James P Hollingsworth

Jira project management and issue tracking integration

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Extract actionable insights from completed coding sessions. Use when a session completes to capture learnings for future sessions.

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Records atomic learned behaviors with confidence scores. Project-scoped instincts are isolated per project and auto-promote to global scope at confidence threshold 0.8. Stores instincts in .claude/context/memory/instincts.jsonl

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Independent LLM judge evaluates task completion separately from the executing agent, catching false success claims by reviewing task goal, actions taken, final state, and evidence. Produces PASS/FAIL with confidence score and reasoning.

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Guidelines for structuring and documenting Jupyter notebooks for reproducibility and clarity.

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PHP expert including Laravel, WordPress, and Drupal development

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Decision matrix for selecting multi-agent topologies (Supervisor, Swarm, Hierarchical, Conductor) with token economics, failure modes, and escalation paths

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Create production-ready Kubernetes manifests for Deployments, Services, ConfigMaps, and Secrets following best practices and security standards. Use when generating Kubernetes YAML manifests, creating K8s resources, or implementing production-grade Kubernetes configurations.

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Details Paraglide.js i18n implementations.

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NativeScript best practices and patterns for mobile applications

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General rules pertaining to Mobile UI development. Covers UI/UX best practices, state management, and navigation patterns.

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Medusa v2 rules and best practices for modular commerce architecture, Workflow SDK, data models, services, and admin customizations.

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Modern Python tooling best practices using uv, ruff, ty, and pytest. Mandates the Trail of Bits Python coding standards for project setup, dependency management, linting, type checking, and testing. Based on patterns from trailofbits/cookiecutter-python.

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Audit memory retrieval quality (drift, staleness, citation-groundedness) and produce remediation backlog.

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Master on-call shift handoffs with context transfer, escalation procedures, and documentation. Use when transitioning on-call responsibilities, documenting shift summaries, or improving on-call processes.

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Semantic search over global agent memory. Use to retrieve previously learned patterns, decisions, gotchas, and workarounds. Prevents stale-context errors across long sessions and multi-agent pipelines.

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Guide developers in creating Model Context Protocol (MCP) servers. Use for building MCP tools that enable LLMs to interact with external services. Covers TypeScript (primary) and Python FastMCP (secondary), tool annotations, Zod/Pydantic validation, and evaluation question creation.

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AI-first security scanning with Medusa. 3,000+ detection patterns covering AI/ML, agents, MCP, RAG, prompt injection, and traditional SAST vulnerabilities. Wraps Medusa CLI with SARIF/JSON parsing, structured finding output, OWASP mapping, and remediation guidance.

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Convert files to Markdown using Microsoft's MarkItDown library

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Focuses on rules and best practices for mobile-first design and responsive typography using tailwind.

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Comprehensive health check across CC auto-memory and agent-studio memory systems — detects orphans, duplicates, staleness, and threshold violations

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Autonomous fixed-budget ML experiment loop — setup, iterative hypothesis testing, git-based keep/discard tracking, and indefinite autonomous execution. Implements the karpathy/autoresearch protocol.

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Employs the logging module judiciously to log important events, warnings, and errors.

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Outlines the monorepo structure and tooling conventions, emphasizing the use of Taskfile.yml, and proper handling of environment variables.

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