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x711_vault_query

Read-onlyIdempotent

Semantic vector search across your private vault. Returns ranked memories by cosine similarity × confidence × importance. Recalls the most relevant facts, insights, and skills your agent has accumulated. FREE always. Requires API key (reads your vault only — other agents cannot access it).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesSearch query. Natural language. Example: 'USDC contract address Base chain' or 'strategies that worked for DeFi yield'.
limitNoMax results to return. Default: 10.

TDQS

A4.2/5.0
Behavior4/5

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

Beyond annotations (readOnly, idempotent), the description adds valuable behavioral details: ranking is based on cosine similarity × confidence × importance, it is free, requires an API key, and only reads the agent's own vault. These are useful operational signals not present in annotations, though it does not detail response format or pagination.

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 compact and front-loaded with the primary purpose, followed by the ranking mechanism and access details. Every sentence adds functional value (ranking, cost, privacy) without redundancy or fluff, making it easy to scan.

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?

Given there is no output schema, the description partially fills the gap by stating that it returns 'ranked memories' with a specific ranking score, and describes the type of content (facts, insights, skills). It does not specify the exact structure of each result, but for a simple search tool this is adequate.

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?

The input schema already covers 100% of parameters with detailed descriptions (including examples for 'q' and constraints for 'limit'). The tool description provides general context about semantic search but does not add further meaning to individual parameters, so it meets the baseline without exceeding it.

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 a specific action ('Semantic vector search') on a specific resource ('your private vault') and even details the ranking mechanism. It distinguishes this from sibling tools by emphasizing the private vault scope and unique scoring formula, setting it apart from general retrieval or web search tools.

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 makes the intended use context obvious ('recalls facts, insights, and skills your agent has accumulated'), so an agent knows when to invoke it. However, it does not explicitly state when not to use it or name alternative tools (e.g., x711_deep_search), so it lacks exclusions or explicit alternatives.

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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TDQS

A3.9/5.0
Disambiguation3/5

Many tools have overlapping purposes, such as multiple search tools (web_search, deep_search, data_retrieval) and multiple communication tools (agent_ping, agent_telegram, swarm_broadcast). The descriptions help differentiate, but the boundaries are not always clear.

Naming Consistency4/5

All tools consistently use the 'x711_' prefix and lowercase_with_underscores format. Submodules like agent, hive, and tx follow predictable patterns. Minor deviations (e.g., x711_ask_clerk) are rare and still descriptive.

Tool Count2/5

With 47 tools, the server is excessively large for a typical MCP service. While it aims to be a comprehensive platform, the high count makes navigation and selection cumbersome for an agent.

Completeness4/5

The tool set covers a wide range of agent needs: web access, memory, communication, on-chain transactions, code execution, and more. Minor gaps exist (e.g., no agent deletion tool), but overall it is remarkably complete for the stated purpose of an agent platform.

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