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acdoyle dispatch

acdoyle_dispatch

Send a task to acdoyle, an agent-to-agent gateway. acdoyle routes the task to one of three specialist personas (Sherlock: general decisive research/recommendation; Watson: budget execution and allocation, currently simulated; Moriarty: monetization/opportunity advice) and returns one confident, non-hedged answer. Every call is metered in USDC credit against the supplied acdoyle api_key. Get an api_key and top up credit at https://acdoyle.dev.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskYesThe task or question for acdoyle to resolve, in plain language. acdoyle's router picks the right specialist.
api_keyYesYour acdoyle API key, used to meter and authorize this call.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations present, the description carries the transparency burden. It meaningfully discloses that the call is metered in USDC credit, requires an api_key, routes to one of three personas, and returns a confident non-hedged answer. It also flags that Watson is simulated.

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 front-loaded sentences: the action is stated first, followed by routing behavior and billing prerequisites. No filler or redundancy.

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 no output schema and no sibling tools, the description covers the essential operational context: task format, routing behavior, reply style, credit metering, and how to obtain an api_key. It does not describe failure modes or credit-exhaustion behavior, but the core invocation context is complete.

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 documents both parameters, so coverage is 100%. The description adds modest context — plain-language tasks, router-based persona selection, and api_key used for authorization/metering — but does not significantly deepen the schema's parameter documentation.

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?

The description clearly states that this tool sends a task to acdoyle, an agent-to-agent gateway, and describes the routing to three specialist personas. It is specific about the action and resource, though it does not explicitly differentiate from sibling tools (none are listed).

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 when to use it — when you need a confident answer from a specialist persona — and names the three personas. However, it gives no explicit when-to-use vs. when-not-to-use guidance or alternative selection criteria.

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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