cass

Index and search coding agent session histories with JSON output.

Updated Apr 6, 2026
One-click install
npx skills add https://github.com/mistakenot/auto-stack --skill cass-mistakenot
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: cass
Source: https://github.com/mistakenot/auto-stack/tree/main/.agents/skills/cass
Command: npx skills add https://github.com/mistakenot/auto-stack --skill cass-mistakenot

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Aggregates and indexes scattered coding agent session logs so developers and AI agents can quickly find prior interactions, debug recurring issues, and transfer knowledge across different agent platforms.

Core Features & Use Cases

  • Unified ingestion from many agent connectors (Codex, Claude Code, Gemini, Cursor, Aider, ChatGPT, Pi-Agent, Factory, and more).
  • High-performance CLI/TUI with an explicit robot mode that emits machine-readable JSON for agent consumption, including filters (agent, workspace, time), pagination, aggregations, and token-budget controls.
  • Incremental and full reindexing, watch mode for live updates, optional local semantic search, deduplication, robust diagnostics, and exported session formats for downstream workflows.
  • Use case: Quickly locate the exact session and code snippet where an agent solved a prior authentication bug, then feed that context to a new agent for automated handoff.

Quick Start

Search your coding agent history for "authentication error" and return up to five machine-readable JSON results including path, line, agent, title, snippet, and score.

Frequently Asked Questions about cass

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I search coding agent session histories across different platforms?

You can search coding agent session histories by indexing local logs from Codex, Claude Code, Gemini, Cursor, and Aider. This provides unified lexical and semantic search, returning snippets and scores for rapid retrieval across all platforms.

What is the best way to transfer context from a previous agent session to a new one?

Transferring context to a new agent requires filtering past interactions by agent, workspace, or time. You can locate exact solved bug snippets and export them as machine-readable JSON for automated downstream handoff.

Can I use semantic search to find specific code snippets from past AI agent interactions?

Yes, you can use optional local semantic search to find specific code snippets from past AI agent interactions. It indexes session stores to retrieve relevant context, applying token-budget controls for LLM integration.

Does robot mode output machine-readable JSON for coding agent history searches?

Yes, robot mode outputs machine-readable JSON for coding agent history searches. It includes path, line, agent, title, snippet, and score, supporting robust filtering and pagination for automated agent consumption.

How do I index and deduplicate session logs from multiple coding agents?

You index and deduplicate session logs from multiple coding agents by running incremental or full reindexing. Watch mode provides live updates, ensuring your filtered corpus remains current and clean for cross-agent knowledge transfer.

What are the limitations of searching local coding agent session stores?

Limitations of searching local coding agent session stores include managing token budgets for LLM integration and handling incremental reindexing overhead. Robust diagnostics help mitigate issues when deduplicating across diverse agent formats.