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/cortex-recon

CortexML & AI

ML and AI reconnaissance: inventories all models in production, LLM integrations and their API usage, training pipelines and their schedules, data sources and their freshness, evaluation setups, and monitoring coverage. Identifies technical debt, models running without evaluation, and unmonitored AI features.

Install

This skill

Install Cortex Recon

1. Add to marketplace

$ claude plugin marketplace add tonone-ai/tonone

2. Install this skill

$ claude plugin install cortex-recon@tonone-ai

The agent

Install Cortex

1. Add to marketplace

$ claude plugin marketplace add tonone-ai/tonone

2. Install Cortex

$ claude plugin install cortex@tonone-ai
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Full installation guide

Invoke this skill

Command|$ /cortex-recon

When to use

When taking over a project that has existing ML infrastructure and need to understand what is there before making changes. When a model-heavy codebase has grown without documentation. When auditing AI usage before a compliance review or enterprise security questionnaire.

Deep dive

AI ML Stack Inventory

ML and AI reconnaissance: inventories all models in production, LLM integrations and their API usage, training pipelines and their schedules, data sources and their freshness, evaluation setups, and monitoring coverage. Identifies technical debt, models running without evaluation, and unmonitored AI features.

Read the article

More from Cortex

All Cortex skills
CortexML

/cortex-model

Builds an end-to-end ML pipeline: data ingestion with validation, feature engineering with a feature store, model training with cross-validation and hyperparameter tuning, evaluation against a held-out test set, and deployment to a serving endpoint with monitoring. Chooses the right model type for the problem.

When building a prediction, classification, or reg…
CortexML

/cortex-prompt

Designs, versions, and evaluates prompts for LLM-powered features. Builds evaluation suites that test prompts against a representative set of inputs so quality regressions are caught before they reach users. Applies systematic prompt engineering techniques and documents what each version changes and why.

When building AI features where prompt quality dir…
CortexML

/cortex-integrate

Integrates an LLM into a production service: API client with retry and timeout handling, streaming response support, semantic caching to avoid redundant API calls, fallback provider configuration, and cost controls including token budget enforcement and request rate limiting per user.

When adding an AI feature to an existing product f…

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