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numenews

numenews

by DisMosGit
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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compute_numerology

Reduce text to its numerological value, returning the gematria sum, digit-reduced value, master-number status, and calculation steps.

Instructions

Reduce a text to its numerological value.

Returns the raw gematria sum, the digit-reduced value (11, 22 and 33 are master numbers and are not reduced further), whether the value is master, and the rendered calculation steps. Pure logic: no Qdrant, no model, no configuration.

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": {
      "text": "<text>"
    },
    "name": "compute_numerology"
  }
}

Input Schema

NameRequiredDescriptionDefault
textYes

Output Schema

NameRequiredDescriptionDefault
textYes
valueYes
gematriaYes
breakdownYes
is_masterYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does so reasonably: it declares the tool pure logic with no Qdrant, model, or configuration dependencies, implying a deterministic, side-effect-free computation. It also previews the output shape (raw sum, reduced value, master flag, steps). It omits any note on edge cases (e.g., non-letter characters) but covers the key behavioral profile.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The purpose is front-loaded in the first sentence, followed by output and behavioral notes. It is efficient, though the detailed enumeration of return values is partly redundant given that an output schema exists.

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 single-parameter, side-effect-free computation with an output schema, the description gives enough to call it correctly: input intent, return contents, and absence of external dependencies. Missing only index/usecase routing among siblings.

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?

One string parameter with 0% schema description coverage, so the schema tells the agent nothing. The description implies the input is text to be reduced, which is essentially self-evident from the parameter name, and adds no format or handling details (case, digits, symbols). Minimum-viable rather than compensating for the coverage gap.

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?

States a specific verb and resource ('reduce a text to its numerological value') with the core transformation named up front, so the agent knows exactly what the tool computes. It does not, however, distinguish itself from the closely related sibling check_master_numbers, which also deals with master numbers.

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?

There is no explicit statement of when to use this tool versus alternatives. 'Pure logic: no Qdrant, no model, no configuration' hints at a contrast with query_qdrant, but no alternative is named and no selection condition is given.

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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