inland-empire
Unified memory substrate. Store facts, patterns, and context. Query with remember, consult, and stats commands.
When & Why to Use This Skill
Inland Empire is a sophisticated unified memory substrate that enables Claude to maintain long-term persistence and 'institutional memory.' By integrating graph-based fact storage, pattern recognition, and session context, it solves the problem of context loss across sessions, allowing agents to recall complex project details, user preferences, and recurring patterns that logic alone might miss.
Use Cases
- Project Continuity: Recalling specific architectural decisions, race conditions, or project-specific nuances when returning to a codebase after a long break.
- User Personalization: Storing and retrieving soft context such as user-specific coding styles, preferred error verbosity, and workflow habits.
- Pattern Recognition: Identifying and documenting recurring issues or 'gut feelings' across multiple interactions to improve future problem-solving efficiency.
- Knowledge Graph Building: Automatically constructing a queryable network of facts and entities using the LibSQL graph backend to enhance research capabilities.
| name | inland-empire |
|---|---|
| description | Unified memory substrate. Store facts, patterns, and context. Query with remember, consult, and stats commands. |
| license | MIT |
| version | 1 |
| required | [] |
| - event_type | memory.evicted |
| priority | high |
| max_absorb_per_minute | 100 |
| max_emit_per_minute | 50 |
Inland Empire
"This is your gut feeling. The raw data of the soul. When logic fails, consult the Empire."
Capabilities
The Inland Empire unifies three memory backends but only exposes sanitized aliases
(fact_memory, pattern_memory, context_memory). Internals (MCP, mem0, JSONL) are hidden.
| Alias | Memory Type | Backend | Storage | Notes |
|---|---|---|---|---|
fact_memory |
fact |
mcp-memory-libsql | Graph entities/relations | Defaults to local SQLite fallback |
pattern_memory |
pattern |
mem0 | Hosted API (MEM0_API_KEY) or self-hosted Postgres (POSTGRES_URL) | |
context_memory |
context |
JSONL | Local file (session_memory.jsonl) | Always available |
Backend detection
- mem0 hosted:
MEM0_API_KEYpresent - mem0 self-hosted:
POSTGRES_URLpresent - mem0 disabled: neither credential; pattern memory gracefully skipped
LIBSQL_URLoptional; if missing, a local SQLite file powers fact memoryINLAND_EMPIRE_STATE_DIRoverrides the storage directory (tests, sandboxes, multi-project)
Commands
remember
Store a memory across configured backends.
python3 inland-empire.py remember "<text>" [--type fact|pattern|context]
Examples:
python3 inland-empire.py remember "User prefers verbose error messages"
python3 inland-empire.py remember "The auth flow has race conditions" --type pattern
consult
Query stored memories with optional depth and type filters. Results contain backend aliases, partial-result indicators, and normalized metadata.
python3 inland-empire.py consult "<query>" [--depth shallow|deep] [--type fact|pattern|context]
Example:
python3 inland-empire.py consult "user preferences" --depth deep --type pattern
Response shape
{
"status": "ok",
"command": "consult",
"result": {
"query": "user preferences",
"depth": "deep",
"results": [
{
"origin": "pattern",
"summary": "User prefers verbose error messages",
"score": 0.812,
"observed_at": null,
"backend": "pattern_memory",
"partial": false,
"metadata": {
"id": "mem0_123",
"user_id": "agent_subconscious",
"created_at": "2024-01-15T10:30:00Z",
"updated_at": "2024-01-15T10:30:00Z",
"mode": "hosted"
}
}
],
"metadata": {
"requested_backends": ["fact_memory", "pattern_memory"],
"completed_backends": ["pattern_memory"],
"timed_out_backends": ["fact_memory"],
"partial": true
}
}
}
stats
Display backend health, detection mode, and basic counts (context entries).
python3 inland-empire.py stats
When to Use
- Store hunches, preferences, and soft context that doesn't belong in files
- Recall project context after breaks
- Detect patterns across sessions
- Build institutional memory for recurring issues