Claude-skill-registry inland-empire

Unified memory substrate. Store facts, patterns, and context. Query with remember, consult, and stats commands.

install

source · Clone the upstream repo

git clone https://github.com/majiayu000/claude-skill-registry

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/inland-empire" ~/.claude/skills/majiayu000-claude-skill-registry-inland-empire && rm -rf "$T"

manifest: skills/data/inland-empire/SKILL.md

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_KEY
```
present
mem0 self-hosted:
```
POSTGRES_URL
```
present
mem0 disabled: neither credential; pattern memory gracefully skipped
```
LIBSQL_URL
```
optional; if missing, a local SQLite file powers fact memory
```
INLAND_EMPIRE_STATE_DIR
```
overrides 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