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Lightning Memory

Lightning Memory

by singularityjason
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

ln_spending_summary

Review spending breakdown by vendor and protocol with a configurable time period to manage your Lightning budget.

Instructions

Get a spending summary for budget awareness.

Shows total sats spent, broken down by vendor and protocol.

Args: since: Time period. Relative: "1h", "24h", "7d", "30d". Or Unix timestamp.

Returns: Spending breakdown with totals by vendor and protocol.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "ln_spending_summary"
  }
}

Input Schema

NameRequiredDescriptionDefault
sinceNo30d

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.7.0

TDQS

B3.3/5.0
Behavior2/5

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

No annotations are provided, so the description carries full responsibility. It does not disclose whether the tool is read-only, safe, or has any side effects. While the output is described, behavioral traits like authentication needs or error handling are missing.

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 brief and front-loaded: one sentence for purpose, then structured Args and Returns. Every sentence adds value; no fluff.

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 tool with one optional parameter and no output schema, the description covers the main aspects. However, given the absence of annotations and sibling tools, a usage hint would improve completeness.

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?

The schema has 0% coverage, but the description explains the 'since' parameter format clearly: relative time periods (1h, 24h, 7d, 30d) or a Unix timestamp. This adds meaning beyond the schema's type and default.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it retrieves a spending summary for budget awareness, showing total sats spent broken down by vendor and protocol. This is a specific verb and resource, but it does not explicitly distinguish from sibling tools like ln_budget_check or ln_budget_status, which are related.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description says 'for budget awareness' implying a review purpose, but provides no explicit guidance on when to use this tool versus alternatives (e.g., ln_budget_check). There are no when-not or exclusion statements.

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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