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GroundTruth Field Evidence

by io.github.unspecifiedcoder
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Review Task

review_task

Review a submitted proof and accept or reject it. Accept releases the on-chain payout to the human oracle; reject fails the task with no payout. Call this after task_status shows the proof.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "task_id": "<task_id>",
      "decision": "<decision>"
    },
    "name": "review_task"
  }
}

Input Schema

NameRequiredDescriptionDefault
reasonNoOptional note explaining the decision
task_idYesThe task ID to review
decisionYesaccept = pay the oracle; reject = no payout

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses the two outcomes and their financial consequences (accept releases payout, reject fails with no payout), which are the key behavioral traits. It does not mention irreversibility, but the effect is clear and the tool is simple.

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 two sentences with zero waste. The core action and consequences are front-loaded, and the usage condition is stated immediately after.

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 simple tool with no output schema, the description covers what it does, when to use it, and the consequences. It does not describe the response format, but that is not required without an output schema, and the tool is straightforward.

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 the schema already documents all parameters. The description adds the timing condition (after proof is shown) but does not elaborate on parameter specifics beyond the schema, meeting the baseline for high coverage.

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 verb (review), the resource (submitted proof), and the binary decision (accept/reject) with explicit payout consequences. It distinguishes itself from siblings like task_status by focusing on the action rather than status retrieval.

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 states when to call ('Call this after task_status shows the proof'), providing a clear precondition. It does not name alternatives or when-not cases, but the sibling tools are obviously different in purpose, so the guidance is sufficient.

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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