Record a completed deal settlement. Updates trust score and revenue tracking.
| Name | Required | Description | Default |
|---|---|---|---|
| node_id | No | Node that delivered | |
| task_id | No | Task/deal ID | |
| result_hash | No | SHA-256 hash of deliverable | |
| revenue_usdc | No | Revenue in USDC |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that the tool updates trust score and revenue tracking, which is a meaningful behavioral trait. However, it does not mention permissions, reversibility, or idempotency, leaving gaps for a state-changing operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short sentences, front-loaded with the primary action. Every word adds value, and there is no redundant repetition of the tool name or schema information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the purpose and side effects but lacks guidance on prerequisites, return values, or consequences. Given no output schema and no annotations, it is adequate for a simple recording action but not fully complete for an agent to understand all implications.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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, so the description adds no additional parameter-level meaning. It does not relate parameters to the trust score or revenue effects mentioned in the tool description, so it stays at the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'Record a completed deal settlement' with a specific verb and resource, and explicitly mentions the side effects on trust score and revenue tracking. This distinguishes it from sibling tools like quantum_deal or quantum_execute, which handle deal creation and execution respectively.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool should be used when a deal settlement is completed, providing clear contextual guidance. However, it doesn't explicitly name alternatives or exclusions, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.