Tessryx

Get dynamic endpoint version

get_dynamic_endpoint_version

Read-only

Read back the full stored definition of a dynamic endpoint 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 endpoint slug (provide this or endpoint_id)
`version`	No	specific version to fetch; omit (0) for the latest version
`endpoint_id`	No	the endpoint 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

A3.8/5.0

Behavior4/5

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

The description discloses the return payload: the exact authored definition as a JSON string and its checksum. It also explains that omitting version returns the latest, adding behavioral context beyond the readOnlyHint annotation. This is useful for agents planning to diff, patch, or resubmit.

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?

Two sentences with dense, relevant information. The core function is stated first, followed by return format details and the version behavior. No filler or redundant restatement of the title.

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

Completeness4/5

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

The description is complete for a read-only tool with an output schema: it states what is returned, how to select the version, and why the return format is useful. It doesn't explicitly warn that exactly one of slug/endpoint_id should be provided, but the schema's descriptions imply that choice.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents slug, version, and endpoint_id. The description adds that the tool reads 'by slug or id' and repeats the version omitting behavior, but it doesn't meaningfully enrich the parameter semantics beyond what the schema already provides.

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

Purpose4/5

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

The description clearly identifies a specific verb ('Read back'), a specific resource ('dynamic endpoint version'), and the retrieval criteria ('by slug or id'). It distinguishes itself from sibling tools like get_dynamic_endpoint by emphasizing the full stored definition of a version, though it doesn't explicitly name the sibling alternatives.

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

Usage Guidelines3/5

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

The description gives operational guidance ('Omit version to get the latest version') but does not state when to use this tool versus related tools such as get_dynamic_endpoint or preview_dynamic_endpoint. Usage context is implied but not explicit.

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.

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