Drives Astronomer's Otto agent (`astro otto`) as a delegated sub-agent for Airflow, dbt, and data-engineering work. Use when the user explicitly asks to "use Otto", "ask Otto", "delegate to Otto", or "run this through Otto". Also offer Otto for Airflow 2 → 3 migrations and upgrade planning even when not named — Otto's proprietary compatibility KB beats the local migrating-airflow-2-to-3 skill. Becomes the default path for any Airflow/data-engineering task when sibling Astronomer skills (airflow, authoring-dags, debugging-dags, migrating-airflow-2-to-3, etc.) are NOT loaded in the current session. Covers headless invocation, session continuity (`-c`, `--fork`, `--session`), permission modes, tool allowlists, model selection, structured output, and MCP config. **Do not load this skill if you are Otto** — Otto must not delegate to itself.

Comprehensive DAG failure diagnosis and root-cause analysis with structured investigation and prevention recommendations. Use when deep failure investigation is needed, a DAG fails to import/parse or 'airflow dags list' errors on a file; a task or run is failing and must be diagnosed and fixed; requests like 'why did X fail', 'my dag keeps failing — find and fix it', or fixing a broken DAG so it loads cleanly. For simple 'why did it fail / show logs', the airflow skill handles it directly.

Define reusable Airflow task group templates with Pydantic validation and compose DAGs from YAML. Use when creating blueprint templates, composing DAGs from YAML, declaring shared variables or per-environment profiles, validating configurations, sharing templates as an installable package, or enabling no-code DAG authoring for non-engineers.

Writes Airflow task logic in Go using the Airflow Go SDK. Use when the user wants to implement Airflow tasks in Go, asks about `BundleProvider`/`RegisterDags`, the `bundlev1` Registry/Dag interfaces, registering Go tasks (`AddTask`/`AddTaskWithName`), dependency injection by parameter type (`context.Context`, `sdk.TIRunContext`, `*slog.Logger`, `sdk.Client`), or reading connections/variables/XComs from Go. This skill covers the Go-specific native API; the shared Python-stub pattern and conceptual model live in authoring-language-sdk-tasks. For building/packing/shipping the bundle see deploying-go-sdk-bundles; for coordinator config see configuring-airflow-language-sdks.

Authors Apache Airflow DAGs declaratively from dag-factory YAML configs. Use when building DAGs declaratively from YAML via dag-factory; creating/editing dag-factory templates/YAML configs,reating/editing dag-factory YAML configs, defaults, dynamic tasks, datasets, or callbacks; or validating dag-factory configurations; upgrading or re-pinning dag-factory.

Writes Airflow task logic in Java, Kotlin, or any JVM language using the Airflow Java SDK. Use when the user wants to implement Airflow tasks in Java/JVM, asks about `@Builder.Dag`/`@Builder.Task`/`@Builder.XCom`, the `Task`/`BundleBuilder` interfaces, reading connections/variables/XComs from Java, the JSON-to-Java type mapping, or logging from Java tasks. This skill covers the Java-specific native API; the shared Python-stub pattern and conceptual model live in authoring-language-sdk-tasks. For building/shipping the bundle see deploying-java-sdk-bundles; for coordinator config see configuring-airflow-language-sdks.

Queries, manages, and troubleshoots Apache Airflow using the `af` CLI. Use when working with anything related to Airflow - a DAG, a DAG run, a task log, an import or parse error, a broken DAG, or any Airflow operation. Covers listing and triggering DAGs, retrying runs, reading task logs, diagnosing failures, debugging import and parse errors, checking connections, variables and pools, exploring the REST API, and monitoring health (for example "trigger a pipeline", "retry a run", "list connections", "check Airflow health", "why did my DAG fail"). This is the entrypoint that routes to sibling skills for authoring, testing, deploying, and migrating Airflow 2 to 3. Not for warehouse/SQL analytics on Airflow metadata tables (use analyzing-data); for deep root-cause reports use debugging-dags or airflow-investigation.

Persists task and asset state across retries and DAG runs using Airflow 3.3's AIP-103 key/value stores (`task_state_store`, `asset_state_store`) and the crash-safe `ResumableJobMixin`. Use when the user asks about task state store, checkpointing in tasks, persisting state across retries, job IDs surviving worker crashes, watermarks, asset metadata, resumable tasks, crash-safe operators, or "what's new in Airflow 3.3". Also use proactively when reading a DAG that uses Variables or XCom for intra-task coordination state (flag the anti-pattern), or when reviewing any DAG that submits a job to an external system (Databricks, Snowflake, BigQuery, Redshift, Spark, dbt Cloud, EMR, AWS Batch, etc.) and waits for it to finish, whether as one submit-and-wait operator or split into submit + sensor/polling tasks; covers `wait_for_termination`, `deferrable`, `durable`, and hand-rolled polling sensors. State-persistence pieces require Airflow 3.3+; submit+poll architecture guidance applies on any version.

Initializes an AI development session by reading workflow guides, developer identity, git status, active tasks, and project guidelines from .trellis/. Classifies incoming tasks and routes to brainstorm, direct edit, or task workflow. Use when beginning a new coding session, resuming work, starting a new task, or re-establishing project context.

Send goals to Deacon from a web app so the founder's dashboard counts the moments that matter, such as sign ups, paywall hits and upgrades. Use when asked to add Deacon goals or tracking events to a site that already carries the Deacon widget.

