list_schedule_versionsGet the earliest and latest version numbers of a schedule (by slug or id), to know the range you can fetch with get_schedule_version.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | No | the schedule slug (provide this or schedule_id) | |
| schedule_id | No | the schedule 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 meaningful behavior: it returns only the earliest and latest version numbers, not the versions themselves, and supports lookup by slug or id. This is enough for an agent to predict the call's outcome.
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, focused sentence that front-loads the core action ('Get the earliest and latest version numbers') and immediately explains the purpose. Every word 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?
The tool is simple, has an output schema, and its annotations cover safety. The description fully explains the operational context and the relationship to get_schedule_version, so nothing critical 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?
Schema coverage is 100%, with both slug and schedule_id already described as 'provide this or' the other. The description repeats this relationship but adds no new detail about formats, constraints, or mutual exclusivity beyond what the schema supplies.
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 ('Get'), a precise resource ('earliest and latest version numbers of a schedule'), and the identifier options (slug or id). It clearly distinguishes this from the sibling get_schedule_version by framing it as the range-finder for that follow-up call.
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: use it to determine the version range before fetching with get_schedule_version. It does not explicitly exclude other tools or list when-not-to-use scenarios, but the intended workflow is evident.
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.