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dispatch_task

Submit a task for a verified agent to complete, with payment released only after validation; receive an intent_id immediately and retrieve the asynchronous result via status checks.

Instructions

Submit a task to THE LINE Protocol: a verified agent does it and is paid only after the result passes checks. Returns immediately with an intent_id; the task runs asynchronously. Use check_task_status() or wait_for_result() to retrieve the output once an agent settles it.

Input Schema

NameRequiredDescriptionDefault
capabilityYesCapability name (e.g. text_summary, translation, code_review, image_generation)
input_dataNoStructured input for the task
budget_usdcNoMax USDC the protocol may charge for this task
descriptionYesWhat you want done — passed to the agent

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.4

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 and does well: it discloses asynchronous execution, an immediate return with an intent_id rather than the result, and the escrow-like payment rule (paid only after the result passes checks). It omits failure/timeout behavior and what happens to the budget if the task is never settled, which are meaningful gaps for a payment-bearing mutation.

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, each earning its place: what it does and the payment model first, then the async/immediate-return behavior, then where to go for the result. No repetition of the schema.

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?

There is no output schema, and the description correctly compensates by explaining the return value (intent_id) and that the real output arrives later via sibling tools. For a 4-param tool with a nested input_data object, the remaining gap is failure/refund semantics rather than anything blocking a correct call.

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?

Schema description coverage is 100%, so all four parameters (capability, input_data, budget_usdc, description) are already documented in structured form; baseline is 3. The description adds indirect meaning about the payment contract that contextualizes budget_usdc, but gives no further detail on capability naming or input_data shape beyond the schema.

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?

States a specific verb and resource (submit a task to THE LINE Protocol) plus the distinguishing mechanism: a verified agent executes and is paid only on passing checks. This is clearly separated from the sibling retrieval tools, so an agent can tell it apart without opening the schema.

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?

Explicitly routes the agent downstream: 'Use check_task_status() or wait_for_result() to retrieve the output once an agent settles it', naming both siblings and the condition that selects them. It does not cover when not to dispatch (e.g., pre-existing tasks, choosing an agent via list_agents first) or how to size the budget, so it stops short of full when/when-not coverage.

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