react-native-native-modules
Master native modules - Turbo Modules, JSI, Fabric, and platform bridging
react-native-deployment
Master deployment - EAS Build, Fastlane, App Store, Play Store, and OTA updates
react-native-navigation
Master React Navigation - stacks, tabs, drawers, deep linking, and TypeScript integration
react-native-state
Master state management - Redux Toolkit, Zustand, TanStack Query, and data persistence
jira-agile
Manage Jira Agile boards and sprints. Use when listing boards, creating sprints, or moving issues to/from sprints.
jira-transitions
Move Jira issues through workflow states. Use when transitioning issues (To Do, In Progress, Done) or setting resolutions.
jira-project-management
Administer Jira projects. Use when creating/archiving projects, managing components, versions, roles, permissions, or project configuration.
jira-issues
Create, read, update, and delete Jira issues. Use when managing Stories, Tasks, Bugs, or Epics - includes field updates and metadata.
jira-spaces
Manage Confluence spaces for project documentation. Create, list, and delete spaces with templates. Use when setting up project documentation structure or managing Confluence content areas.
jira-safe
Implement SAFe methodology in Jira. Use when creating Epics, Features, Stories with proper hierarchy, acceptance criteria, and parent-child linking.
jira-search
Search Jira issues using JQL queries. Use when filtering issues by project, status, assignee, date, or building reports.
jira-auth
Authenticate with Jira Cloud REST API using API tokens. Use when setting up Jira connections, validating credentials, or handling rate limiting.
jira-projects
Manage Jira projects. Use when listing projects, getting project configuration, retrieving issue types, or managing components and versions.
glean-description-lookup
Use this skill when looking up field descriptions for Mozilla Glean telemetry tables (tables ending in _live or _stable, e.g. <app>_stable.<ping>_v1). Fetches descriptions from the Glean Dictionary (dictionary.telemetry.mozilla.org) using WebFetch with targeted field extraction — only the fields referenced in query.sql, never the full table schema.
model-requirements
Use this skill when gathering requirements for new BigQuery data models OR when asked to edit existing queries in bqetl. For new models, guides structured requirements interviews. For existing queries, understands current model, checks downstream dependencies, and gathers requirements for changes. Works as pre-planning before query-writer skill.
query-writer
Use this skill when writing or updating SQL queries (query.sql) or Python ETL scripts (query.py) following Mozilla BigQuery ETL conventions. ALWAYS checks for and updates existing tests when modifying queries. Coordinates downstream updates to schemas and tests. Works with bigquery-etl-core, metadata-manager, and sql-test-generator skills.
metadata-manager
Use this skill when creating or updating DAG configurations (dags.yaml), schema.yaml, and metadata.yaml files for BigQuery tables. Handles creating new DAGs when needed and coordinates test updates when queries are modified (invokes sql-test-generator as needed). Works with bigquery-etl-core, query-writer, and sql-test-generator skills.
skill-creator
ALWAYS use this skill when users ask to "create a skill", "make a skill for...", "add a new skill", or similar requests. This skill guides the creation of effective skills in the bigquery-etl repository that extend Claude's capabilities with specialized knowledge for BigQuery ETL workflows, Mozilla data platform conventions, or telemetry analysis. CRITICAL - First checks for conflicts with existing skills and recommends using/updating existing skills when appropriate. Do NOT attempt to create skills without invoking this skill first.
base-schema-audit
Use this skill to audit tables for missing column descriptions and classify each missing column into the correct base schema promotion target (global.yaml, app_<product>.yaml, or <dataset_name>.yaml). Accepts a dataset name and an optional table filter — omit the filter to audit all tables in the dataset. Outputs a per-column recommended_target report for use in _missing_metadata.yaml. Composable with schema-enricher (Step 6).
bigconfig-generator
Use this skill when creating or updating Bigeye monitoring configurations (bigconfig.yml files) for BigQuery tables. Works with metadata-manager skill.
bigquery-etl-core
The core skill for working within the bigquery-etl repository. Use this skill when understanding project structure, conventions, and common patterns. Works with model-requirements, query-writer, metadata-manager, sql-test-generator, and bigconfig-generator skills.
column-description-finder
Use this skill when looking up, auditing, or managing column descriptions from global, application-specific, and dataset-specific column definition YAML files (bigquery_etl/schema/global.yaml, bigquery_etl/schema/app_<name>.yaml, and bigquery_etl/schema/<dataset>.yaml). Use it to find a description for a specific column, list all columns in a base schema, audit which columns in a table's schema.yaml are covered by base schemas, or identify columns missing descriptions. Works with schema-enricher skill.
