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aimedialab

Risha.ai MCP Server

Official
by aimedialab

risha_create_generation

Create a generation request and automatically poll until it completes or fails, replacing manual create and read steps.

Instructions

Create a Risha generation request and optionally poll until completed/failed. Use this instead of manual create/read polling.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
waitNo
titleNo
capabilityYesRisha capability ID
pollSecondsNo
prompt_dataYesPrompt payload expected by the capability
timeoutSecondsNo
Behavior2/5

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

No annotations are provided, so the description bears full burden for behavioral disclosure. It mentions optional polling but does not disclose mutation effects, authentication requirements, cost implications, or error handling. For a creation tool, this is minimal disclosure.

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, front-loaded with the primary action and a key benefit. Every word contributes to understanding. No unnecessary details.

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?

Given the tool's complexity (6 parameters, nested object, no output schema, no annotations), the description is too brief. It does not explain the return value, error conditions, or how polling parameters interact. The user agent lacks critical context for correct invocation.

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?

The input schema has 33% coverage (only capability and prompt_data have descriptions). The description adds no parameter-specific details. It does not explain how wait, pollSeconds, timeoutSeconds, or title affect behavior. High schema coverage would mitigate this, but low coverage demands more from the description, which is absent.

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?

The description clearly states the tool creates a Risha generation request and optionally polls until completion or failure. It hints at differentiation from manual alternatives ('Use this instead of manual create/read polling'), but does not explicitly distinguish from sibling tools like risha_call or risha_generate_image.

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 advises using this tool instead of manual create/read polling, providing clear context on when to use it. However, it does not specify when not to use it or list explicit alternatives, leaving some ambiguity.

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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