VaultCrux Memory Core

Query Memory

query_memory

Search the user's conversation memory. Returns ranked results with content, source timestamps, and confidence scores. For KNOWLEDGE UPDATE questions ('current', 'now', 'most recent'): make two calls — one with scoring_profile='balanced' and one with scoring_profile='recency' — then use the value from the most recent source_timestamp. For COUNTING questions ('how many', 'total'): results may not be exhaustive — search with varied terms and enumerate explicitly before counting. If all results score below 0.3, reformulate with synonyms or specific entity names from the question.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No
`query`	Yes
`topic`	No
`format`	No
`date_to`	No
`agent_id`	No
`date_from`	No
`date_range`	No
`question_date`	No
`scoring_profile`	No
`confidence_threshold`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`results`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedJun 2, 2026

addedInput schema / properties / format

Added value: +{
+  "enum": [
+    "raw",
+    "narrative"
+  ],
+  "type": "string"
+}

Changed2 schema fields changedApr 23, 2026

addedInput schema / properties / question_date

Added value: +{
+  "minLength": 1,
+  "type": "string"
+}

changedInput schema / properties / scoring_profile / enum

Previous value: -[
-  "balanced",
-  "recall",
-  "recency"
-]New value: +[
+  "balanced",
+  "recall",
+  "recency",
+  "temporal",
+  "assistant_ref",
+  "vocabulary_gap",
+  "supersession",
+  "aggregation"
+]

Changed1 schema field changedMar 31, 2026

changedOutput schema / properties / results / items / properties / sourcePlatform / enum

Previous value: -[
-  "openai",
-  "claude",
-  "gmail",
-  "slack",
-  "browser",
-  "manual"
-]New value: +[
+  "openai",
+  "claude",
+  "gmail",
+  "slack",
+  "browser",
+  "manual",
+  "ob1"
+]

Changed1 schema field changedMar 29, 2026

addedInput schema / properties / scoring_profile

Added value: +{
+  "enum": [
+    "balanced",
+    "recall",
+    "recency"
+  ],
+  "type": "string"
+}

Changed1 schema field changedMar 28, 2026
- changedInput schema / properties / limit / maximum
```
Previous value: -20New value: +50
```
First observedMar 20, 2026

TDQS

A3.9/5.0

Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses key behavioral traits: results are ranked, may not be exhaustive for counting, and repeated calls or reformulation may be needed for low-confidence results. It does not explicitly state read-only nature, but 'search' implies no mutation, and the disclosed traits are valuable.

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 front-loaded with the core purpose, followed by targeted usage advice. Each sentence adds value, and the structure is logical. Slightly on the longer side but appropriate for the level of detail given.

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 tool is complex (11 params, nested objects, enums) and the description covers specific scenarios well but omits general parameter semantics and filtering behavior. With an output schema present, return values are covered, but the overall description is not fully complete for all potential uses.

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

Parameters2/5

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

The schema has 11 parameters at 0% description coverage, so the description must compensate. It adds meaning for scoring_profile (balanced vs recency) and confidence_threshold (via the 0.3 cutoff), but leaves limit, topic, format, date filters, question_date, and agent_id completely unexplained. This is insufficient for the parameter complexity.

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's function: 'Search the user's conversation memory' and specifies the output format ('ranked results with content, source timestamps, and confidence scores'). This is a specific verb+resource combination that distinguishes it from sibling memory tools like enumerate_memory_facts or get_relevant_context.

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 provides explicit usage strategies for two question types (knowledge update and counting) and a low-confidence reformulation rule. These are clear contextual guidelines, though it does not mention alternatives or explicitly state when not to use this tool.

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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