stability_list_engines
Lists all available Stability AI generation engines for the UnClick MCP Server using your API key.
Instructions
List all available Stability AI generation engines.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| api_key | Yes |
Lists all available Stability AI generation engines for the UnClick MCP Server using your API key.
List all available Stability AI generation engines.
| Name | Required | Description | Default |
|---|---|---|---|
| api_key | Yes |
Changes observed during successful MCP inspections.
v0.1.9v0.1.5Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is fully covered. The phrase 'all available' adds a modest signal that the list is complete and unpaginated, but the description says nothing about auth requirements (the required api_key) or the shape of a returned engine record.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One short sentence, front-loaded with the verb and resource, with no wasted clauses. There is nothing to trim and nothing buried.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only catalog tool with no output schema and full annotation coverage, the essentials are present, but the description omits the one linkage an agent actually needs: that these engine identifiers feed the Stability generation tools. With no output schema, the return shape is also left entirely to inference.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter is api_key with 0% schema description coverage, so the description is the only place semantics could be documented — yet it never mentions the credential at all. The name is self-explanatory enough that an agent will likely supply it correctly, keeping this at minimum-viable rather than poor.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb ('List') and resource ('Stability AI generation engines') with the scope 'all available'. An agent can tell this apart from the generation siblings (stability_text_to_image, stability_upscale) because it retrieves catalog data rather than producing images, though the description never explicitly names those alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No when-to-use guidance and no mention of the sibling tools it complements. The obvious use case — discovering engine IDs before calling stability_text_to_image — must be inferred entirely by the agent rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.