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ContextPulse

ContextPulse

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by ContextPulse
OverviewSchemaRelated ServersScoreDiscussions
Python
Local

memory_recall

Retrieve a stored value from your local memory database by providing the exact key. Returns the saved content as a string or indicates if the key is not found.

Instructions

Recall the value stored at an exact key from the local memory database.

Returns the stored value as a string, or a "not found" indicator if the key doesn't exist.

USE WHEN: you stored something via memory_store and need to retrieve it by its exact key. NOT FOR: fuzzy or substring lookup — use memory_search. For semantic similarity, use memory_semantic_search.

BEHAVIOR: pure read. Sub-millisecond. Does NOT update any access timestamp — repeated recall is invisible.

PARAMETERS: key: exact key as passed to memory_store. Case-sensitive. Required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed2 schema fields changedv0.1.2
    • addedInput schema / properties / key
      Added value: +{
+  "title": "Key",
+  "type": "string"
+}
    • addedInput schema / required
      Added value: +[
+  "key"
+]
  2. First observedv0.1.0

TDQS

A5/5.0
Behavior5/5

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

Discloses 'pure read' and 'sub-millisecond' performance, notes no timestamp update, and explains the return value behavior (string or 'not found' indicator). No annotations exist, so description fully covers behavioral traits.

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?

Structured into clear sections (main, USE WHEN, NOT FOR, BEHAVIOR, PARAMETERS) with no extraneous text. Every sentence serves a distinct purpose, front-loaded with core action.

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

Completeness5/5

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

For a simple key-based recall tool, the description covers purpose, usage, behavior, parameters, and return behavior. With no output schema details needed, it is fully self-contained given the tool's simplicity.

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?

Despite 0% schema coverage, description includes a dedicated PARAMETERS section explaining 'key' as exact, case-sensitive, required—adding semantics beyond the schema's type/required fields.

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 'Recall the value stored at an exact key'—a specific verb+resource. It distinguishes from siblings by mentioning memory_search and memory_semantic_search for non-exact lookups.

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?

Provides explicit 'USE WHEN' (after memory_store) and 'NOT FOR' (fuzzy/substring/semantic lookup) with direct sibling names, giving clear when-to-use and when-not-to-use 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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