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agent_bootstrap

Generate a bootstrap token from an email to enable zero-human onboarding without outbound mail, then use it to authorize machine-pay billing requests.

Instructions

Start zero-human onboarding: create bootstrap token from email (no outbound mail). Next POST /api/billing/machine-pay with Bearer bootstrapToken.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailYes
labelNo
Behavior3/5

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

With no annotations present, the description carries the burden of behavioral disclosure. It usefully states 'no outbound mail' and implies the response contains a bootstrapToken. However, it does not disclose token lifetime, idempotency, authorization requirements, or error behavior.

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?

Two sentences with no filler. The core action is front-loaded, and the second sentence adds valuable follow-up guidance without bloating the description.

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 simple 2-parameter tool, the description provides a usable workflow: create token from email, then use it with billing_machine_pay. But it omits label semantics, response format details, and any failure/edge-case context, so it is adequate but not complete.

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%, so the description must compensate. It makes it clear that email is the input from which the token is created, but it says nothing about the optional label parameter, leaving its purpose entirely unexplained.

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 action: 'create bootstrap token from email'. It also distinguishes this tool from siblings by noting it has 'no outbound mail' and by naming the next step, billing_machine_pay, making the tool's role in the onboarding flow unambiguous.

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 explicit usage context: 'Start zero-human onboarding'. It also tells the agent what to do next with the result, which is practical workflow guidance. It does not explicitly mention alternatives or when not to use this tool, but the context is clear enough.

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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