unpublish_dynamic_endpointTake a dynamic endpoint offline so its public URL stops serving content.
| Name | Required | Description | Default |
|---|---|---|---|
| endpoint_id | Yes | the endpoint id to take offline |
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | ||
| version | No | ||
| definition | No | ||
| public_url | No | ||
| description | Yes | ||
| endpoint_id | Yes | ||
| content_type | Yes | ||
| display_name | Yes | ||
| latest_version | Yes | ||
| last_published_version | 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?
The annotations already signal destructiveHint=true and openWorldHint=false. The description adds that the public URL stops serving content, which is the operative behavioral effect, but it does not mention reversibility, state prerequisites (e.g., must be currently published), or whether existing pending runs are affected. With annotations carrying the safety signal, this is acceptable but not rich.
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?
A single, front-loaded sentence communicates the action, the resource, and the observable effect. No filler or repetition of the input schema.
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 one-parameter lifecycle action with annotations and an output schema, the description covers the essential behavior. It is slightly thin on prerequisites and reversibility, but nothing critical is missing for an agent to invoke this tool correctly.
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?
Schema description coverage is 100%: the endpoint_id property is already described as 'the endpoint id to take offline'. The description adds the public URL context but no additional format, source, or selection guidance, so it does not meaningfully elevate the parameter semantics beyond the schema baseline.
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 tool's description states a specific action ('take a dynamic endpoint offline') and its direct consequence ('its public URL stops serving content'). This clearly distinguishes unpublish from delete_dynamic_endpoint and update_dynamic_endpoint, using the lifecycle verb 'unpublish'.
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: it is the action for making a dynamic endpoint stop serving publicly while presumably keeping it available for republishing. It does not explicitly name alternatives or list when-not-to-use conditions, but the context is unambiguous enough for an agent to select it.
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.