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Magic 8 Ball Ask

magic_8_ball_ask
Read-onlyIdempotent

Ask a yes-or-no question and get a mystical answer. Returns response text. Supports cynical mode for negative-weighted answers or corporate mode for business jargon. Use when you need a random decision, tie-breaker, or humorous perspective.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cynicalNoWeighted toward negative responses
questionYesYour yes-or-no question for the Magic 8-Ball
corporateNoAll answers in business speak

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
magic_8_ball_responseYesThe mystical answer from the Magic 8-Ball

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds value by explaining the response type ('Returns response text') and the two optional modes (cynical, corporate), which are not covered by annotations.

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?

Two sentences with no filler. The first sentence states the core purpose, and the second adds usage guidance and mode features. Every word serves a purpose.

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?

Given the low complexity (3 simple parameters, output schema present), the description covers purpose, usage, and modes. It could mention that answers are random or that there is no factual basis, but it is adequate for an agent to understand the tool's role.

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 description coverage is 100%. The description complements the schema by explaining the effect of 'cynical' (negative-weighted) and 'corporate' (business jargon) beyond the schema definitions. While most meaning is already in schema, the description adds helpful context.

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 ('Ask'), the resource ('yes-or-no question'), and the outcome ('get a mystical answer'). It also mentions support for cynical and corporate modes, distinguishing it from any potential sibling tools.

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?

The description explicitly says 'Use when you need a random decision, tie-breaker, or humorous perspective,' providing clear context for when to invoke the tool. It does not include negative guidance but is sufficient.

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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TDQS

A4.2/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, but the three ask_pipeworx variants (standard, beta, grounded) share similar routing and could cause confusion for an agent. The memory tools and novelty tool are distinct. Overall, ambiguity is low.

Naming Consistency4/5

Tool names follow a consistent snake_case verb_noun pattern (e.g., ask_pipeworx, compare_entities, subscribe). Minor deviations like 'search_within' and 'magic_8_ball_ask' do not break the pattern. High consistency.

Tool Count3/5

With 32 tools, the server is on the heavier side for a single MCP server. However, given the broad domain coverage (financials, economics, prediction markets, etc.), each tool serves a distinct purpose. Bordering on too many, but justified by scope.

Completeness4/5

The tool surface covers a comprehensive range of data research operations: querying, deep research, entity profiling, comparisons, discovery, subscriptions, alerts, claim validation, and prediction market analysis. Minor gaps exist (no data modification tools), but they are out of scope for a query-oriented server.