sqlite-graphrag 1.1.5

Persistent GraphRAG memory for Claude Code, Codex, Cursor, and 24+ AI agents — one self-contained ~19 MiB Rust binary, zero daemon. Never re-explain your codebase again. Hybrid retrieval (FTS5 BM25 + cosine similarity + multi-hop graph traversal) surfaces the right memory in milliseconds. Embedding and entity enrichment run as parallel REST calls against your cloud LLM — no fragile headless subprocesses, no ONNX runtime, no model downloads. Soft-delete with full version history, transactional atomic writes, BLAKE3-tracked mutations. OAuth-only: raw API keys ABORT the spawn.
Documentation 
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{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "$id": "https://github.com/daniloaguiarbr/sqlite-graphrag/schemas/pending-list.schema.json",
  "title": "pending list",
  "description": "Output of `sqlite-graphrag pending list` for three-stage `remember` checkpoint queue inspection (GAP-001, v1.0.82).",
  "type": "object",
  "additionalProperties": false,
  "required": [
    "action",
    "filter_status",
    "count",
    "entries",
    "elapsed_ms"
  ],
  "properties": {
    "action": { "const": "pending_list" },
    "filter_status": {
      "type": ["string", "null"],
      "description": "Status filter as echoed; null when listing all buckets."
    },
    "count": { "type": "integer", "minimum": 0 },
    "entries": {
      "type": "array",
      "items": {
        "type": "object",
        "additionalProperties": false,
        "required": [
          "pending_id",
          "name",
          "namespace",
          "memory_type",
          "status",
          "attempt_count",
          "last_error",
          "embedding_dim",
          "created_at",
          "updated_at"
        ],
        "properties": {
          "pending_id": { "type": "integer", "minimum": 0 },
          "name": { "type": "string" },
          "namespace": { "type": "string" },
          "memory_type": { "type": "string" },
          "status": {
            "type": "string",
            "enum": [
              "validated",
              "embedding_in_progress",
              "embedding_done",
              "committed",
              "abandoned",
              "failed"
            ]
          },
          "attempt_count": { "type": "integer", "minimum": 0 },
          "last_error": { "type": ["string", "null"] },
          "embedding_dim": { "type": ["integer", "null"] },
          "created_at": { "type": "integer", "minimum": 0 },
          "updated_at": { "type": "integer", "minimum": 0 }
        }
      }
    },
    "elapsed_ms": { "type": "integer", "minimum": 0 }
  }
}