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Remembra

Remembra

by Hilbras
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

Digest a session

memory_digest

Extract facts, decisions, roles, and history from a conversation transcript and store them automatically, skipping duplicates. Call at session end to save key information beyond the context window.

Instructions

Extract facts, decisions, roles and history from a conversation transcript and store them automatically (exact and near-identical duplicates are skipped; changed quantities go to the LLM merge). Call at the end of a session with the transcript or a detailed summary of it. Requires REMEMBRA_LLM + an API key.

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": {
      "transcript": "<transcript>"
    },
    "name": "memory_digest"
  }
}

Input Schema

NameRequiredDescriptionDefault
scopeNoScope for extracted memories (default: global)
sourceNoOriginating session/client
transcriptYesConversation transcript or a detailed summary of the session

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv4.8.0
    • addedInput schema / properties / transcript / minLength
      Added value: +1
  2. First observedv0.4.0

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations, the description carries the behavioral disclosure burden. It does disclose deduplication behavior and the REMEMBRA_LLM/API key prerequisite, but the phrase 'changed quantities go to the LLM merge' is vague and unexplained, and side effects or failure behavior are not covered.

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 two sentences, front-loaded with the main action, and includes dedup behavior, timing, and a prerequisite without filler. Every sentence earns its place.

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

Completeness3/5

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

The core operational context is present: what to do, when to call, and what input to provide. However, with no output schema, the description does not explain what the tool returns or how the LLM merge behaves, leaving some ambiguity for an agent.

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%, so the baseline is 3. The description adds little beyond the schema, only reinforcing that transcript can be a detailed summary. No extra semantics are provided for scope or source.

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 clearly states the tool extracts facts, decisions, roles, and history from a transcript and stores them, which is a specific verb+resource. It does not explicitly name sibling tools to differentiate, but the session-digest framing distinguishes it from memory_store and memory_batch.

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 gives clear timing guidance: 'Call at the end of a session' with a transcript or detailed summary. It does not mention when not to use the tool or alternatives, so it stops short of full routing guidance.

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

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