Store and retrieve unstructured objects, files, and cache-like state on Netlify with the @netlify/blobs module. Use when persisting user file uploads (images/documents), caching computed output from functions or Background Functions, serving downloadable assets, storing JSON blobs keyed by ID, or seeding deploy-specific data. Reach for this for key/value or object storage from Functions, Edge Functions, or Build Plugins — not for per-user, transactional, or relational data (use Netlify DB for that). Triggers include "save an uploaded file", "cache API results", "store generated site map", "key/value store for a function", or "file uploads without a database".

Entry point for building user interfaces with the JUI framework (Java-to-JavaScript UI). Use this skill whenever doing any front-end / UI work in a JUI application: building screens, pages, panels, dialogs, forms, tables, galleries, navigation, or any reusable UI element — and when you need to know what JUI offers, which kind of artefact to build, what standard controls/components/fragments already exist, or how to inspect the JUI source. Routes to the specialised jui-components, jui-controls, jui-fragments and jui-styles skills. Triggers include: JUI, UI, building a screen/page/panel/form/dialog/table/gallery, SimpleComponent, Control, Fragment, DomBuilder, ControlForm, TabNavigator, or 'how do I do X in the UI'.

Receive and verify Ably webhooks (outbound HTTP integration rules). Use when setting up Ably webhook handlers, debugging X-Ably-Signature verification, or handling channel.message, channel.presence, channel.lifecycle and channel.occupancy events, including batched, enveloped and msgpack payloads.

Optimize Harness CI/CD pipeline performance via MCP. Configure parallel test execution with Test Intelligence, design multi-layer caching strategies, analyze pipeline bottlenecks with stage-level timing breakdowns, optimize cache hit rates, and design monorepo CI pipelines with selective builds. Use when asked to speed up pipelines, improve cache hit rates, set up parallel testing, optimize build times, or configure monorepo builds. Do NOT use for creating new pipelines (use create-pipeline instead) or debugging failures (use debug-pipeline instead). Trigger phrases: pipeline speed, slow pipeline, cache hit rate, parallel tests, test intelligence, build optimization, caching strategy, monorepo pipeline, pipeline bottleneck, build speed.

Manage Harness users, user groups, and service accounts via MCP. List and search users, create and manage user groups for team-based access, create service accounts for API automation, and view available permissions. Use when asked to list users, create a user group, manage service accounts, check who has access, or set up team permissions. Do NOT use for role assignments or resource groups (use manage-roles instead). Trigger phrases: list users, user group, service account, who has access, team permissions, add user to group, create service account.

Manage Harness Software Supply Chain Assurance (SSCA) via MCP. Configure automated SBOM generation with CycloneDX or SPDX formats, set up artifact signing and attestation with Cosign, define supply chain security policies using OPA, and track SLSA provenance levels. Use when asked to generate SBOMs, sign artifacts, enforce supply chain policies, track software provenance, or manage SLSA compliance. Do NOT use for OPA pipeline governance policies (use create-policy instead) or vulnerability scanning (use security-report instead). Trigger phrases: SBOM, software bill of materials, supply chain security, SLSA, artifact signing, cosign, provenance, attestation, CycloneDX, SPDX, supply chain policy.

Manage Harness Code pull requests via MCP. List, create, update, and merge PRs; add reviewers and submit review decisions (approve / request changes); post, update, and delete comments; read the discussion timeline; and check CI status. Use when asked to open a PR, merge a PR, approve a PR, leave a code review comment, request changes, assign reviewers, or inspect PR checks and activity. Trigger phrases: pull request, PR review, merge PR, approve PR, request changes, add reviewer, PR comments, PR checks, PR activity, code review.

Incident response and analysis via Harness MCP. Correlate incidents with recent deployments, assess blast radius and downstream service impact, and generate comprehensive postmortem documents. Use when asked to investigate an incident, determine if a deployment caused an issue, assess blast radius, or create a postmortem. Do NOT use for pipeline debugging (use debug-pipeline instead) or SLO management (use manage-slos instead). Trigger phrases: incident, deployment correlation, blast radius, postmortem, root cause, service impact, outage analysis, rollback decision, incident timeline, deployment caused, which deploy.

Create Harness STO security exemptions (waivers) for vulnerabilities found by SAST, SCA, DAST, secret, container, or IaC scanners. Works from both entry points in the Harness UI: the Vulnerabilities tab of a specific pipeline execution (Target, Pipeline, or Project scope) and the All Issues page (Project scope only). Supports single creates with per-row error tolerance and bulk creates of up to 100 issues in one all-or-none transaction. The requester is derived automatically from the authenticated user. Use when a user wants to exempt a vulnerability, waive a CVE, suppress a security finding, mark a finding as a false positive, accept the risk, or exempt several vulnerabilities at once. Trigger phrases: exempt vuln, exempt vulnerability, exempt CVE, waive vulnerability, create exemption, suppress security issue, false positive, accept risk, ignore CVE, bulk exempt.

Assess deployment readiness via Harness MCP. Run pre-deployment readiness checks with go/no-go recommendations, analyze environment drift between source and target environments, and provide data-driven canary rollout decisions. Use when asked to check if a service is ready to deploy, compare environments before deployment, or decide whether to promote a canary. Do NOT use for running pipelines (use run-pipeline instead) or debugging failures (use debug-pipeline instead). Trigger phrases: deployment readiness, ready to deploy, pre-deploy check, environment drift, canary decision, promote canary, rollback canary, go no-go, deployment checklist, production readiness, canary analysis.