policyengine-github-agent-skill
Guidance for working with the PolicyEngine GitHub agent bot
policyengine-interactive-tools
Building standalone interactive calculators and dashboards that embed in policyengine.org
policyengine-microsimulation
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policyengine-modal-deployment
Deploying PolicyEngine backend APIs to Modal — workspace setup, authentication, deployment commands, environments, and troubleshooting
policyengine-python-client
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policyengine-simulation-mechanics
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policyengine-vercel-deployment
Deploying PolicyEngine frontend apps to Vercel - naming, scope, team settings
policyengine-analysis
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policyengine-district-analysis
Analyze policy impacts for congressional districts and representatives' constituents. Use when the user mentions a specific district (NY-17, CA-52), a representative's name, or asks about geographic policy impacts at district level. Provides HuggingFace district datasets.
content-generation
Generate marketing content from PolicyEngine blog posts - social media images, social post copy, and branded assets
l0
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microcalibrate
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microdf
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microimpute
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policyengine-uk-data
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policyengine-us-data
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policyengine-design
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policyengine-plugin-maintenance
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policyengine-research-lookup
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policyengine-standards
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policyengine-user-guide
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policyengine-writing
PolicyEngine writing style for blog posts, documentation, PR descriptions, and research reports - emphasizing active voice, quantitative precision, and neutral tone
policyengine-canada
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policyengine-healthcare
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policyengine-uk
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policyengine-us
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policyengine-tailwind-shadcn
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policyengine-ui-kit-consumer
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policyengine-aggregation
PolicyEngine aggregation patterns - using adds attribute and add() function for summing variables across entities
policyengine-code-organization
Code organization patterns for PolicyEngine - variable naming conventions, folder structure, file organization
free-shipping-threshold-analysis
Analyzes Fulfil order data to determine profitable free shipping thresholds using order value distribution, hero product analysis, and shipping economics. Use when merchants ask about free shipping strategy, threshold optimization, shipping offers, AOV analysis, or need data-driven shipping decisions. Requires access to Fulfil data warehouse (sales_orders, shipments tables).
fulfillment-optimization
Analyzes warehouse shipment backlogs to optimize batch picking and packing workflows. Use when a merchant needs help clearing order backlogs, improving picking efficiency, optimizing batch sizes, or understanding order composition patterns. Triggers on questions about shipping delays, picking strategies, packing station setup, warehouse workflow optimization, or order fulfillment bottlenecks. Works with Fulfil MCP data or user-provided shipment data (CSV/Excel).
skill-developer
Create and manage Claude Code skills following Anthropic best practices. Use when creating new skills, modifying skill-rules.json, understanding trigger patterns, working with hooks, debugging skill activation, or implementing progressive disclosure. Covers skill structure, YAML frontmatter, trigger types (keywords, intent patterns, file paths, content patterns), enforcement levels (block, suggest, warn), hook mechanisms (UserPromptSubmit, PreToolUse), session tracking, and the 500-line rule.
debug
Apply systematic debugging methodology using medical differential diagnosis principles. Trigger when AI modifies working code and anomalies occur, or when users report unexpected test results or execution failures. Use observation without preconception, fact isolation, differential diagnosis lists, deductive exclusion, experimental verification, precise fixes, and prevention mechanisms.
error-troubleshooter
Automatically troubleshoot unexpected results OR command/script errors without user request. Triggers when: (1) unexpected behavior - command succeeded but expected effect didn't happen, missing expected errors, wrong output, silent failures; (2) explicit failures - stderr, exceptions, non-zero exit, SDK/API errors. Applies systematic diagnosis using error templates, hypothesis testing, and web research for any Stack Overflow-worthy issue.
adr-creator
Create Architecture Decision Records (ADRs) documenting significant technical decisions for the FF Analytics platform. This skill should be used when making architectural choices, evaluating alternatives for data models or infrastructure, documenting trade-offs, or when the user asks "should we use X or Y approach?" Guides through the ADR creation workflow from context gathering to documentation.
