pythondoc-authoring

Skills for designing, writing, reviewing, and debugging GitHub Actions workflows that consume netcracker/qubership-workflow-hub actions and Netcracker/.github templates.

3 skills

Apply NiFi 1.x to 2.x upgrade advisor recommendations to exported flow JSON files.

1 skill

Author Architecture Decision Records that follow the ADR contract used across Qubership repositories.

1 skill

Review GitHub pull requests and GitLab merge requests from an isolated Git workspace and publish feedback with user authorization.

1 skill

Agent-guided setup, testing, repair, and delivery verification.

1 skill

Authoring classify rules, response-scope handling, adapters, and tests for the api-diff library.

1 skill

Converts books, documentation folders, and source collections (PDF, EPUB, DOCX, HTML, Markdown, RST, AsciiDoc, RTF, MOBI/AZW) into structured agent skills: a master SKILL.md with core frameworks and a topic index, on-demand chapter files, a glossary, a patterns file, and a decision cheatsheet. Ships 4 stdlib-only tools (multi-format extractor with invisible-Unicode sanitization, four-family generated-skill validator covering frontmatter/safety/budget/index, pre- and post-flight token budget estimator with a worth-converting verdict, and a plugin emitter that wraps a compiled skill as an installable claude-skills package behind a rights gate), 5 references citing 7-8 sources each, a cs-book-to-skill agent, and /cs-book-to-skill + /cs-book-to-plugin commands. Derived from virgiliojr94/book-to-skill (MIT).

1 skill · 2 commands · 1 agent

67 specialized skills for full-stack development: 12 language experts (Python, TypeScript, Go, Rust, C++, Swift, Kotlin, C#, PHP, Java, SQL, JavaScript), 8 backend frameworks, 7 frontend/mobile, plus infrastructure, DevOps, security, and testing skills. Includes 9 project workflow commands for epic planning, discovery, execution, and retrospectives.

67 skills · 10 commands

Granola MCP connects your meeting history to ChatGPT so your assistant can pull real context from past conversations while you work. Use MCP when you're already working on something bigger: - Writing PRDs or proposals: Pull customer feedback, stakeholder input, and decisions from relevant meetings directly into your draft - Building presentations or reports: Combine insights from multiple conversations with your other research and data - Coding with context: Give your AI the project background, requirements, and technical decisions discussed in planning meetings - Strategic analysis: Merge meeting insights with documents, data, and other sources for comprehensive analysis How it works: Your AI assistant can search your Granola meetings by topic, person, company, or timeframe - then cite specific conversations in its responses. No more switching tabs to find "what the customer said" or "when we decided that." The difference: Instead of copy-pasting meeting notes into prompts, your AI pulls exactly what it needs from your meeting history automatically. You stay focused on the work, not the research or context.

1 MCP server · app connector

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

A coordinated engineering team of named AI specialists that remembers your project between sessions. Call yui to route work, or call any specialist directly: Go (jaan, siim, mart), Angular (liis, kadi, tiiu), iOS (ren, shu, ryo), Python (eero, anu, ivo), React (noa, rui, aki), SQL (saku), NoSQL (remo), architecture for any stack (kai), process management (enn), and DevOps/infra (sora). Each ships as both a skill and a subagent. Bundled hooks capture finished work when a session ends and say at the next session start that saved work exists, and record per-session and per-agent token and time usage. Every specialist follows the same discipline: read context first, make the smallest correct change, verify.

23 skills · 20 agents · hooks

Data lake, analytics, search, streaming, ETL, and orchestration workflows with S3 Tables, AWS Glue, Athena, Amazon Redshift, Amazon OpenSearch Service, Amazon MSK, Amazon Managed Service for Apache Flink, Amazon MWAA, and Amazon SageMaker Catalog. Covers managed Iceberg tables on S3 Tables, ingestion from JDBC databases (Oracle, SQL Server, PostgreSQL, MySQL, RDS), Amazon Redshift, Snowflake, BigQuery, and DynamoDB, AWS Glue Data Catalog inventory and asset discovery, federated Athena queries, vector storage and semantic search on Amazon S3 Vectors, Amazon OpenSearch Service and Serverless (migration from Solr/Elasticsearch, provisioning, vector/semantic/hybrid search, log analytics, trace analytics), Amazon MSK Provisioned with Standard and Express brokers (cluster sizing, performance and consumer lag troubleshooting, topic management, MSK Replicator for disaster recovery and active-active replication, and Streaming Tables delivery to S3 Tables), migrating self-managed Apache Kafka to MSK Express, Apache Flink application development on Amazon Managed Service for Apache Flink, and Amazon MWAA Provisioned and MWAA Serverless (authoring, testing, and debugging DAGs and workflows, and Airflow version upgrades for provisioned environments), and Amazon SageMaker Catalog and AWS Glue Data Catalog curation (business descriptions, glossaries, metadata forms, publishing, and safe asset retirement) with subscription-based access requests, approvals, audits, and revocations.

18 skills · 1 MCP server