Skip to main content
Glama

quantum_execute

Execute a tool on an OracleNet oracle. The muscle of the mesh. Routes to the right oracle, calls it, delivers the result, logs the neural synapse, and updates routing weights. Use quantum_intent first to find the right tool, then quantum_execute to run it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toolYesTool name to execute (e.g. compliance_preflight, fed_rate)
oracleNoOracle name/key hint (optional, auto-detected from tool)
argumentsYesArguments to pass to the tool
caller_didNoYour DID for tracking (optional)

Schema Changelog

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

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses side effects: 'logs the neural synapse, and updates routing weights,' which is useful. But it does not explain potential risks, synchronous behavior, or error handling. The description adds some context but lacks depth about consequences of execution.

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 concise (four sentences) and front-loads the core purpose. The metaphor 'The muscle of the mesh' adds flavor but is non-essential. Overall, it's efficient with minimal fluff, earning a 4.

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?

For a complex executor tool with no output schema, the description provides workflow guidance and side effects but does not specify return format, error behavior, or prerequisites. The schema covers parameters, but the lack of output details leaves a gap. It's adequate but not complete.

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 has 100% description coverage for all four parameters, including examples for 'tool' and explanations for 'oracle' and 'caller_did'. The description adds no parameter-specific details, but the schema already handles this dimension, so a baseline of 3 is appropriate.

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: 'Execute a tool on an OracleNet oracle.' It further details the process ('Routes to the right oracle, calls it, delivers the result') and explicitly distinguishes from the sibling tool quantum_intent by positioning it as the follow-up step. The verb+resource structure is specific and unambiguous.

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 gives explicit workflow guidance: 'Use quantum_intent first to find the right tool, then quantum_execute to run it.' This clearly indicates when to use this tool relative to a sibling. However, it does not mention exclusions or alternatives beyond quantum_intent, so it's not a full 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

C2.9/5.0
Disambiguation2/5

Several tools have unclear boundaries: quantum_ask and quantum_intent both serve as natural language 'front doors' with similar descriptions, and quantum_route and quantum_refer both find the best oracle for a task. This creates significant overlap that could cause agents to select the wrong tool.

Naming Consistency4/5

Most tools follow a consistent quantum_<verb_or_noun> snake_case pattern (e.g., quantum_join, quantum_execute, quantum_settle). The single exception is neural_status, which breaks the prefix convention, but overall the naming is predictable and readable.

Tool Count3/5

With 20 tools, the server sits in the heavy range (16-25). While the broad scope of OracleNet (intelligence, natural language, deals, reputation, subscriptions, scanning) somewhat justifies the count, it feels overpacked and could be streamlined by merging overlapping tools.

Completeness3/5

The tool surface covers core workflows: joining, querying status/nodes/reputation, routing, executing, dealing, settling, rating, and subscribing. However, lifecycle gaps exist—no unsubscribe, leave/delete node, deal cancellation, or dispute resolution—which can leave agents with dead ends.

Resources