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manageVector

Manage vector embeddings for Cursor10x MCP by performing store, search, update, and delete operations to enhance AI memory retention and recall.

Instructions

Unified tool for managing vector embeddings with operations for store, search, update, and delete

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentIdNoID of the content this vector represents (for store, update, delete)
contentTypeNoType of content (message, file, snippet, etc.)
limitNoMaximum number of results for search operation
metadataNoAdditional info about the vector (optional)
operationYesOperation to perform (store, search, update, delete)
thresholdNoSimilarity threshold for search operation
vectorNoVector data as array of numbers (for store, update) or query vector (for search)
vectorIdNoID of the vector to update or delete
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. While it lists operations, it doesn't describe what 'manage' entails - whether operations are atomic, have side effects, require specific permissions, have rate limits, or what happens on failure. For a multi-operation tool with 8 parameters and no annotation coverage, this is a significant gap.

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, efficient sentence that communicates the core purpose. It's appropriately sized for a multi-operation tool, though it could be slightly more structured by separating operation types or adding brief context.

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?

For a complex tool with 8 parameters, multiple operations, no annotations, and no output schema, the description is inadequate. It doesn't explain return values, error conditions, operation interdependencies, or how this fits within the broader vector management system alongside tools like 'diagnoseVectors'.

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 schema already documents all parameters thoroughly. The description doesn't add any meaningful parameter semantics beyond what's in the schema - it mentions operations but doesn't clarify parameter dependencies or operation-specific requirements. Baseline 3 is appropriate when the schema does the heavy lifting.

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 this is a 'unified tool for managing vector embeddings' with specific operations listed (store, search, update, delete), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'diagnoseVectors' or explain how this differs from other vector-related operations that might exist in the context.

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?

The description mentions the four operations but provides no guidance on when to use this tool versus alternatives like 'diagnoseVectors' or other sibling tools. There's no indication of prerequisites, constraints, or typical use cases for each operation type.

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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