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createBountyInvoice

Create a Lightning invoice for bounty escrow, specifying the issue ID and amount to enable secure payments.

Instructions

Create Lightning invoice for bounty escrow (POST /api/bounty/create). Use GITTR_LNBITS_* env or pass lnbitsUrl + lnbitsAdminKey. Publish kind 9806 after pay via publishBountyToNostr.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
amountYes
issueIdYes
lnbitsUrlNo
descriptionNo
lnbitsAdminKeyNo
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the HTTP method (POST), authentication requirements (lnbits credentials), and the post-payment action of publishing to Nostr. However, it does not disclose side effects on the bounty, whether the operation is idempotent, or what happens on failure. The description adds useful context but lacks important behavioral details.

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, two sentences long, and front-loaded with the main action. Every sentence adds valuable information: the endpoint, credentials, and the follow-up Nostr publication. There is no fluff or repetition.

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?

The tool has moderate complexity with a payment flow and a Nostr publishing step, and there is no output schema. The description covers the main action and the post-pay step, but it does not explain the expected return value (e.g., invoice details, payment request), how payment status is checked, or error scenarios. For an agent to use this tool effectively and handle the follow-up, more context would be beneficial.

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 explains the optional credential parameters (lnbitsUrl, lnbitsAdminKey) and mentions env var alternatives, but it does not explain the required parameters (issueId, amount) or what values they should take (e.g., amount in satoshis). The description gives only partial parameter guidance, leaving the most critical inputs ambiguous.

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 creates a Lightning invoice for bounty escrow, giving a specific verb and resource. It also provides the endpoint (POST /api/bounty/create), which precisely defines the operation. This distinguishes it from sibling bounty tools like bountyRelease or submitBounty.

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 create a Lightning invoice for bounty escrow) and gives instructions on authentication via env vars or passing credentials. It also mentions a follow-up action (publish via publishBountyToNostr after payment), which helps the agent understand the workflow. However, it does not explicitly mention when not to use it or compare with alternative tools.

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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