list_app_versionsGet the earliest and latest version numbers of an app (by slug or id), to know the range you can fetch with get_app_version.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | No | the app slug (provide this or app_id) | |
| app_id | No | the app id (provide this or slug) |
| Name | Required | Description | Default |
|---|---|---|---|
| latest_version | Yes | ||
| earliest_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?
Annotations already declare readOnlyHint=true and destructiveHint=false, covering safety. The description adds useful behavioral context beyond the annotations by specifying that the tool returns only the earliest and latest version numbers rather than all versions, and by framing the result as a fetchable range.
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 sentence with no filler: it states the action, the resource, the acceptable identifiers, and the purpose relative to get_app_version. The key scoping detail (earliest/latest range) is front-loaded and every phrase earns its place.
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 low-complexity, read-only lookup with an output schema present and both parameters fully documented, the description is sufficient. It explains what the tool returns and why an agent would call it, and the sibling context plus annotations cover the remaining operational guidance.
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%, and the schema already documents that slug or app_id can be provided as alternatives. The description repeats "by slug or id" but adds no new format, constraints, or interaction details beyond what the schema provides, so baseline 3 is appropriate.
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 earliest and latest version numbers of an app," clarifying that this tool returns a range rather than a full list. It also differentiates from the sibling get_app_version by explicitly framing the output as the range one can fetch, so an agent can distinguish the two.
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 context for when to use the tool: to learn the range before fetching a specific version with get_app_version. It names the relevant alternative but does not explicitly state exclusions or exactly when not to use it, so it stops slightly short of a perfect 5.
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.