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Mcp-Omega-Brain

Mcp-Omega-Brain

by VrtxOmega
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Python
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veritas_compute_quality

Evaluates individual evidence quality by computing a VERITAS Quality score from provenance, uncertainty, and method metrics. Returns a 0.0-1.0 quality score for gate submission readiness.

Instructions

Computes the VERITAS Quality(e) score for a single evidence item using: clamp01(0.50provenance + 0.30uncertainty + 0.20*method). Use this to evaluate individual evidence quality before submitting to the evidence gate. Returns JSON with fields: quality (float 0.0-1.0).

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": {
      "evidence_item": "<evidence_item>"
    },
    "name": "veritas_compute_quality"
  }
}

Input Schema

NameRequiredDescriptionDefault
evidence_itemYesEvidence item with provenance (tier, source_id), method (protocol, repeatable), value (x, units, uncertainty), and timestamp.
policy_envNoOptional policy environment for match scoring. Defaults to empty.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added
  2. Removedv2.1.1
  3. Changed2 schema fields changedv1.0.2
    • changedInput schema / properties / evidence_item / description
      Previous value: -"A single VERITAS evidence item containing at minimum: provenance (with tier and source_id), method (with protocol and repeatable flag), value (with x, units, and optional uncertainty), and timestamp."New value: +"Evidence item with provenance (tier, source_id), method (protocol, repeatable), value (x, units, uncertainty), and timestamp."
    • changedInput schema / properties / policy_env / description
      Previous value: -"Optional policy environment specification for environment-match scoring. Defaults to empty object if omitted."New value: +"Optional policy environment for match scoring. Defaults to empty."
  4. Changed2 schema fields changedv1.0.1
    • changedInput schema / properties / evidence_item / description
      Previous value: -"Single evidence item with provenance, method, timestamp, ttl_seconds"New value: +"A single VERITAS evidence item containing at minimum: provenance (with tier and source_id), method (with protocol and repeatable flag), value (with x, units, and optional uncertainty), and timestamp."
    • changedInput schema / properties / policy_env / description
      Previous value: -"Policy environment spec for match scoring"New value: +"Optional policy environment specification for environment-match scoring. Defaults to empty object if omitted."
  5. First observedv1.0.0

TDQS

A4.3/5.0
Behavior3/5

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

No annotations are provided, so the description must cover behavioral traits. It does not state whether the tool has side effects or requires specific permissions, but it clearly indicates it computes and returns a score without mentioning mutations.

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 three concise sentences—each serving a distinct purpose: formula, usage, and output. No redundancy or unnecessary information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description adequately describes the return format. It covers input requirements and usage context, making it complete for a straightforward computational tool.

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

Parameters4/5

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

Schema coverage is 100%, providing a baseline of 3. The description adds value by detailing nested fields expected in evidence_item (provenance, method, value, timestamp) and clarifies the role of policy_env, enriching understanding beyond the schema.

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 computes the VERITAS Quality score for a single evidence item, using a specific formula. It distinguishes from siblings like veritas_evidence_gate by positioning itself as a prerequisite step.

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 explicitly advises using the tool to evaluate individual evidence quality before submitting to the evidence gate, providing clear context and a directive. It does not explicitly state when not to use alternatives, but the usage scenario is well-defined.

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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