Data & AI

Creates or modify a configuration property of a microservice. Use when explicitly asked by the user to create or modify a configuration property of a microservice, or when it makes sense to externalize a certain setting of the microservice.

Creates or modify a metric of a microservice. Use when explicitly asked by the user to create or modify a custom metric for a microservice, or when it makes sense measure a certain operation taken by the microservice.

Test-Driven Development patterns for testing AI deliberation features. Use when adding new deliberation features, adapters, convergence detection, or decision graph components. Encodes TDD workflow: write test first → implement → verify.

Query and analyze the AI Counsel decision graph to find past deliberations, identify patterns, and debug memory issues

Guide for creating new CLI or HTTP adapters to integrate AI models into the AI Counsel deliberation system

Guide for safely adding new MCP tools to the AI Counsel server

Expert debugging guide for AI Counsel's convergence detection system. Use when deliberations aren't converging as expected, early stopping fails, semantic similarity seems wrong, or voting vs semantic status conflicts occur.

Analyze an existing PostgreSQL database to identify tables that would benefit from conversion to TimescaleDB hypertables

Comprehensive PostgreSQL-specific table design reference covering data types, indexing, constraints, performance patterns, and advanced features

Use when design is complete and you need detailed implementation tasks for engineers with zero codebase context - creates comprehensive implementation plans with exact file paths, complete code examples, and verification steps assuming engineer has minimal domain knowledge

Use when creating or developing, before writing code or implementation plans - refines rough ideas into fully-formed designs through collaborative questioning, alternative exploration, and incremental validation. Don't use during clear 'mechanical' processes

Self-learning system that captures corrections during sessions and reminds users to run /reflect to update CLAUDE.md. Use when discussing learnings, corrections, or when the user mentions remembering something for future sessions.

Analyze meeting notes to find action items and create Jira tasks for assigned work. When Claude needs to: (1) Create Jira tasks or tickets from meeting notes, (2) Extract or find action items from notes or Confluence pages, (3) Parse meeting notes for assigned tasks, or (4) Analyze notes and generate tasks for team members. Identifies assignees, looks up account IDs, and creates tasks with proper context.

Automatically convert Confluence specification documents into structured Jira backlogs with Epics and implementation tickets. When Claude needs to: (1) Create Jira tickets from a Confluence page, (2) Generate a backlog from a specification, (3) Break down a spec into implementation tasks, or (4) Convert requirements into Jira issues. Handles reading Confluence pages, analyzing specifications, creating Epics with proper structure, and generating detailed implementation tickets linked to the Epic.

Intelligently triage bug reports and error messages by searching for duplicates in Jira and offering to create new issues or add comments to existing ones. When Claude needs to: (1) Triage a bug report or error message, (2) Check if an issue is a duplicate, (3) Find similar past issues, (4) Create a new bug ticket with proper context, or (5) Add information to an existing ticket. Searches Jira for similar issues, identifies duplicates, checks fix history, and helps create well-structured bug reports.

Generate project status reports from Jira issues and publish to Confluence. When Claude needs to: (1) Create a status report for a project, (2) Summarize project progress or updates, (3) Generate weekly/daily reports from Jira, (4) Publish status summaries to Confluence, or (5) Analyze project blockers and completion. Queries Jira issues, categorizes by status/priority, and creates formatted reports for delivery managers and executives.

Detect and capture technical preferences, naming conventions, and architectural practices from user messages into Packmind standards. Trigger when user prescribes HOW to code rather than WHAT to build (e.g., "Use snake_case for columns", "Always use async/await", "Prefix interfaces with I"). Does NOT trigger for feature requests, bug reports, or general implementation tasks without coding preferences.

Search across company knowledge bases (Confluence, Jira, internal docs) to find and explain internal concepts, processes, and technical details. When Claude needs to: (1) Find or search for information about systems, terminology, processes, deployment, authentication, infrastructure, architecture, or technical concepts, (2) Search internal documentation, knowledge base, company docs, or our docs, (3) Explain what something is, how it works, or look up information, or (4) Synthesize information from multiple sources. Searches in parallel and provides cited answers.

Extracts files from repomix-packed repositories, restoring original directory structures from XML/Markdown/JSON formats. Activates when users need to unmix repomix files, extract packed repositories, restore file structures from repomix output, or reverse the repomix packing process.

This skill should be used when establishing comprehensive QA testing processes for any software project. Use when creating test strategies, writing test cases following Google Testing Standards, executing test plans, tracking bugs with P0-P4 classification, calculating quality metrics, or generating progress reports. Includes autonomous execution capability via master prompts and complete documentation templates for third-party QA team handoffs. Implements OWASP security testing and achieves 90% coverage targets.