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Cost Anomaly Detection for Sessions

This tool performs robust outlier detection on individual session spending. Utilizing Median and Median Absolute Deviation (MAD), it calculates a modified z-score, making it highly resistant to extreme values, unlike mean+sigma methods. It specifically identifies which singular sessions are anomalous, making it crucial for cost monitoring, auditing, and integrating into CI/CD pipelines to prevent unexpected resource overruns.

Analyze Costs Per Conversation Session

cost-conversation

This skill provides a granular, session-by-session view of total accumulated costs. It lists metrics such as start time, message count, top model, and total cost for every recorded conversation. This is ideal for identifying which specific sessions consumed the most resources, which is crucial for project retrospectives and evaluating the sustainability of current session patterns.

Cost Summary Report Generator

Provides a stable, single-call interface to dump all operational cost data. This includes total spending, usage per model tier, budget status, top sessions, and federation aggregates. Output is reliable JSON or Markdown, making it ideal for other plugins, automated dashboards, or programmatic consumption.

Cost Tracking for AI Sessions

This tool automatically reads usage data from active AI coding sessions (JSONL format). It tallies token usage per model and tier, calculates the total cost in USD using specified pricing models, and persists a structured record into the cost-tracking namespace. Use this after completing a chunk of work or at the end of a session to provide accurate data for cost reporting and optimization.

AI Evaluation and Regression Testing Harness

A formal framework designed for evaluating AI-assisted code generation sessions. It implements Development Oriented Evals (EDD) principles, allowing users to define capability and regression criteria. The system supports multiple evaluation types—code-based, model-based, and human review—and tracks reliability using advanced metrics like pass@k, ensuring robust quality control for AI agents.

FastAPI Patterns For Production APIs

fastapi-patterns

This guide outlines architectural patterns and best practices for building scalable, production-ready APIs with FastAPI. It covers proper project structure, separating concerns using routers, services, and CRUD layers, implementing dependency injection for database sessions and authentication, defining Pydantic schemas for request/response, handling asynchronous operations, and managing custom error responses.

Federation Health and Status Check

federation-status

This tool provides a comprehensive overview of the federation's operational status. It allows users to check overall health, list connected peers along with their trust levels and scores, and summarize crucial metrics like active sessions, message exchanges, PII redactions, and detected threats. Use it to inspect cross-installation agent connectivity and ensure the stability of the federated system.

Long-Term Objective Tracking System

A robust framework designed to track complex, long-running objectives that span multiple sessions, weeks, or even months. It manages goals through structured milestones, maintains persistent progress records, and includes critical drift detection to ensure projects stay on target and scope creep is managed effectively. Ideal for research programs, migration projects, or multi-stage development initiatives.

Claude Memory Bridge for Unified Search

This memory bridge ingests Claude Code's local auto-memory markdown files and structures them into AgentDB. It generates high-fidelity ONNX embeddings, handles deduplication using cosine similarity, and indexes the memories in a scalable namespace. This enables seamless, unified semantic search across all historical sessions and projects, significantly enhancing RAG capabilities.

Persist and Restore Agent Sessions

session-persist

This toolset allows users to save and restore complete agent sessions, ensuring context continuity across multiple conversations. It captures the agent's entire state, including memory, configuration, task progress, and learning metrics. Use it when pausing work and needing to resume later with full context, or for checkpointing long-running tasks.

Goal Prompt Generator for Autonomous Sessions

alirezarezvani/claude-skills

This tool takes vague, rambling descriptions of desired outcomes and transforms them into a single, highly polished, autonomous prompt. Instead of building the deliverable, it crafts the comprehensive prompt (including quality bars, tool mandates, and verification loops) that a fresh AI session can execute completely on its own. Ideal for structuring complex, multi-step AI tasks.

SkillOpt-Sleep: Offline Agent Self-Evolution

alirezarezvani/claude-skills

SkillOpt-Sleep enables an AI agent to undergo a simulated "sleep cycle" for continuous, measurable self-improvement. It harvests past sessions, mines recurring tasks, and re-runs them offline. It then consolidates findings into the agent's memory and skills, ensuring only validated improvements are adopted. This process maximizes long-term competence from short-term interactions.

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