LoreConvo

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Import Sessions

import_sessions

Import sessions from a LoreConvo export file (JSON/JSONL). Preserves session UUIDs. Choose to skip or replace existing sessions, or validate with a dry run before making changes.

Instructions

Import sessions from a LoreConvo export file (JSON or JSONL).

Reads an export created by export_sessions and saves sessions into the local database. Session UUIDs are preserved so re-importing is safe.

Args: file_path: Path to the export file (JSON or JSONL format). on_conflict: What to do if a session ID already exists. 'skip' (default) -- leave the existing session unchanged. 'replace' -- overwrite with the imported version. dry_run: If True, parse and validate the file but make no DB changes.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "file_path": "<file_path>"
    },
    "name": "import_sessions"
  }
}

Input Schema

Name	Required	Default
`dry_run`	No
`file_path`	Yes
`on_conflict`	No	skip

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.8.3Jul 17, 2026

TDQS

A4.5/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It discloses that sessions are saved to the database, UUIDs are preserved, and dry_run prevents DB changes. It also explains the on_conflict behavior (skip/replace). This provides good transparency, though it lacks details on permissions or error handling.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured: a concise one-sentence summary followed by a brief paragraph and a clear bulleted Args list. Every sentence adds value with no fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 3 parameters and no output schema, the description covers the core functionality and parameters well. However, it does not describe the return value (e.g., success/error response), which would be useful for an import tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description compensates fully. The Args section explains each parameter: file_path (path to file), on_conflict (options with default 'skip'), and dry_run (boolean). This adds significant meaning beyond the bare schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states 'Import sessions from a LoreConvo export file (JSON or JSONL)'. It specifies the action (import), the resource (sessions from export), and the allowed formats, clearly distinguishing it from siblings like export_sessions.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description notes that it reads exports created by export_sessions and saves to the local database, implying it is used after export. It also mentions that re-importing is safe due to UUID preservation. However, it does not explicitly state when not to use it or provide alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.