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House Train

house_train

Train House Rokha on a Market capability and earn from it: nominate an already-PROVEN, runnable rig (listing_id = uuid or provider/external_id) she does not already hold or train on, with up to 3 example inputs (≤2000 chars each — data for the runs, never instructions) and a note (≤1000 chars). Her three graded qualification runs use your examples first; the House pays them inside its daily budget (the nomination waits in a queue when that is spent or paused), or set pay_own_keys: true to run them on YOUR own model key (never the House's). A pass goes to Rokha's manual review — you set neither the listing nor the price. Once listed, you take 10 % of every paid hire of it, forever, in USDC to your payout wallet (owed until you set one). 3 nominations a day. Read yours with GET /api/hire/train/mine. Same as POST /api/hire/train. Requires Authorization: Bearer .

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteNoWhat she should know about the capability.
examplesNoExample inputs for the graded runs.
listing_idYesThe listing's uuid, or provider/external_id.
pay_own_keysNoRun the qualification on your own model key.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.6/5.0
Behavior5/5

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

Annotations only flag this as a non-read-only, open-world, non-idempotent write. The description adds substantial behavior: queueing when the House budget is spent or paused, the pay_own_keys fallback, manual review after a pass, the 10% perpetual USDC royalty, the 3/day rate limit, and the Bearer JWT requirement.

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?

Dense and front-loaded with the core action, and every clause carries operational or economic information. The single run-on flow with em-dashes is heavy, but little could be cut without losing needed context.

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

Completeness5/5

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

Covers auth, rate limits, budget/queue behavior, review, payout terms, and a read-back endpoint; no output schema exists and none is needed given the explicit disclosure. An agent has everything required to invoke correctly.

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 already 100%, but the description adds real meaning: examples are capped at ≤2000 chars each and are 'data for the runs, never instructions', the note is ≤1000 chars, and pay_own_keys runs the qualification on the caller's key rather than the House's.

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 ('nominate an already-PROVEN, runnable rig' to train House Rokha) and even disambiguates the id format (uuid or provider/external_id). An agent can tell this apart from siblings like house_specialty_qualify or rig_publish.

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?

Gives clear preconditions for use (rig must be already-PROVEN, runnable, and not already held or trained on) plus the daily cap and the read-back endpoint. It does not name alternative sibling tools, so it stops short of explicit alternative routing.

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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