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llm_approve_route

Decide whether to proceed with a blocked high-cost AI call by approving, rejecting, or downgrading to a cheaper model.

Instructions

Approve or reject a pending high-cost routing decision.

Use this when llm_route (or any routing tool) blocked a call because the estimated cost exceeded LLM_ROUTER_ESCALATE_ABOVE. The pending call is stored server-side until you approve or cancel it.

Args: approve: True to proceed with the call, False to cancel it. downgrade_to: Optional cheaper model to use instead of the blocked one (e.g. "gemini/gemini-2.5-flash" instead of "openai/o3").

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
approveNo
downgrade_toNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses that the tool approves or cancels a pending call and that the call is stored server-side. However, it does not mention possible side effects like whether approval triggers immediate execution or cancellation removes the pending call, nor does it discuss error states. Still, the core behavior is transparent enough for an agent.

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 very concise: a single-sentence purpose, a short usage context paragraph, and a clear Args section. Every sentence adds value, and the structure front-loads the key action.

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?

For a simple 2-parameter tool with an output schema (not shown but present), the description covers purpose, usage, and parameters adequately. It lacks mention of error handling or timeout behavior for the pending call, but these are minor given the tool's simplicity.

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?

Schema coverage is 0%, so the description must explain parameters. It does so clearly: approve (boolean to proceed or cancel) and downgrade_to (optional string with an example like 'gemini/gemini-2.5-flash' for a cheaper model). This adds meaning well beyond the bare schema types.

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: 'Approve or reject a pending high-cost routing decision.' It specifies the verb (approve/reject) and resource (pending high-cost routing decision), and among siblings like llm_route and llm_reroute, this tool uniquely handles the approval step after a cost-based block.

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?

Explicitly states when to use: when llm_route (or any routing tool) blocked a call due to cost exceeding LLM_ROUTER_ESCALATE_ABOVE. It also explains the pending call is stored server-side, implying that you need to use this tool before the call is dropped. This leaves no ambiguity about the context.

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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