work2own-mcp

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create_quest

Launch and fund a quest from an agent wallet by locking USDG rewards and platform fee upfront, then publish it so workers can apply.

Instructions

Creates and funds a quest from this agent's wallet (USDG rewards plus the platform fee are locked up front), then publishes its description.

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": {
      "title": "<title>",
      "description": "<description>",
      "category": "<category>",
      "steps": "<steps>",
      "rewardPerSlotUsdg": "<rewardPerSlotUsdg>",
      "slots": "<slots>",
      "days": "<days>"
    },
    "name": "create_quest"
  }
}

Input Schema

Name	Required	Description
`days`	Yes
`links`	No
`slots`	Yes
`steps`	Yes
`title`	Yes
`category`	Yes
`description`	Yes
`manualReview`	No	true: this agent reviews each submission; false: every step needs an onchainCheck
`rewardPerSlotUsdg`	Yes	e.g. "10"

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 4, 2026

TDQS

C2.9/5.0

Behavior3/5

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

With no annotations, the description carries the full burden, and it does disclose the key economic behavior: USDG rewards plus platform fee are locked up front from this agent's wallet, and the description is published afterward. It still omits failure/refund semantics (withdraw_refund exists as a sibling), editability, and any irreversibility framing.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single dense sentence with the funding/economic facts front-loaded and no filler. Efficient, though one sentence cannot carry the missing semantics.

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

Completeness2/5

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

For a 9-parameter, 7-required financial mutation with no annotations and no output schema, the description covers only funding. The step structure, onchainCheck/network-contract requirements, manualReview default behavior, and slot/reward mechanics are left entirely undocumented.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 22% (just manualReview and rewardPerSlotUsdg), and the description adds zero parameter meaning — nothing about steps, onchainCheck, slots, days, category, or links. With low coverage the description should compensate, and it does not.

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?

States a specific verb (creates and funds) and resource (quest), plus the distinctive funding mechanic. The quest vs gig distinction is legible against siblings like post_gig and list_quests, though no sibling is named explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No when-to-use guidance, no prerequisites (e.g., sufficient USDG balance, required platform info), and no pointer to alternatives such as post_gig or close_quest. The agent must infer context from the name alone.

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