get_dynamic_endpoint_definition_schemaGet the JSON Schema a dynamic endpoint definition must satisfy. Fetch this before authoring the definition for create_dynamic_endpoint / create_dynamic_endpoint_version.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| json_schema | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds context by explaining that the returned schema is a required precondition for authoring dynamic endpoint definitions, which goes beyond the annotations and clarifies the tool's role in the workflow.
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?
The description is two sentences with no wasted words. The main purpose is front-loaded, and the second sentence adds essential workflow guidance about which create tools it supports.
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 zero-parameter read-only tool with an output schema, annotations, and clear reference to the dependent create operations, the description is fully sufficient. Nothing needed to invoke the tool correctly is missing.
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 tool has zero parameters, so the baseline is 4 per the rubric. There is nothing additional to document about parameters in the description.
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?
The description states a specific verb and resource: 'Get the JSON Schema a dynamic endpoint definition must satisfy.' This clearly identifies what the tool does and differentiates it from sibling get_*_definition_schema tools by naming the dynamic endpoint resource explicitly.
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?
The description gives clear usage context: 'Fetch this before authoring the definition for create_dynamic_endpoint / create_dynamic_endpoint_version.' It does not explicitly mention alternatives for other definition schemas, but the resource-specific naming and sibling list make the applicable context clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Every resource family follows the same verb+noun pattern and each tool name uniquely identifies a resource-action pair (create_app vs create_app_version vs update_app vs publish_app). Closest overlaps like analyze_resource vs get_resource_graph and patch_datafile vs update_datafile are explicitly differentiated by their descriptions, so misselection risk is low despite the scale.
Names are almost uniformly verb_noun snake_case with a consistent lifecycle vocabulary: create/get/update/delete/list/publish/unpublish/version. Minor outliers like whoami and run_schedule_now are idiomatic and do not break the predictability of the set.
At 93 tools this far exceeds the calibration's 50+ extreme-mismatch case. The count is inflated by repeating create/get/update/delete/version/publish/unpublish across ten resource families; even though each family is systematic, the combined surface is very hard for an agent to navigate and keep in context.
Core CRUD/publish/version lifecycles are present for apps, workflows, endpoints, schedules, schemas, datafiles, and api templates, and dependency analysis is well covered. However, secret creation/updating, asset upload, custom-domain deletion, and version-range enumeration for several resource types are absent or left to the external dashboard, so agents hit a few manual dead ends.