Turns a plain-language data/statistics task into correct, runnable Stata code, with good-vs-bad command guidance, Python↔Stata interop, and a growing recipe library (ARDL, time-series and panel regression, unit-root tests).
Not in a marketplace yet, so it loads for one session with --plugin-dir.
Plugin stata-recipes in sugatoray/aiskills. Commands read from the repo's manifest — today.
stata-recipesTurns a plain-language description of a data/statistics task into correct, runnable Stata code — a .do file or command sequence, not pseudocode. Use this whenever the user asks how to do something in Stata, wants a Stata command or .do file written or fixed, mentions Stata alongside a modeling task
Problems found in this repo's manifests
Files GitHub issue(s) for a PR's work — one flat issue, or a parent epic plus children via GitHub's native parent/child relationship — then rewrites the PR's title (kept short) and description with an itemized, correctly nested issue list.
1 skill
Animated architecture and network diagrams with flowing packets, orthogonal routing, selectable nodes, and scenario playback.
Docs skills: writes verified user documentation for a library, CLI or framework, structured like FastAPI, Pydantic, DuckDB and Effect docs: Getting Started, Tutorial, How-to Guides, Concepts, Reference, FAQ, SVG diagrams, and llms.txt for AI agents. Every snippet is run before it is published.
Skills for generating images in a variety of styles and applying visual styles or effects to existing images, including art walls and simulated comment overlays.
Persona skills: /prodigy acts as the top performer in any role or field and shares how they frame problems, deliver, avoid pitfalls, decide, and how to level up.
Repo-related skills: acting on a repository's own hosted state (issues, pull requests, releases, and similar). Files GitHub issue(s) for a PR's work and keeps the PR's title/description in sync with them.
Market data ingestion — feed normalization, OHLCV vectorization, and HNSW-indexed pattern matching
2 skills · 1 command · 1 agent
TDengine IDMP plugin with packaged skills for discovery, schema inspection, and safe operational workflows.
23 skills
Hypothesis testing, A/B experiment analysis, sample size calculation, and confidence intervals. 3 stdlib-only Python tools: Z-test/t-test/chi-square with effect sizes, sample size calculator with power tradeoffs, and Wilson score confidence intervals.
1 skill
Nine-skill stack for top-5 economics manuscripts (AER / AER: Insights / AEJ): topic selection, modern causal identification (DiD / IV / RDD / SCM / Bartik), referee-anticipating robustness, Keith-Head-style introductions, AER booktabs tables, AEA Data and Code Availability deposits (openICPSR-ready), submission preflight, and R&R rebuttal letters. Ships Stata / R / Python templates and classic-AER-paper exemplars.
15 skills
Build, deploy, and operate applications on AWS. Skills to author infrastructure-as-code (CDK, CloudFormation), use core services (Lambda, API Gateway, Step Functions, ECS/Fargate, ECR, IAM, Amazon Bedrock with Knowledge Bases and Guardrails, AWS Blocks), select and operate databases across relational, key-value, document, wide-column, graph, time-series, and in-memory engines (Aurora PostgreSQL/MySQL, Aurora DSQL, RDS, Oracle Database@AWS, DynamoDB, DocumentDB, Keyspaces, Neptune, Timestream, ElastiCache, and MemoryDB), and complete common tasks across observability (CloudWatch, X-Ray, CloudTrail, ADOT), messaging and streaming (SQS, SNS, EventBridge, Kinesis, MSK), AWS SDKs (boto3, JS v3, Swift), cost optimization, and Well-Architected Framework reviews across all six pillars.
27 skills · 1 MCP server
Time series forecasting and analysis
1 skill · 1 command
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