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set_ai_booking_rule_auto_booking

Separate FINANCIALLY SIGNIFICANT auto-booking control. Never invoke without the user's matching approval. Default preview; enabling requires explicit_enable and does not authorize a test booking.

Input Schema

NameRequiredDescriptionDefault
kindYes
dry_runNo
enabledYes
rule_idYes
company_nameNo
operation_keyNo
explicit_enableNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

With no annotations, the description carries the burden well: it flags financial significance, requires matching user approval, states that preview is the default, and clarifies that enabling requires explicit_enable and does not authorize a test booking. It does not describe side effects or reversibility, but it discloses the key safety behaviors.

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, each doing meaningful work. The financial-significance warning is front-loaded, followed by approval and preview/enable constraints. No filler.

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

Completeness3/5

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

For a 7-parameter, financially significant mutation with no annotations, the description covers the safety flow but omits most parameter semantics and does not say what enabling actually changes. Output schema exists, so return values need not be described. Adequate but incomplete.

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

Parameters2/5

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

Schema description coverage is 0% across seven parameters. The description only clarifies dry_run (default preview) and explicit_enable, leaving required parameters like kind, rule_id, enabled, and optional company_name/operation_key unexplained. It adds some meaning but does not compensate for the coverage gap.

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 identifies a specific resource and scope: a 'Separate FINANCIALLY SIGNIFICANT auto-booking control' tied to the tool name set_ai_booking_rule_auto_booking. It is clear enough what domain this touches, though it does not explicitly name the sibling it differs from (e.g., update_ai_booking_rule or explicit_enable_bank_rule_auto_booking).

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 gives a strong when-not-to-use guardrail: 'Never invoke without the user's matching approval.' It also explains that the default is preview and enabling requires explicit_enable. It stops short of naming alternative tools, but the approval and preview flow is clear usage guidance.

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

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