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RYLA

ryla_generation_status

Check the status of a generation job by its jobId.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jobIdYesThe jobId returned by a ryla_generate_* tool call

Schema Changelog

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

  1. First observed

TDQS

A3.6/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states that a status is checked; it does not say whether the call is read-only, whether it can be polled repeatedly, what statuses can be returned, or what happens for an invalid/expired jobId.

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 a single, front-loaded sentence with no wasted words. It names the action, the target, and the required identifier immediately.

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 one-parameter status tool with no output schema, the description plus schema covers what an agent needs to invoke it correctly. It could mention expected output or polling behavior, but those are not required for basic invocation.

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%, and the single jobId parameter is already documented as coming from a ryla_generate_* tool call. The tool description adds no parameter-level detail beyond what the schema provides, so the baseline score of 3 is appropriate.

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 identifies a specific verb ('Check'), a distinct resource ('status of a generation job'), and the key input ('jobId'). This cleanly separates it from the sibling generation tools, which create jobs rather than report on them.

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

Usage Guidelines3/5

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

The description implies this tool is used after a generation call because it requires the jobId from a ryla_generate_* tool, but it never explicitly says when to use it or that it should be used for polling/completion checks. No alternatives or exclusions are mentioned.

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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TDQS

A3.7/5.0
Disambiguation4/5

Most tools map to a distinct generation type or resource, and the ryla_generate_* family is easy to partition by output type. The main ambiguity is ryla_generate_base_image vs ryla_generate_image, but the description for ryla_generate_image explicitly positions it as the primary Studio tool and clarifies the required characterId.

Naming Consistency4/5

The ryla_ prefix and snake_case are applied consistently, and generate_* forms a clear pattern for most action tools. A few names deviate from the verb_noun pattern (ryla_generation_status, ryla_server_info, ryla_account_credits_balance), but they are still predictable.

Tool Count5/5

At 11 tools, the set is well-scoped for a media generation server: generation types, status polling, account checks, and character lookup are each covered. The count supports the domain without feeling bloated.

Completeness3/5

The generation lifecycle is well-covered: jobs can be submitted, polled, status checked, and outputs viewed via the gallery. However, character management is almost entirely absent: there is no way to create, update, or delete a character through the MCP, and the list_characters description explicitly pushes creation to the external app, leaving a notable workflow gap.

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