Skip to main content
Glama
labyrinth-analytics

LoreConvo

Official

Get Related Sessions

get_related_sessions

Retrieve sessions related to a given session using keyword co-occurrence and semantic embeddings.

Instructions

Find sessions related to a given session by co-occurrence and embedding. Pro only.

Returns co-occurrence links (shared_term_count >= 1) and embedding-based semantic links (shared_term_count=0 sentinel). Co-occurrence results rank above embedding results when sorting by shared_term_count DESC. Response version=2 signals the new format with link_type field.

Args: session_id: UUID of the session to find related sessions for limit: Max results to return (default 10, max 50) min_shared_terms: Minimum shared keywords required (default 3)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
session_idYes
min_shared_termsNo
Behavior5/5

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

With no annotations, the description fully discloses behavior: it explains co-occurrence vs embedding links, the sentinel for shared_term_count=0, ranking order, and response version signaling. This is comprehensive for a read-like tool.

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

Conciseness4/5

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

The description is well-structured with a summary sentence, behavior explanation, and parameter list. Every sentence adds value, though it could be slightly more concise without losing clarity.

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?

Without an output schema, the description explains return format, ranking, and versioning. It lacks mention of error conditions or existence checks, but is otherwise thorough for the tool's complexity.

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?

The 'Args:' section provides detailed descriptions for all three parameters, including defaults and max for limit, even though the schema has no descriptions. This fully compensates for the 0% schema coverage.

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 clearly states the tool finds sessions related to a given session using co-occurrence and embedding. It specifies the resource ('sessions related to a given session') and method, distinguishing it from siblings like 'get_session' or 'get_recent_sessions'.

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

Usage Guidelines3/5

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

The description mentions 'Pro only' as a constraint, but does not provide explicit guidance on when to use this tool versus alternatives like 'link_sessions' or 'search_sessions'. The usage context is implied but not fully clarified.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/labyrinth-analytics/loreconvo'

If you have feedback or need assistance with the MCP directory API, please join our Discord server