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Lightning Memory

Lightning Memory

by singularityjason
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Python
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ln_agent_verify

Look up an agent's compliance attestation by providing its Nostr public key. Returns attestation details or indicates unknown status.

Instructions

Look up an agent's compliance attestation.

Args: agent_pubkey: The agent's Nostr public key to verify.

Returns: Attestation details or {status: "unknown"} if not found.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "agent_pubkey": "<agent_pubkey>"
    },
    "name": "ln_agent_verify"
  }
}

Input Schema

NameRequiredDescriptionDefault
agent_pubkeyYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.7.0

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations provided, the description adequately discloses the tool's behavior: it performs a lookup and returns either attestation details or a status object. It does not mention side effects, permissions, or rate limits, but given the simple read operation, the description is sufficient.

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 extremely concise with a clear header and structured Args section. Every sentence adds value: the first line states purpose, and the Args and Returns explain the single parameter and output. No unnecessary information.

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?

Given the tool's simplicity (one required parameter, no output schema), the description covers all necessary aspects: purpose, parameter, and return format (including the 'unknown' status case). It is complete for an agent to correctly select and invoke the tool.

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

Parameters5/5

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

The input schema has 0% description coverage, so the description carries the full burden. It defines the parameter 'agent_pubkey' as 'The agent's Nostr public key to verify', adding meaningful context beyond the schema's type field. This fully 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?

The description clearly states the verb 'look up' and the resource 'compliance attestation', making the tool's purpose explicit. It distinguishes itself from siblings like ln_agent_attest, which likely creates attestations, by focusing on verification.

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

Usage Guidelines3/5

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

The description implies usage for checking existing attestations but does not explicitly state when to use this tool versus alternatives like ln_agent_attest for creation. The context is clear but not prescriptive.

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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