cass

name	cass
description	Mine past agent sessions for working prompts, decisions, and patterns. Use when "what did I ask?", "find that prompt", session archaeology, or agent history.

cass Session Search

Core Insight: Your repeated prompts are your best prompts. If you typed it 10+ times, it works. Mine your history.

The Goldmine Principle

Your conversation history contains:

• Refined prompts — Every rephrase that worked better was captured
• Working rituals — Prompts repeated 10+ times ARE your methodology
• Scope decisions — "When did we decide NOT to do X?"
• Recovery moments — What you searched for after context loss = what mattered

The insight: Mining your past beats inventing new approaches.

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THE EXACT PROMPT — Discovery Workflow

1. Bootstrap: Check health, refresh index, get project overview
   cass status --json && cass index --json
   cass search "*" --workspace /data/projects/PROJECT --aggregate agent,date --limit 1 --json

2. Find prompts: Search for keywords, filter to user prompts (lines 1-3)
   cass search "KEYWORD" --workspace /data/projects/PROJECT --json --fields minimal --limit 50 \
     | jq '[.hits[] | select(.line_number <= 3)]'

3. Follow hits: View the actual content
   cass view /path/from/source_path.jsonl -n LINE -C 20

4. Expand context: See the full conversation flow
   cass expand /path/from/source_path.jsonl --line LINE --context 3

5. Discover related: Find the whole work cluster
   cass context /path/from/source_path.jsonl --json

Why This Workflow Works

• Aggregations first — Know the terrain before diving in
• --fields minimal — 5x smaller output, preserves context window
• line_number <= 3 — User prompts live at the top of sessions
• Context clustering — Work happens in clusters; one good hit → many related sessions

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Quick Reference

# Health + refresh (ALWAYS first)
cass status --json && cass index --json

# Project overview: who did what, when?
cass search "*" --workspace /path --aggregate agent,date --limit 1 --json

# Find keyword, minimal output
cass search "KEYWORD" --workspace /path --json --fields minimal --limit 50

# Follow a hit
cass view /path.jsonl -n LINE -C 20        # Line-oriented
cass expand /path.jsonl --line LINE --context 3  # Message-oriented

# Find related sessions
cass context /path.jsonl --json

# Export for parsing
cass export /path.jsonl --format json --include-tools -o /tmp/out.json

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When to Use What

You Want	Use	Why
Project overview	--aggregate agent,date --limit 1	Counts only, no content
Find prompts	--fields minimal + jq select(.line_number <= 3)	User prompts are lines 1-3
Ritual detection	Count matches: >10 = ritual	Repeated = working
Full conversation	cass expand --context 3	Message boundaries preserved
Raw JSON parsing	cass export --include-tools -o file.json	Never pipe exports
Content not found	rg "string" /path.jsonl	cass skips tool outputs

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Critical Rules

Rule	Why	Consequence
--limit 1 minimum	--limit 0 panics	Use 1 for aggregations
--fields minimal	Token efficiency	5x smaller output
Export to file	Piping causes broken pipe panic	-o /tmp/out.json always
Exact workspace paths	Case-sensitive matching	Use --aggregate workspace to discover
--include-tools	Tool calls hidden by default	Required for full export

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Search Modes

Mode	When	Example
lexical (default)	Exact strings, filenames	"AGENTS.md", "--workspace"
semantic	Conceptual, unknown wording	"scope reduction discussions"
hybrid	Broad exploration	"architecture decisions"

Default to lexical. Only use semantic when you don't know exact wording.

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The Heuristics

Signal	Meaning	Action
line_number 1-3	User prompts	Filter: select(.line_number <= 3)
/subagents/ line 2	THE extraction prompt	Copy-paste ready
total_matches > 10	Ritual pattern	Document it, reuse it
0 results + content exists	Workspace path mismatch	Use --aggregate workspace

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jq Essentials

# User prompts only
| jq '[.hits[] | select(.line_number <= 3)]'

# Source paths for follow-up
| jq '.hits[].source_path' -r

# Aggregation buckets
| jq '.aggregations.agent.buckets'

# Count matches
| jq '.total_matches'

# Find repeated prompts (ritual detection)
| jq '[.hits[] | select(.line_number <= 3) | .title[0:80]] | group_by(.) | map({prompt: .[0], count: length}) | sort_by(-.count) | .[0:20]'

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References

Need	Reference
Full command reference	COMMANDS.md
Workflow recipes	RECIPES.md
jq patterns	PATTERNS.md
Pitfalls & fixes	PITFALLS.md
Session file formats	SESSION_FORMATS.md

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Scripts

Script	Usage
./scripts/quick_analysis.sh /path	One-command project overview
./scripts/prompt_miner.py --workspace /path	Find repeated prompts
./scripts/validate.sh	Validate cass is working

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Validation

# Quick health check
cass status --json | jq '.index.fresh'

# Should return: true

If false, run: cass index --json