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Cursor10x MCP

Cursor10x MCP

by aiurda
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

storeDecision

Store project decisions with title, content, reasoning, and importance level into long-term memory for AI assistant recall and persistence.

Instructions

Stores a project decision in the long-term memory

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": {
      "title": "<title>",
      "content": "<content>"
    },
    "name": "storeDecision"
  }
}

Input Schema

NameRequiredDescriptionDefault
contentYesContent of the decision
importanceNoImportance level (low, medium, high)medium
metadataNoOptional metadata for the decision
reasoningNoReasoning behind the decision
titleYesTitle of the decision

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool stores data in 'long-term memory', implying persistence, but lacks details on permissions, idempotency, error handling, or what constitutes a 'project decision'. This leaves significant gaps for a mutation tool.

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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, making it easy for an agent to parse quickly.

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 mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what 'long-term memory' entails, how decisions are retrieved or updated, or the implications of storage. Given the complexity and lack of structured data, more context is needed.

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 fully documents all 5 parameters. The description adds no additional meaning beyond implying storage of 'project decision' data, which aligns with parameters like 'title' and 'content'. This meets the baseline for high schema coverage.

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 action ('Stores') and the resource ('a project decision in the long-term memory'), making the purpose evident. However, it doesn't explicitly differentiate from sibling tools like 'storeMilestone' or 'storeRequirement', which appear to be similar storage operations, preventing a perfect score.

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 provides no guidance on when to use this tool versus alternatives. With sibling tools like 'storeMilestone' and 'storeRequirement' that might serve similar purposes, there's no indication of context, prerequisites, or exclusions to help an agent choose appropriately.

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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