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external-sync-wizard
This skill is an expert guide for setting up bidirectional synchronization between SpecWeave and external tools like GitHub Issues, Jira, and Azure DevOps. It provides interactive wizards to configure sync direction and helps establish SpecWeave as the local source of truth.
technical-writing
This skill provides expert technical writing assistance for developer documentation including README files, API documentation, tutorials, and changelogs, helping create clear, structured, and maintainable documentation following industry best practices.
role-orchestrator
A multi-agent orchestration system that coordinates specialized roles (PM, Architect, DevOps, QA, etc.) to collaboratively execute complex, multi-step projects through intelligent task decomposition and structured workflow management.
spec-generator
Generates comprehensive specification documentation (spec.md, plan.md, tasks.md with embedded tests) for SpecWeave increments using flexible, context-aware templates, ensuring proper project assignment and structured planning.
progress-sync
This skill automatically synchronizes progress across all systems with one command, including auto-creating missing external issues in GitHub/JIRA/ADO when none exist, ensuring complete end-to-end tracking without manual intervention.
python-backend
A specialized Python backend developer skill for building APIs with FastAPI, Django, or Flask, handling database integration, data processing, machine learning model serving, and background tasks with comprehensive tooling and best practices.
time-series-forecaster
This skill performs time series forecasting using ARIMA, Prophet, LSTM, and statistical methods to predict future trends, detect seasonality, and provide confidence intervals, integrated with SpecWeave's workflow for accurate temporal predictions.
confluent-ksqldb
This skill provides expert guidance on Confluent ksqlDB, enabling real-time stream processing on Kafka topics using SQL-like queries. It covers core concepts like streams and tables, joins, aggregations, windowing, and creating materialized views for immediate analytics.
model-explainer
This skill provides model interpretability using SHAP, LIME, and feature importance to explain why models make specific predictions. It helps build trust, debug models, and meet regulatory requirements by generating human-readable explanations for both individual predictions and overall model behavior.
device-testing
This skill provides comprehensive React Native testing expertise, covering unit tests with Jest, integration tests, component testing with React Native Testing Library, and E2E testing with Detox on simulators and real devices.
hetzner-provisioner
This skill provisions budget-friendly Hetzner Cloud infrastructure using Terraform/Pulumi. It generates IaC code for servers, databases, SSL, and Docker deployment, enabling full-stack SaaS hosting for as low as $10-15/month.
code-standards-analyzer
Analyzes codebases to automatically discover, document, and audit coding standards, naming conventions, and patterns while detecting anti-patterns and security issues, generating evidence-based documentation to align standards with actual code practices.
increment-planner
Creates structured implementation plans for any type of software increment (features, hotfixes, bugs, etc.) by automatically generating numbered directories, templates, and preventing duplicates within user projects.
multi-project-spec-mapper
This skill intelligently analyzes user stories and automatically maps them to appropriate projects (FE, BE, MOBILE, INFRA) based on content and tech stack. It organizes specifications into project-specific folders and splits monolithic specs, streamlining management for multi-project setups like microservices or multi-team environments.
github-issue-standard
This skill enforces a mandatory, standardized format for all GitHub issues created by SpecWeave. It ensures issues have consistent titles with proper feature/user story links, checkable acceptance criteria and tasks, working GitHub URLs, and extracted priority metadata, improving traceability and workflow automation.
reflect
A self-improving AI memory system that learns from user corrections and successful patterns across sessions, storing knowledge in skill-specific MEMORY.md files to prevent repeated mistakes and enable continuous improvement.
service-connect
This skill automatically orchestrates connections to external services by intelligently selecting the optimal method from MCP servers, REST APIs, SDKs, or CLIs, ensuring reliable access to databases and cloud platforms while avoiding common connection issues.
github-issue-tracker
Enables fine-grained task tracking within GitHub issues by automatically creating checklists with time estimates, posting detailed completion comments with change logs and time tracking, and managing task assignments and blockers for collaborative development teams.
billing-automation
This skill automates billing systems for recurring payments, invoicing, and subscription management, handling tasks like dunning, proration, and tax calculation to streamline SaaS and subscription-based revenue operations.
detector
This skill detects SpecWeave projects and provides workflow documentation for its slash commands. It explains how to use commands like /inc, /do, and /progress to manage development increments with features like auto-resume, auto-close, and progress tracking.
ado-multi-project
This skill organizes specifications and splits tasks across multiple Azure DevOps projects by intelligently analyzing content to map increments to the correct project, supporting various organizational architectures like project-per-team and area-path-based setups.
increment-quality-judge-v2
This skill provides AI-powered quality assessment using the LLM-as-Judge pattern, evaluating specifications and plans across 7 dimensions including risk scoring to deliver PASS/CONCERNS/FAIL decisions with actionable recommendations.
ado-mapper
This skill enables bidirectional synchronization between SpecWeave increments and Azure DevOps work items, handling export, import, and conflict resolution while maintaining traceability between the two systems.
experiment-tracker
Organizes machine learning experiments by automatically configuring tracking tools (MLflow, Weights & Biases, or built-in) to log all runs within SpecWeave increments, ensuring reproducibility, team knowledge preservation, and easy experiment comparison.