Tessryx

Create schema

create_schema

Schema authoring — create a BRAND-NEW schema (mints the schema + its version 1). json_schema is the JSON Schema body datafiles bound to this schema (by schema_id) are validated against; property order is preserved exactly — it sets the field order of the generated editor, so author it in the order you want humans to see. Media uploads, entity references, cron and colors need an x-tessryx-ui hint or they render as bare text — get_guide("schemas"). Pass publish=true to publish schema version 1 immediately (the version datafiles resolve by default), or later with publish_schema. (To add a version to a schema that already exists, use create_schema_version.)

Input Schema

TableJSON Schema

Name	Required	Description
`slug`	Yes	URL-safe slug, optionally hierarchical.
`publish`	No	If true, immediately publish the version this call creates (the common create-then-publish in one step). Defaults to false; omit to leave the version as an unpublished draft.
`description`	No	What this schema describes.
`json_schema`	Yes	The JSON Schema body datafiles validate against; becomes version 1. Property order is preserved verbatim.
`display_name`	No	Human-readable name.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`slug`	Yes
`version`	Yes
`published`	Yes
`schema_id`	Yes

Schema Changelog

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

First observedSep 7, 2026

TDQS

A4.9/5.0

Behavior5/5

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

Beyond the sparse annotations, the description discloses important behavioral details: property order is preserved and becomes the editor field order, certain types need x-tessryx-ui hints to render properly, and publish defaults to false. It makes the side effects of the call clear.

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?

The description is dense but every sentence carries important operational knowledge. It front-loads the core purpose, then flows naturally from schema authoring details to publishing and versioning alternatives without wasted words.

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?

Given the output schema exists and all parameters are already described in the input schema, the description covers the remaining contextual needs: version creation, publishing behavior, ordering semantics, and UI rendering caveats. An agent has enough to invoke this tool correctly and avoid common pitfalls.

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 description coverage is 100%, so the baseline is 3. The description adds meaningful semantics for json_schema (order preservation, UI implications, hint requirements) and publish (immediate publication semantics), going beyond the raw schema definitions.

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 clearly states it creates a brand-new schema and implicitly its version 1, using a specific verb and resource. It explicitly distinguishes itself from create_schema_version, so an agent can tell them apart immediately.

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

Usage Guidelines5/5

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

The description gives concrete routing guidance: use create_schema_version when adding a version to an existing schema, use publish_schema for later publishing, and consult get_guide("schemas") for UI hints. This is explicit and directly actionable.

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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