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Glama

Recall from memory

recall
Read-onlyIdempotent

Retrieve relevant memories from persistent memory for the current situation, ranked by relevance, importance, and recency, to inform returning-user conversations.

Instructions

Retrieve what was previously remembered that relates to the current situation. Ranked by relevance, weighted by importance and decayed by age, so a recent statement outranks an old one saying the opposite. Worth calling at the start of a conversation with a returning user. This searches memory, not documents — use ask_documents for anything the organisation wrote down.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYesWhat you are trying to recall, in natural language.
agentIdNo
subjectNoNarrow to one subject, e.g. 'user:ankit'.
sessionIdNoNarrow to one conversation.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.2.2
    • removedInput schema / additionalProperties
      Removed value: -false
  2. First observedv0.1.1

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so safety is covered. The description adds genuinely new behavioral context: results are ranked by relevance, weighted by importance, and decayed by age, so recency can override an older contradictory statement — this shapes how an agent should interpret and trust the results.

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?

Three sentences, zero filler, with the core ranking behavior and the routing exclusion both front-loaded. Every sentence carries distinct information.

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?

For a read tool with no output schema, the description covers purpose, timing, ranking semantics and sibling routing. It stops short of describing the shape or fields of a recalled memory item, and leaves limit/agentId unexplained, but overall it is sufficient to invoke correctly.

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 coverage is 60%; query, subject and sessionId are documented in the schema but limit and agentId are bare, and the description adds no parameter-level detail such as how narrowing by subject/session interacts with ranking. With moderate coverage, the schema does most of the work and the description neither helps nor hurts.

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?

States a specific verb ('retrieve') and resource ('what was previously remembered'), plus the retrieval model (relevance/importance/age ranking). It cleanly separates itself from ask_documents, which targets organisational documents rather than memory.

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

Usage Guidelines5/5

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

Gives both a positive trigger ('start of a conversation with a returning user') and an explicit alternative with its domain ('use ask_documents for anything the organisation wrote down'). An agent can decide without opening any schema.

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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