BigQuery, and Spanner, and works with any programming language or framework.

Basic usage or getting-started notes: - [Install dbt Core](https://docs.getdbt.com/docs/get-started/installation) or explore the [dbt Cloud CLI](https://docs.getdbt.com/docs/cloud/cloud-cli-installation), a command-line interface powered by [dbt Cloud](http... - Read the [introduction](https://docs.getdbt.com/docs/introduction/) and [viewpoint](https://docs.getdbt.com/docs/about/viewpoint/) - ## Join the dbt Community

Integrates with dbt Cloud Administrative API v2 to trigger and monitor data transformation jobs. Manages model runs, source freshness checks, and test execution through dbt API endpoints with Snowflake and BigQuery adapter support.

Manages dbt Core and dbt Cloud API workflows for SQL-based data transformations. Handles model lineage, incremental builds, and data quality tests with Great Expectations integration.

The official dbt MCP Server by dbt Labs provides Model Context Protocol tools for AI agents to interact with dbt projects, query the Semantic Layer, execute SQL, generate SQL from natural language, and explore data model lineage across dbt Core, Fusion, and Platform environments.

Basic usage or getting-started notes: - [Install dbt Core](https://docs.getdbt.com/docs/get-started/installation) or explore the [dbt Cloud CLI](https://docs.getdbt.com/docs/cloud/cloud-cli-installation), a command-line interface powered by [dbt Cloud](http... - Read the [introduction](https://docs.getdbt.com/docs/introduction/) and [viewpoint](https://docs.getdbt.com/docs/about/viewpoint/) - ## Join the dbt Community

Analyzes dbt project DAGs using the dbt manifest.json artifact and the dbt Cloud API. Detects circular dependencies, orphaned models, and generates lineage visualizations.

Analyzes dbt project DAGs to identify circular references, orphaned models, and suboptimal materialization strategies. Uses dbt-core manifest.json parsing with Jinja template resolution for accurate lineage tracking.

Parses dbt project manifests and catalog artifacts to build complete data lineage graphs. Uses the dbt Cloud API v2 for run metadata and the dbt Core manifest.json for model dependency analysis.

Extracts and visualizes dbt model dependency lineage using the dbt Core manifest.json artifact API. Parses ref() and source() calls to build DAG representations via the dbt Cloud API v2.

Parses dbt manifest.json and catalog.json to extract full model lineage graphs using the dbt Core artifact API. Generates interactive DAG visualizations and impact analysis for model changes.

Parses dbt project artifacts (manifest.json and catalog.json) to build a lineage graph and identify models with no tests, stale documentation, or missing uniqueness assertions. Integrates with dbt Cloud API to fetch latest run results and annotates each model with pass/fail status.

Generates and validates dbt (data build tool) models, tests, and documentation for Snowflake, BigQuery, and Redshift. Parses dbt manifest.json to analyze DAG lineage and detect circular dependencies.

Run fast DNS lookups, compare record types, and inspect resolver behavior when domains, MX records, or service endpoints look wrong.

Use Firefox DevTools MCP when an agent needs to inspect pages, trace network and console activity, capture screenshots, and automate reproduction steps in Firefox instead of relying on Chrome-first tooling.

Pull DOM, console, network, and CDP telemetry from a live Chromium session when an agent needs to debug a failing browser task.

An agent skill built on Decap CMS (formerly Netlify CMS), the open-source Git-based content management system for static site generators. Provides a visual editing interface backed by Git commits, enabling content workflows for Hugo, Jekyll, Gatsby, Next.js, and other Jamstack frameworks.

Decap CMS is a Git-based content management system for static site generators. It provides an admin UI at /admin, authenticates against Git-backed backends, and lets teams edit structured content in repositories without building a custom editorial interface from scratch.

Decode JWTs, inspect claims, and verify or sign tokens with local keys during auth debugging and test setup.

Turn an APK into readable Java or decompiled source artifacts so an agent can inspect behavior before deeper reverse-engineering or triage.

Real-time speech-to-text using Deepgram Nova-2 API with streaming WebSocket connections. Supports diarization, punctuation, and language detection via the Deepgram Python SDK for podcast and meeting transcription workflows.

Transcribes audio using the Deepgram Nova-2 API with diarization, punctuation, and smart formatting. Supports streaming via WebSocket and batch via REST with pre-recorded endpoint and callback URLs.

Submits podcast MP3 URLs to Deepgram Nova-2 with paragraph and summarize features, then clusters returned timestamps into logical chapters using a sliding-window topic boundary algorithm. Outputs YouTube-compatible chapter timestamps and an RSS-ready podcast:chapters JSON feed. Optionally posts chapters as a Notion database entry.

Streams live audio to Deepgram's WebSocket API at wss://api.deepgram.com/v1/listen for real-time speech-to-text. Handles interim results, utterance detection, and speaker diarization via the Deepgram Node SDK.

Store prompts, task chains, and reusable agent workflows as versioned project files so teams can review and reuse agent behavior through Git.

Encode test, lint, build, and docs routines as named Python sessions so humans and agents run the same workflow every time.

A syntax-highlighting pager for git diff, grep, and blame output built in Rust. Provides word-level diff highlighting, side-by-side views, line numbering, and theme support using the same syntax themes as bat.