lxDIG MCP

episode_recall

Retrieve relevant episodes from agent memory using semantic search, temporal filters, and entity matching to maintain context across sessions.

Instructions

Recall episodes by semantic, temporal, and entity relevance

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": {
      "query": "<query>"
    },
    "name": "episode_recall"
  }
}

Input Schema

Name	Required	Description	Default
`query`	Yes	Recall query
`agentId`	No	Agent filter
`taskId`	No	Task filter
`types`	No	Episode type filters
`entities`	No	Entity filters
`limit`	No	Result limit
`since`	No	ISO timestamp or epoch ms
`profile`	No	Response profile	compact

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.1Jun 21, 2026

TDQS

C2.9/5.0

Behavior2/5

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

With no annotations, the description must fully disclose behavior. It mentions three relevance axes but omits any behavioral traits (e.g., no side effects, performance implications, authorization needs, or limitations like result pagination). The description is insufficient for an agent to understand operational context.

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 a single, concise sentence that quickly communicates the core function. It is front-loaded and avoids redundancy, though it could be slightly expanded to improve completeness without losing conciseness.

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

Completeness2/5

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

The tool has 8 parameters and no output schema, yet the description is too brief to explain what episodes are, how recall works across the three relevance dimensions, what the response contains, or how to effectively use filters (agentId, taskId, types, entities). It lacks sufficient context for a complex retrieval tool.

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

Parameters3/5

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

Schema description coverage is 100%, but parameter descriptions are minimal (e.g., 'Recall query', 'Agent filter'). The main description adds no additional parameter context (e.g., format of 'since', meaning of 'types'). Since coverage is high, baseline 3 is appropriate; the description does not significantly augment the schema.

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

Purpose4/5

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

The description uses a specific verb 'Recall' and identifies the resource 'episodes' and three relevance dimensions (semantic, temporal, entity). This distinguishes it from siblings like semantic_search (which likely targets documents) and graph_query (which targets graph structures), though the term 'episode' is not defined.

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

Usage Guidelines2/5

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

No guidance is provided on when to use episode_recall vs. alternative tools such as semantic_search or graph_query. There is no mention of prerequisites, contraindications, or complementary tools.

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