DPYC Oracle

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check_ban_status

Checks an npub's membership status to determine if it is banned under the DPYC Social Contract. Returns true only for known banned members, letting operators enforce bans during credit purchases.

Instructions

Check whether an npub is banned from the DPYC Social Contract.

Looks up the member in the community registry and checks whether their status is "banned". Unknown npubs are not considered banned (they simply aren't members).

Free, unauthenticated. Used by operators during the cold path (credit purchases) to enforce community bans.

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": {
      "npub": "<npub>"
    },
    "name": "check_ban_status"
  }
}

Input Schema

Name	Required	Description	Default
`npub`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.3.0Sep 15, 2026

TDQS

A4.2/5.0

Behavior4/5

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

With no annotations, the description carries the full burden. It discloses a key behavior: 'Unknown npubs are not considered banned (they simply aren't members).' Also states 'Free, unauthenticated,' which is useful for understanding access. The read-only nature is implied by 'Check whether.' While side effects are not explicitly denied, the description provides sufficient behavioral context for a simple lookup.

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?

Three short sentences/paragraphs, each adding value. The main purpose is first, followed by nuance and usage context. No redundancy or filler.

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 tool with one param and an output schema, the description covers the operation, the not-found case, auth requirements, and typical usage. It does not describe rate limits or data freshness, but these are not critical for this simple check. The output schema exists, so return-value details are not needed here.

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

Parameters3/5

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

The schema has only one parameter 'npub' with no description (0% coverage). The description mentions the parameter in the tool's purpose and states 'Looks up the member in the community registry,' which explains its use. However, it does not specify format, valid values, or edge cases beyond the unknown-npub behavior, which is more behavioral than parameter semantics. Thus minimal additional meaning.

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 opens with a specific verb and resource: 'Check whether an npub is banned from the DPYC Social Contract.' This clearly distinguishes it from sibling tools like cast_ban_vote (which votes on bans) and lookup_member (which retrieves member details).

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 provides explicit context: 'Used by operators during the cold path (credit purchases) to enforce community bans.' and states 'Free, unauthenticated.' It does not explicitly mention alternatives, but the intended use case is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.