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ln_preflight

Check payment safety by running budget limits, anomaly detection, and trust verification. Prevents overspending, price anomalies, and unverified vendors before processing.

Instructions

Pre-flight check before making a payment.

Runs budget limits, anomaly detection, and trust verification to produce an approve/reject/escalate decision. Use this before every payment to catch overspending, price anomalies, and unverified vendors.

Args: vendor: Vendor name or domain. amount_sats: Proposed payment amount in satoshis.

Returns: Decision: verdict (approve/reject/escalate), reasons, budget remaining, anomaly status, and trust score.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
vendorYes
amount_satsYes
Behavior4/5

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

No annotations provided, so description carries full burden. It discloses the three types of checks (budget, anomaly, trust) and the key elements of the return value (verdict, reasons, budget remaining, anomaly status, trust score). This is sufficient for a non-destructive verification tool.

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 well-structured with clear sections for purpose, usage, arguments, and returns. Each sentence adds value. No redundant or extraneous text.

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

Completeness5/5

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

The tool has two required parameters and no output schema. The description thoroughly covers both parameters with meaningful descriptions, and includes a Returns section that details the decision structure. Given the simplicity of the tool, this is complete.

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

Parameters4/5

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

Schema descriptions are empty (0% coverage). The description's Args section adds meaning: 'vendor: Vendor name or domain' clarifies the format, and 'amount_sats: Proposed payment amount in satoshis' specifies the unit. This compensates for the lack of schema descriptions.

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?

Description explicitly states it is a 'pre-flight check before making a payment' and lists the specific checks (budget limits, anomaly detection, trust verification). It clearly distinguishes from sibling tools that are more specialized (e.g., ln_budget_check, ln_anomaly_check, ln_vendor_reputation) by being an integrated check.

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?

Explicitly says 'Use this before every payment to catch overspending, price anomalies, and unverified vendors.' This provides clear context on when to use it. It does not explicitly mention when not to use it or alternatives, but the purpose is clear enough that an agent would know this is the primary pre-flight check.

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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