data-ingestion-builder
Build new data ingestion providers following the FF Analytics registry pattern. This skill should be used when adding new data sources (APIs, files, databases) to the data pipeline. Guides through creating provider packages, registry mappings, loader functions, storage integration, primary key tests, and sampling tools following established patterns.
data-quality-test-generator
Generate comprehensive dbt test suites following FF Analytics data quality standards and dbt 1.10+ syntax. This skill should be used when creating tests for new dbt models, adding tests to existing models, standardizing test coverage, or implementing data quality gates. Covers grain uniqueness, FK relationships, enum validation, and freshness tests.
dbt-model-builder
Create dbt models following FF Analytics Kimball patterns and 2×2 stat model. This skill should be used when creating staging models, core facts/dimensions, or analytical marts. Guides through model creation with proper grain, tests, External Parquet configuration, and per-model YAML documentation using dbt 1.10+ syntax.
notebook-creator
Create Jupyter notebooks for FF Analytics following project conventions. Use this skill when the user requests analysis notebooks for player evaluation, roster health, trade scenarios, market trends, or projection quality analysis. Guides through notebook structure, DuckDB connections, mart queries, visualization standards, and freshness banner patterns.
sprint-1-executor
Execute Sprint 1 tasks for FASA optimization and trade analytics. This skill should be used when the user requests execution of any Sprint 1 task (Tasks 1.1-1.4, 11-13, 2.1-2.4, 3.1-3.2), including cap space parsing, Sleeper integration, FASA target marts, FA acquisition history, roster depth analysis, enhanced FASA targets, notebooks, valuation models, trade analysis, automation workflows, or documentation. Each task is atomic, standalone, and designed for independent execution with built-in validation. Current focus: Phase 2 FASA Intelligence (Tasks 11-13, 1.4).
sprint-planner
Design and structure development sprints with atomic, LLM-ready task files. This skill should be used when the user wants to plan a new development sprint, break down complex projects into executable tasks, or create a sprint execution framework. Produces sprint plans, atomic task specifications, and corresponding executor skills for LLM coding agents.
strategic-planner
Design comprehensive technical specifications and strategic plans for data architecture and analytics projects. This skill should be used when planning major features, creating SPEC documents, assessing product requirements, breaking down complex projects into phases, or documenting architectural strategies like SPEC-1. Guides through requirements gathering, MoSCoW prioritization, phase planning, and open items tracking.
ff-dynasty-strategy
Expert guidance on dynasty fantasy football strategies, player valuation frameworks, roster construction, trade evaluation, and asset management. Use this skill when analyzing dynasty trades, evaluating player value, designing roster strategies, assessing competitive windows, or answering fantasy football domain questions. Covers VoR/VBD methodologies, aging curves, market inefficiencies, draft pick valuation, and win-now vs rebuild strategies.
ff-ml-modeling
Expert guidance on machine learning and feature engineering for fantasy football player projection models. Use this skill when building predictive models, engineering features from player statistics, selecting appropriate ML algorithms, or addressing sports-specific ML challenges. Covers feature engineering patterns, model selection frameworks, validation strategies, and interpretability techniques for fantasy football analytics.
ff-statistical-methods
Expert guidance on statistical analysis methodologies and Monte Carlo simulation for fantasy football. Use this skill when selecting regression approaches, designing simulations, performing variance analysis, or conducting hypothesis tests. Covers regression types (OLS, Ridge, Lasso, GAMs), Monte Carlo frameworks, regression-to-mean analysis, and statistical best practices for player performance modeling.
acceptance-test
Use when writing acceptance tests or adding scenarios to spec.yaml. Defines Given/When/Then format and acceptance test patterns.
create-skill
Use when creating or modifying skills. Defines skill file structure, naming conventions, and integration patterns.
evaluation
Use when creating or updating agent evaluation suites. Defines eval structure, rubrics, and validation patterns.
install-dependencies
Use when adding project dependencies. Defines dependency management rules and language-specific patterns.
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