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Conspiracy Theory

Conspiracy Theory Generate

conspiracy_theory_generate
Read-onlyIdempotent

Generate a conspiracy theory in one of three modes: 'connect' (link thing_one + thing_two), 'investigate' (explore an event), or 'complete' (extend an "I have noticed that..." prompt). Control depth (surface/deep/full_tinfoil) and confidence level.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeYes
depthNo
eventNoEvent to investigate (investigate mode)
promptNo"I have noticed that..." (complete mode)
thing_oneNoFirst thing to connect (connect mode)
thing_twoNoSecond thing to connect (connect mode)
confidenceNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
depthNoDepth of investigation applied
theoryNoGenerated conspiracy theory text
confidenceNoConfidence level of the theory
connectionsNoSupporting connections or related concepts

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added
  2. Removed
  3. First observed

TDQS

A4.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, covering safety and behavior. The description reinforces that the tool generates new content (open world) but adds little beyond what annotations provide, such as the mode-specific behavior.

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 a single sentence (35 words) that efficiently covers all modes, controls, and parameter associations. It is front-loaded with the action 'Generate a conspiracy theory' and wastes no words, achieving high density of useful information.

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 tool's moderate complexity (3 modes, 7 parameters) and the presence of an output schema, the description is largely complete. It explains the modes and how to control them but does not describe the output structure, which is handled by the output schema.

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 description adds meaning beyond the schema by linking parameters to specific modes (e.g., thing_one/thing_two for connect, event for investigate, prompt for complete). This clarifies conditional parameter usage, which the schema alone does not express. Schema description coverage is 57%, and the description compensates by explaining which parameters are relevant for each mode.

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 tool generates conspiracy theories in three distinct modes ('connect', 'investigate', 'complete') with specific verbs like 'link', 'explore', and 'extend'. It differentiates the tool from sibling tools, which are focused on research and prediction rather than creative generation.

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 explains when to use each mode (connect two things, investigate an event, complete a prompt) but does not explicitly state when not to use the tool or compare it to alternatives. However, the modes are self-explanatory and provide enough context for an agent to choose appropriately.

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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