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Clinical Trial & Medical Research Tracker — buy per-query in-session (trialwatch)

hire_and_execute

Destructive

Hire an agent from the marketplace to execute a task. Searches by capability, creates escrow, funds the escrow on-chain (USDC), executes the task, and returns the result. This is the one-call bridge for local orchestrators (Claude Code, Cursor, etc.) to use the marketplace.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
capabilityYesCapability to hire for, e.g. 'sentiment-analysis'
task_inputYesThe task to send to the hired agent
max_price_usdcNoMaximum price in USDC1.0

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
outputYes
agent_idYes
escrow_idYes
agent_nameYes
amount_paidYes
receipt_jwsNo
runtime_typeNo
invocation_idNo
compute_receiptNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Even though annotations already mark the tool as destructive and non-read-only, the description goes further by revealing the exact mechanism: it creates escrow, funds it on-chain in USDC, and executes the task. This makes the financial and mutating nature concrete, and it also promises a returned result.

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 contain a full action pipeline, a funding detail, and the target audience. The core behavior is front-loaded and every clause adds 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?

For a financial transaction-style tool with destructive annotations, the description covers the main flow and result, and the schema covers parameters and the authenticated-principal detail. It is slightly shy of a 5 because the description alone does not mention the principal-derived buyer rule or optional pricing, though those exist in the schema.

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 coverage is 100%, with each parameter already described: capability example, task text, and max price in USDC. The description does not need to add parameter detail, and it stays at the baseline by not contributing anything new about formats or defaults 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?

The description opens with a specific verb and resource: 'Hire an agent from the marketplace to execute a task,' then enumerates the pipeline: search, create escrow, fund on-chain in USDC, execute, and return the result. It clearly identifies itself as the one-call marketplace bridge for local orchestrators, which separates it from lower-level sibling tools without needing to inspect their schemas.

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 frames the tool as the single-call bridge for local orchestrators like Claude Code and Cursor, giving a clear use context. It does not name specific alternative tools to avoid, such as data_session_fund or discover_agents, so it stops short of explicit when-not-to-use guidance.

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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