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By jcmrs
Semantic validation and translation between natural language user intent and domain-specific technical implementations. Bridges the gap between human natural language and AI specificity of needs.
npx claudepluginhub jcmrs/jcmrs-plugins --plugin semantic-linguistProvide conversational complete reference of domain mappings between Autogen, Langroid, and general concepts with cross-domain translations
Configure semantic validation sensitivity, interaction style, enabled domains, and custom user trigger words or phrases for personalized ambiguity detection
Analyze recent conversation messages for ambiguous terminology and provide semantic validation with conversational summary and optional detailed report
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AI-powered translation plugin with /tr command (--hq for high-quality)
AI/ML capabilities including prompt engineering, RAG, and chunking strategies
Use this agent when you need to create or convert prompts using the SYMBO (symbolic) notation system. This agent MUST be activated whenever generating SYMBO prompts or converting existing prompts to symbolic format. Examples: <example>Context: User wants to create a symbolic prompt for a task management system. user: 'Create a SYMBO prompt for a project task tracker with memory and learning capabilities' assistant: 'I'll use the angelos-symbo agent to create this symbolic prompt following SYMBO notation rules' <commentary>The user is requesting a SYMBO prompt, so the angelos-symbo agent must be used to ensure proper symbolic notation and rule compliance.</commentary></example> <example>Context: User has a natural language prompt they want converted to SYMBO format. user: 'Convert this prompt to SYMBO notation: You are an AI that helps with code reviews by analyzing code quality, suggesting improvements, and tracking common issues across projects' assistant: 'I need to convert this to SYMBO notation using the angelos-symbo agent' <commentary>Since this involves SYMBO prompt generation/conversion, the angelos-symbo agent must be activated.</commentary></example>
Professional AI/ML Engineering toolkit: Prompt engineering, LLM integration, RAG systems, AI safety with 12 expert plugins
Achieve certain comprehension of AI work — /grasp (κατάληψις: a grasping firmly)
This skill should be used when the model's ROLE_TYPE is orchestrator and needs to delegate tasks to specialist sub-agents. Provides scientific delegation framework ensuring world-building context (WHERE, WHAT, WHY) while preserving agent autonomy in implementation decisions (HOW). Use when planning task delegation, structuring sub-agent prompts, or coordinating multi-agent workflows.
Conversational Claude Code plugin for rigorous, multi-perspective technical spec creation using dynamic memory graphs, adaptive workflows, and multi-role analysis. Ideal for Spec Kit methodology and non-technical users.
Procedural Memory System - Learns procedures, processes, and workflows from session experiences, generates project-scoped rules for consistent behavior. Shame on you.
Persistent schema-driven running log with three-component architecture: quick-capture ideas, AI auto-detection, and backlog review librarian
Leverage Google Gemini's CLI for analyzing large codebases beyond typical context limits using @ syntax for file/directory inclusion
Transforms messy human intent and repository analysis into living operational domain profiles through 6-phase knowledge engineering pipeline
A curated marketplace of Claude Code plugins.
Status: 🧪 Testing Phase
Plugin extending the Axivo Claude Collaboration Platform, providing functionality to create Domain Profiles - rooted in behavioral programming, SRE, Domain Knowledge Graphs Ontology (langroid, crewai, langraph, semantic kernel et alii) - and comprehensive guided templates and validation.
Features:
Location: ./plugins/profile-creator
Status: 🧪 Testing Phase (Phase 1 Complete, Phase 2 Prototype Testing In Progress)
Persistent schema-driven running log that captures ideas, consultations, and Claude's reasoning patterns for cross-session learning and process memory. Addresses context window dependency by maintaining structured decision trails, assumptions, and learnings across sessions.
Features:
Commands:
/activate running-log — Initialize skill/log [type] [content] — Manual entry creation/review [filter] — Query and display logLocation: ./plugins/running-log
Status: 🧪 Testing Phase (v1.0.0 - Automated Tests Pass, Manual Validation Required)
"Shame on you." - Because Claude learns from your corrections.
Long-term learning system that transforms conversational history into actionable procedural knowledge through a three-tier memory architecture. Captures both rigid procedures (technical patterns, coding practices) and flexible processes (workflows, decision patterns), extracting recurring behaviors and synthesizing context-aware rules that persist across sessions.
Features:
.claude/rules/pms/Commands:
/pms:encode — Manual episodic encoding trigger/pms:extract — Semantic pattern extraction from sessions/pms:synthesize — Procedural rule generation from patterns/pms:reflect — Complete workflow (encode → extract → synthesize)/pms:status — Display memory system state/pms:validate — Validate JSON schema integrity/pms:reset — Clear semantic/procedural memory/pms:rebuild — Regenerate semantic knowledge from episodic recordsDocumentation:
ARCHITECTURE.md - Technical deep dive into component designSKILL.md - Plugin-dev integration guideexamples/USAGE_EXAMPLES.md - 7 workflow scenarios + troubleshootingVALIDATION_GUIDE.md - End-to-end testing instructionsCHANGELOG.md - v1.0.0 release notesLocation: ./plugins/claude-pms
Status: 🧪 Testing Phase
Documentation Reader for Axivo Claude Collaboration Platform, providing access through components, protocols, and competencies. Provides systematic access to Claude Collaboration Platform documentation, enabling both users and Claude Code to query and reference official documentation organized by platform architecture.
Features:
Commands:
/jcmrs:docs [search query] — Search official platform documentation