Tessryx

Create schedule

create_schedule

Schedule authoring — create a BRAND-NEW schedule (mints the schedule + its version 1). The definition names a workflow (versioned-slug ref, published/latest), a recurrence (EITHER a 5-field cron + IANA timezone, OR an 'every N minutes/hours' interval), and an optional static input bound as the workflow's $input on every fire; fetch its JSON Schema with get_schedule_definition_schema and author against it. Pass publish=true to activate it (start firing) in one step, or publish later with publish_schedule. (To add a version to a schedule that already exists, use create_schedule_version.)

Input Schema

TableJSON Schema

Name	Required	Description
`slug`	Yes	Unique per-tenant slug; hierarchical path segments allowed (e.g. reports/daily-summary).
`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 Defaults to false; omit to leave the version as an unpublished draft.
`definition`	Yes	The schedule definition, as a JSON object. Fetch the exact JSON Schema it must satisfy with get_schedule_definition_schema and author against it (or copy an existing one with the get_*_version tool). The owning service validates it on submit.
`description`	No	What this schedule does (human + LLM-facing prose).
`display_name`	No	Human-readable name.

Output Schema

TableJSON Schema

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

Schema Changelog

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

First observedSep 7, 2026

TDQS

A4.6/5.0

Behavior4/5

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

Annotations are sparse ({openWorldHint:false, destructiveHint:false}), so the description carries the burden and meets it: it discloses that the call mints two artifacts (the schedule plus its version 1), that publish=true activates firing, and that the workflow definition must reference a versioned-slug (published/latest). It does not cover auth prerequisites or failure behavior, but the creation and activation semantics are clearly stated and consistent with destructiveHint=false.

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

Conciseness4/5

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

The description is a single dense paragraph but front-loaded with the core purpose ('Schedule authoring — create a BRAND-NEW schedule') and every clause earns its place: mint semantics, definition anatomy, publish behavior, and sibling routing. It is slightly repetitive with the definition parameter's schema text, but not bloated.

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?

For a complex tool with a deeply nested required parameter, an output schema, and several tightly related siblings, the description is complete: it says what artifacts are created, what the definition must contain, how to author it correctly, how publish/activation works, and exactly which sibling to use instead. Return-value explanation is unnecessary given the output schema.

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%, setting the baseline at 3, but the description adds genuine value beyond the schema: it explains the internal anatomy of the required 'definition' object (versioned-slug ref, cron+IANA timezone vs. 'every N minutes/hours' interval, optional $input binding), which the schema does not describe. This compensates for the one nested parameter with the most ambiguity.

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 opens with a specific verb and resource: 'create a BRAND-NEW schedule (mints the schedule + its version 1)'. The 'BRAND-NEW' qualifier and closing parenthetical explicitly contrast with create_schedule_version for existing schedules, so an agent can distinguish this tool from its closest sibling without opening the schema.

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?

Provides explicit when-to-use guidance: 'To add a version to a schedule that already exists, use create_schedule_version' names the exclusion condition and the alternative tool. It also explains the publish path alternatives (publish=true inline vs. publish_schedule later) and directs the agent to get_schedule_definition_schema before authoring the definition.

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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