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quantum_reputation

Query any agent reputation: score 0-100, grade A+ to F, trust level.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agent_didYes
period_daysNo

Schema Changelog

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

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses that the query returns a score, grade, and trust level, but does not mention any behavioral aspects such as authentication requirements, data freshness, or side effects. As a query tool, it is implied non-mutating, but this is not explicit.

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, information-dense sentence. Every word contributes meaning: it states the action, the subject, and the output range. No unnecessary words or repetition.

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?

For a simple query tool with only two parameters and no output schema, the description provides the core return values and overall purpose. However, it does not explain the purpose of period_days or provide any usage scenarios, which would improve completeness. Overall, it is mostly complete for a low-complexity tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description does not mention either parameter (agent_did, period_days) or their meaning. The description adds no value beyond the parameter names, which are not self-explanatory enough to compensate for the lack of documentation.

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?

Description clearly states the verb 'Query' and the resource 'any agent reputation', and adds specific output dimensions (score 0-100, grade A+ to F, trust level). This distinguishes it from sibling tools like quantum_status or quantum_trust_passport by focusing specifically on reputation metrics.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the tool is used for querying reputation, but provides no explicit guidance on when to use it versus alternatives. It does not mention any exclusions or prerequisites, so the usage context is only implied, not directly stated.

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

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