3. Data, Science & AI

Compresses conversation history and reduces token usage for efficient LLM context management in long-running sessions.

Enables implementation of agent memory systems including cross-session persistence, knowledge graphs, and vector store-based entity tracking for AI applications.

Models agent mental states using BDI architecture, enabling cognitive agent development and neuro-symbolic AI integration through belief-desire-intention frameworks.

Analyzes AI agent reasoning traces to debug, optimize, and improve performance, resolving failures and context degradation.

Diagnoses and mitigates context degradation, attention issues, and context confusion in AI agent systems.

Automates book data extraction, SFT dataset creation, and style model training with LoRA and author voice replication capabilities.

Provides design and implementation guidance for multi-agent system patterns including supervisor, swarm, context isolation, and agent coordination.

Guides LLM project planning, pipeline architecture design, task-model evaluation, and cost estimation for agent-assisted development.

Optimizes AI model context to reduce token usage and improve efficiency through techniques such as KV-cache and context partitioning.

Enables evaluation of AI agent performance through test frameworks, rubrics, and multi-dimensional quality gates for agent pipelines.

Enables systematic LLM output evaluation through rubric creation, bias mitigation, and automated scoring for model comparison and quality assessment.

Optimizes LLM context window usage through semantic search and targeted references, improving model efficiency and relevance in AI applications.

Retrieves economic indicators like GDP, unemployment, and inflation from FRED API for macroeconomic analysis and research.

Accesses public cancer imaging datasets from NCI Imaging Data Commons for AI research via metadata queries and browser visualization without authentication.

Executes direct PostgreSQL queries for debugging, performance analysis, and SQL optimization using read-only connections.

Executes direct ClickHouse queries for analytics, metrics, and event data exploration with read-only access.

Provides read-only administrative access to Meilisearch index status, health, tasks, and configuration for debugging and monitoring search operations.

Integrates with protocols.io API for managing scientific protocols, including creation, updates, steps, materials, and collaborative features in research workflows.

Offers AI-ready drug discovery datasets including ADME, toxicity, and DTI benchmarks with molecular oracles for therapeutic ML and pharmacological prediction.

ETE toolkit for phylogenetic tree manipulation, evolutionary event detection, orthology/paralogy analysis, and visualization in phylogenomics research.

Toolkit for microbiome analysis with sequence alignment, phylogenetic trees, diversity metrics, and statistical tests like PERMANOVA.

Queries NCBI ClinVar for variant clinical significance, enabling gene/position searches, pathogenicity interpretation, and VCF annotation in genomic medicine.

Queries Ensembl REST API for genomic data including gene lookups, sequence retrieval, and variant analysis across 250+ species.

Performs differential gene expression analysis on RNA-seq data using DESeq2 in Python, including Wald tests, FDR correction, and volcano/MA plots.