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Glama

set_safety_config

Set loop prevention and safety limits for agent execution, including maximum iterations, confidence threshold, approval checkpoints, and timeout duration.

Instructions

Configure loop prevention and safety settings.

Args: max_iterations: Maximum iterations before stopping confidence_threshold: Stop when confidence exceeds threshold require_approval_after: Require approval after N iterations timeout_seconds: Global timeout in seconds

Returns: Updated safety configuration

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
max_iterationsNo
timeout_secondsNo
confidence_thresholdNo
require_approval_afterNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior2/5

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

There are no annotations, so the description must fully disclose behavioral traits. It only says 'configure' without explaining the scope (global vs per-agent), persistence, immediate effect on running executions, or any permissions required. It also does not mention that the configuration likely affects execute_agent and execute_pipeline. This lack of behavioral detail is a significant gap for a mutation tool.

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 concise, front-loads the purpose, and uses a clean list for parameters. It includes a Returns section for clarity. Every sentence contributes value without redundancy.

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?

The description explains parameters and returns but lacks broader context: it does not clarify whether the configuration applies globally or per agent, whether it persists across sessions, or how it interacts with execute_agent and execute_pipeline. Without this, an agent may not understand the full impact of calling the tool. The absence of an output schema and annotations increases the need for contextual detail, which is not provided.

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

Parameters5/5

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

The description adds clear meaning to every parameter: max_iterations 'Maximum iterations before stopping', confidence_threshold 'Stop when confidence exceeds threshold', require_approval_after 'Require approval after N iterations', and timeout_seconds 'Global timeout in seconds'. With schema coverage at 0%, this is essential and well-executed.

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's purpose: 'Configure loop prevention and safety settings.' This is a specific verb+resource combination that distinguishes it from siblings like get_safety_config, which retrieves rather than modifies. The phrasing is not tautological and leaves no ambiguity about the tool's function.

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

Usage Guidelines3/5

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

The description implies usage—it is the setter counterpart to get_safety_config—but does not explicitly state when to use this tool versus alternatives. It does not mention 'use this to modify safety parameters' or contrast with get_safety_config. An agent could infer the appropriate time, but explicit guidance is missing.

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