Tessryx

Get schedule version

get_schedule_version

Read-only

Read back the full stored definition of a schedule version by slug or id. Returns the exact definition body that was authored (as a JSON string, so you can parse it to diff or patch and resubmit as a new version) plus its checksum. Omit version to get the latest version.

Input Schema

TableJSON Schema

Name	Required	Description
`slug`	No	the schedule slug (provide this or schedule_id)
`version`	No	specific version to fetch; omit (0) for the latest version
`schedule_id`	No	the schedule id (provide this or slug)

Output Schema

TableJSON Schema

Name	Required	Description	Default
`version`	Yes
`definition`	Yes
`content_sha256`	Yes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

First observedSep 7, 2026

TDQS

A4.5/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description adds meaningful behavioral context beyond the annotations: it discloses that the return value is a JSON string containing the authored body and a checksum, and that omitting version fetches the latest. The readOnlyHint and destructiveHint annotations align with the read-only nature of the description, with no contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three concise sentences with no filler. The core purpose is front-loaded, and the return-format detail and version default are mentioned efficiently without unnecessary elaboration.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description is complete for this tool's complexity: it covers what the tool returns, how to identify a version, and the default behavior. The output schema and annotations cover return structure and safety, so nothing essential is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds value by clarifying that slug and schedule_id are alternative lookup keys and that omitting version returns the latest version, reinforcing and extending the schema's parameter descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action ('Read back the full stored definition') on a specific resource ('a schedule version') and clarifies the lookup by slug or id. It clearly differentiates this tool from siblings like list_schedule_versions, which lists versions, and get_schedule_definition_schema, which returns the schema rather than the stored definition.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It provides clear context for when to use the tool: when you need the exact authored definition body, checksum, or latest version. It does not explicitly exclude alternatives or state when not to use it, but the purpose is specific enough that an agent can infer the correct usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A4/5.0

Disambiguation5/5

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.

Naming Consistency5/5

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.

Tool Count1/5

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.

Completeness4/5

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.

Resources

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