Tessryx

List schedule runs

list_schedule_runs

Read-only

List a schedule's fire history, newest-first. Each item is a thin REFERENCE to a workflow run (run_id + the cron slot it fired for) — resolve its status/output/traces with the workflow run tools (get_workflow_run / get_workflow_run_traces). An AUTOMATIC fire is stored as a diagnosis, not an archive: its status, message, failing step and a head of each captured value are kept, but the output is sampled (output_truncated) and large trace values are shortened. Use run_schedule_now to capture a firing in full.

Input Schema

TableJSON Schema

Name	Required	Description
`page_size`	No	maximum number of runs to return in this page
`page_token`	No	token from a previous response's next_page_token to fetch the next page
`schedule_id`	Yes	the schedule id whose run history to list

Output Schema

TableJSON Schema

Name	Required	Description	Default
`runs`	Yes
`next_page_token`	Yes

Schema Changelog

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

First observedSep 7, 2026

TDQS

A4.7/5.0

Behavior5/5

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

Beyond the readOnlyHint and destructiveHint annotations, the description discloses important behavior: results are newest-first, items are thin references rather than full runs, automatic fires are stored as diagnoses, outputs are sampled/truncated, and large trace values are shortened. This is exactly the kind of behavioral context an agent needs to interpret results correctly.

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 compact and front-loaded with the core purpose, followed by essential behavioral caveats and a pointer to the alternative tool. Each sentence adds distinct value: scope, reference semantics, truncation behavior, and full-capture guidance.

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 that an output schema is present, the description does not need to restate return fields. It explains the crucial semantics not visible in the schema: ordering, thin-reference nature, diagnostic storage for automatic fires, output sampling, and how to obtain fuller data. An agent has enough context to correctly invoke and interpret this tool.

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 all three parameters are already documented in the input schema. The tool description adds no additional parameter-level meaning, which is acceptable but does not exceed the baseline expected when the schema fully covers parameters.

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 verb and resource: listing a schedule's fire history, newest-first. It clearly distinguishes this tool from related siblings by scoping it to schedule fire history rather than generic run listing, and by contrasting it with run_schedule_now for full capture.

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 explicit guidance on when to use related tools: resolve run details with get_workflow_run/get_workflow_run_traces, and use run_schedule_now when a full firing capture is needed. This tells an agent not only what this tool does, but how to proceed after calling it and which alternative to choose for richer data.

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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