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Glama

vaara_check

Assess the risk level of an AI agent action before execution. Returns a risk estimate, interval, and allow/deny/escalate decision without recording to the audit trail.

Instructions

Check the risk level of an action BEFORE executing it. Returns a risk assessment with point estimate, conformal interval, and recommended decision (allow/deny/escalate). Does NOT record to the audit trail — use vaara_intercept for that.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agent_idNoIdentifier for the agent requesting the actionmcp-agent
tool_nameYesThe tool/action to check (e.g., 'tx.transfer', 'data.delete')
confidenceNoAgent's self-assessed confidence in the action (0.0-1.0)
parametersNoAction parameters (optional, for context)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.14.0

TDQS

A4.4/5.0
Behavior4/5

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

No annotations exist, so the description carries the full burden, and it does disclose the important non-side-effect: it does not write to the audit trail. It also describes the return payload (point estimate, conformal interval, allow/deny/escalate decision). It does not mention auth requirements, latency, or whether the check itself is logged anywhere, leaving a modest gap.

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 short sentences, front-loaded with the primary purpose, then the return shape, then the sibling disambiguation. No filler or repetition; every sentence earns its place.

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?

There is no output schema, but the description compensates by enumerating the return values. Purpose, return shape, and the critical non-recording behavior are covered for a non-mutating check tool; minor gaps like auth or latency expectations remain.

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 100%, so all four parameters (agent_id, tool_name, confidence, parameters) are already documented in the schema. The description adds no parameter-level meaning beyond what the schema provides, so the baseline of 3 applies.

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?

States a specific verb (Check) and resource (risk level of an action), with a clear scope qualifier ('BEFORE executing it'). It explicitly distinguishes itself from the closest sibling by naming vaara_intercept as the tool that records to the audit trail.

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

Usage Guidelines5/5

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

Gives the when ('BEFORE executing it'), the when-not ('Does NOT record to the audit trail'), and the alternative ('use vaara_intercept for that'). This is an explicit routing rule an agent can act on without inference.

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