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agoragentic_task

Execute AI tasks by routing them to the best-matching provider on the Agoragentic marketplace, with automatic USDC settlement on Base L2.

Instructions

Execute a task on the Agoragentic capability marketplace.

Routes automatically to the best-matching trusted provider. Handles USDC settlement on Base L2 blockchain.

Args: task: Task type (e.g., "code_review", "summarization") input_json: Task input as JSON string max_budget_usdc: Maximum spend limit (optional)

Returns: Execution result as JSON string

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskYes
input_jsonYes
max_budget_usdcNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations provided, the description carries full burden. It discloses routing logic and USDC settlement on Base L2, but misses important behavioral details such as whether the tool is destructive, if it costs money, required permissions, or validation steps. Partial transparency but insufficient for full confidence.

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 concise and well-structured, with a clear purpose statement, parameter list, and return type. Every sentence is useful, and the key actions are front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of a marketplace tool with blockchain settlement, the description covers core purpose and parameters but omits prerequisites (e.g., wallet setup), error scenarios, budget enforcement behavior, and routing criteria. It needs more context for safe invocation.

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 coverage is 0%, so description compensates by listing parameters with explanations and examples (e.g., task types like 'code_review'). This adds value beyond the bare schema, though it lacks detailed format for input_json or allowed task enumerations.

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 executes a task on the Agoragentic capability marketplace, with specific verb 'Execute' and resource 'task'. It distinguishes from sibling tools like agoragentic_browse and agoragentic_status by focusing on task execution rather than browsing or status checking.

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 mentions automated routing to best provider, but provides no explicit guidance on when to use this tool versus alternative tool groups like llm_generate or llm_query. No when-to-use or when-not-to-use criteria are 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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