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Omniaeye
by Omniaeye

omnia_get_decision

Read-only

Retrieve a previously saved decision by its unique ID, avoiding recomputation. Access stored classifications, scores, or probabilities directly.

Instructions

Read a persisted local decision by its opaque ID, without re-evaluating it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
decision_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelYes
usageNo
cachedNo
policyYes
statusYes
answersYes
evidenceYes
identityYes
providerYes
created_atYes
input_hashYes
decision_idYes
duration_msYes
review_reasonsYes
schema_versionNoomnia.mcp.decision.v1

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the read-only nature is covered. The description adds that it operates on a 'persisted local decision' and explicitly says 'without re-evaluating it', which discloses that it does not trigger recomputation. This adds context beyond the annotation, though it could mention behavior like error handling for nonexistent IDs.

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, front-loaded sentence with no filler. It states the action, resource, and a key distinguishing characteristic, earning its place with zero waste.

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?

With an output schema present, return values are already documented. The tool is simple (one parameter, read-only), and the description covers its purpose, the nature of the ID, and the key distinction from siblings. Nothing an agent needs to call it correctly is missing.

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 0%, so the description must compensate. The description labels decision_id as an 'opaque ID', clarifying that it is a meaningless token rather than a human-readable key. This adds semantic meaning beyond the schema's type and pattern constraints, making the parameter's role clear.

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 uses a specific verb 'Read' and identifies the resource as 'a persisted local decision', clearly distinguishing it from evaluation tools. The phrase 'without re-evaluating it' further separates it from siblings like omnia_evaluate, making the purpose 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 implies when to use this tool (retrieve a stored decision without recomputation) but does not explicitly name alternatives or exclusion conditions. The phrase 'without re-evaluating it' hints at the contrast with evaluation tools, but it would be stronger to explicitly state 'use this when you have a decision ID and need the stored result, not a fresh evaluation.'

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