create-pr
Use this skill when the prompt asks to create, open, or submit a pull request in the bigquery-etl repository. Handles branch creation, staging, committing, pushing, and opening a draft PR with a structured description. Triggered by phrases like "create a PR", "open a PR", "submit a PR", "push and open a PR".
schema-enricher
Use this skill to enrich schema.yaml files for BigQuery tables in the bigquery-etl repository. Handles creating schema.yaml when it doesn't exist, finding and filling missing column descriptions (from base schemas, upstream source schema, query context, or application context), validating columns against the query, and generating a summary with recommendations for where to add new descriptions (global.yaml, <dataset_name>.yaml, or app_<name>.yaml). Works with column-description-finder skill.
schema-readme-generator
Use this skill to create or update README.md files for BigQuery ETL tables in the mozilla bigquery-etl repository. Follows layout conventions derived from comparing README files across the repo — rich style with emoji headings, Mermaid data flow diagram, graduated example queries, and concise metadata overview table. Requires schema.yaml with complete descriptions (run schema-enricher first if needed) and a complete metadata.yaml.
sql-test-generator
ALWAYS use this skill when users ask to create, generate, or write UNIT TESTS for BigQuery SQL queries. Invoke proactively whenever the request includes "test" or "tests" with a query/table name. This skill is for unit testing ONLY (not data quality checks - use bigconfig-generator for Bigeye monitoring). Works with bigquery-etl-core skill to understand query patterns.
android-emulator-skill
Production-ready scripts for Android app testing, building, and automation. Provides semantic UI navigation, build automation, accessibility testing, and emulator lifecycle management. Optimized for AI agents with minimal token output. Android equivalent of ios-simulator-skill.
token-audit
Audit a repository for token waste — find redundant context files, measure baseline, recommend optimizations
visual-review-pipeline
Automated visual review pipeline — Playwright screenshots, self-analysis, fix loop, escalation. Used by Aphrodite for UI verification.
wisdom-accumulation
Extract learnings between implementation waves. Use to share conventions and gotchas across phases.
streaming-patterns
Implement SSE, WebSockets, LLM token streaming, and real-time broadcasting in FastAPI.
codemap
Generate codebase maps with directory trees and relationships. Use for onboarding and architecture documentation.
code-review-checklist
Systematic code review with quality gates, security audit, and parallel checks. Use for structured feedback on pull requests.
cache-strategy
Cache patterns for Redis, CDN, TTL, and invalidation. Use for architecture decisions on caching strategies.
auto-continue
Auto-continue through todos with idle detection and safety gates. Use for multi-step orchestration.
artifact-management
Structured artifact trail for feature implementations — plans, implementations, reviews, and decisions.
plan-architecture
Plan feature architecture with component breakdown, data flow, and dependency mapping. Use before implementation to define contracts between layers.
agent-observability
Observability with OpenTelemetry, metrics, and logging. Use for monitoring agents and LLM calls.
agent-evaluation
Evaluate AI agent outputs — hallucination detection, quality scoring, behavioral testing, and CI/CD pipelines.
agent-coordination
Multi-agent orchestration with model routing, category delegation, and sprint management. Use for coordinating Pantheon agents.
api-design-patterns
Design RESTful APIs with pagination, filtering, and OpenAPI docs. Use for FastAPI endpoint design.
memory-bank
Memory bank rules, structure, and optimization — complete guide to Pantheon memory management.
file-prompts
Load prompts from external files with path expansion. Use for version-controlled prompts outside config.
test-architecture
Advanced testing with E2E, load, mutation, and contract tests. Use for production-ready test coverage beyond unit tests.
tdd-with-agents
TDD enforcement with RED→GREEN→REFACTOR cycle and advanced testing patterns. Use for test-driven development across all layers.
task-system
File-backed task management with dependencies and parallel execution. Use for complex work with 3+ interdependent tasks.
simplify
Behavior-preserving code simplification to reduce complexity while keeping outputs, side effects, and APIs unchanged.
session-goal
Pin session objectives to prevent scope creep. Use for alignment across long multi-agent sessions.
security-audit-pro
Security audit with SAST, SCA, containers, SBOM, PII detection. Use for comprehensive security reviews.
remote-sensing-analysis
Remote sensing pipeline with optical/SAR processing and ML classification. Use for satellite imagery analysis.
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