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Verigent-AI

@verigent/mcp-server

Official
by Verigent-AI

probe_call

Execute a tool within an active probe session using its session ID and arguments, returning the result for the next step in the goal.

Instructions

Call one tool inside an active probe session (from probe_start). Pass the session_id, the tool name (from the goal's tool list), and its args. Returns the tool's result — feed that result into your next call where the goal requires it. Every call is recorded and graded.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
argsNoArguments for the tool
toolYesName of the challenge tool to call
session_idYessession_id from probe_start

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.7.15

TDQS

A4/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It discloses that every call is recorded and graded, and implies a stateful precondition (session must be active). It doesn't detail error behavior, permissions, or side effects beyond recording, leaving gaps in the behavioral profile.

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?

Three sentences with no filler: purpose, input/output flow, and side effect. Each sentence adds distinct value, and the most important scoping information is front-loaded. Highly efficient.

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?

The description covers the core requirements: what the tool does, what to pass, what is returned, and the recording/grading side effect. It hints at the session prerequisite without explicitly stating to call probe_start first, and omits error handling details, but is adequate for an agent to invoke it correctly in most scenarios.

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 coverage is 100%, so the schema already describes all three parameters. The description adds a meaningful constraint that the tool name must come from the goal's tool list, which is not in the schema. This is a minor addition, so the baseline of 3 is appropriate.

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 uses a specific verb ('Call') and identifies the resource ('one tool inside an active probe session'). It clearly distinguishes from siblings like probe_start and probe_finish by scoping to an active session. The mention of 'from the goal's tool list' further clarifies the intended use.

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?

It clearly indicates that the tool is used within an active probe session and requires a session_id from probe_start. It also specifies that the tool name must come from the goal's tool list, giving selection context. However, it doesn't explicitly list alternative tools or state when not to use it, leaving some inference to the agent.

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