Skip to main content
Glama

jev_system_one

Evaluate agent state with typed questions to return calibrated scores or true/false judgments, enabling safe decision-making in workflows.

Instructions

Call TypeSafe Jev with named questions. Each question uses type, instructions, criteria ONLY, never question or rubric. Score requires 2..64 ordered criteria from lowest to highest score. Noul uses true/false criteria descriptions. Example questions: {"completed":{"type":"noul","criteria":{"true":"The requested completion is visible","false":"Completion is absent"}}, "risk":{"type":"score","criteria":["No sensitive action","Reversible action","Sensitive or irreversible action"]}}. Report any error as an incomplete evaluation, never as overall success.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNojev-latest
stateYes
questionsYes
timeout_sNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

B3.1/5.0
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 does disclose an error-handling convention ('Report any error as an incomplete evaluation, never as overall success') and imposes input constraints, but it does not state side effects, permissions, or whether the operation is read-only. This is partial, not complete, behavioral transparency.

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 dense but not bloated; it front-loads the core action, then gives pragmatic constraints and a compact example. Each sentence adds necessary information, and the example JSON is directly useful without being excessive.

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

Completeness2/5

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

With no annotations and a schema that has no property descriptions, the description is the only source of semantics. It covers the nested 'questions' format and error conventions well, but it never defines the required 'state' parameter, nor does it explain 'model' or 'timeout_s'. An agent would likely struggle to construct a fully correct call.

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?

Schema description coverage is 0%, so the description must compensate. It explains the 'questions' parameter well: structure, supported types, criteria-count limits, and a concrete example. However, it leaves 'state', 'model', and 'timeout_s' semantically unexplained, which is a significant gap for a required parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific action ('Call TypeSafe Jev') and names the required payload shape (named questions with type/instructions/criteria). It is clear about what the tool does, though it does not explicitly contrast it with sibling tools such as jev_choose or jev_step.

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

Usage Guidelines2/5

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

There is no guidance about when to use jev_system_one versus the sibling tools. The description focuses on how to format questions ('Score requires 2..64 ordered criteria', 'Noul uses true/false criteria descriptions') but does not state when to prefer this tool over alternatives, or when not to use it.

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