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set_spend_limit

Control AI coding costs by setting hard spending limits for team members to prevent budget overruns and manage usage effectively.

Instructions

Set a hard spending limit (in dollars) for a specific team member. Use with caution — this will block the user from making requests once the limit is reached.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailYesUser email to set the limit for
limitDollarsYesHard spending limit in dollars (0 to remove limit)
Behavior3/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It effectively describes the tool's impact ('block the user from making requests once the limit is reached') and includes a cautionary note. However, it lacks details on permissions required, whether the change is reversible, or any rate limits, which are important for a mutation tool with no annotation coverage.

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 two sentences, front-loaded with the core purpose and followed by a cautionary note. Every sentence earns its place by adding critical information, with no wasted words or redundancy.

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?

Given that this is a mutation tool with no annotations and no output schema, the description is moderately complete. It covers the purpose, impact, and caution, but lacks details on permissions, reversibility, or response format. For a tool that modifies user access, more behavioral context would be beneficial to ensure safe usage.

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?

The schema description coverage is 100%, so the schema already documents both parameters ('email' and 'limitDollars') adequately. The description adds minimal value beyond the schema by mentioning 'in dollars' and implying the limit is for a team member, but it does not provide additional syntax, format details, or constraints beyond what the schema specifies.

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 specific action ('Set a hard spending limit'), the resource ('for a specific team member'), and the unit ('in dollars'). It distinguishes this tool from its sibling tools, which are primarily read-only 'get' operations, by being the only tool that modifies spending limits.

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?

The description provides clear context for when to use this tool ('to block the user from making requests once the limit is reached') and includes a cautionary note ('Use with caution'). However, it does not explicitly mention when not to use it or name specific alternatives among the sibling tools, such as using 'get_spending' to check current spending before setting a limit.

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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