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Nerdit

Official
by nerdit-ai
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Python
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list_schedule_runs

Retrieve the latest runs for a deployed app's schedule, newest first, including trigger, timing, outcome, and status details. Use it to check execution history and troubleshoot scheduled jobs.

Instructions

A schedule's runs, newest first (50 are kept).

    Each run is ``{run_id, trigger, started_at, finished_at, outcome,
    status_code}``. ``trigger``: ``cron`` | ``manual`` | ``catchup``.
    ``outcome``: ``running``, ``accepted`` (202), ``ok`` (other 2xx),
    ``failed`` (any other status), ``timeout``, ``unreachable`` (no
    connection) or ``skipped_overlap``. The app's response body is never kept.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "name": "<name>",
      "schedule_name": "<schedule_name>"
    },
    "name": "list_schedule_runs"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameYesName (or row id) of an existing deployed app — only kind 'service' can be exposed: ``share_service``/``add_domain`` refuse a model or database with 422 ``*.kind_unsupported``, while the remove tools just find nothing to undo.
limitNoRuns to return (1-50).
schedule_nameYesSchedule name: lowercase letters, digits and '-', 1-32 characters, starting with a letter (e.g. ``morning``); the app receives it as ``X-Nerdit-Schedule``.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.9.3

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does substantial work: it discloses ordering, a hard retention cap of 50 runs, the exact record shape, the meaning of every trigger and outcome value (including the HTTP-status mapping for accepted/ok/failed), and the important limitation that response bodies are never stored. It stops short of stating read-only behavior explicitly, error behavior, or whether retention is global or per-schedule.

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?

Front-loaded with the core fact plus ordering and retention, then a compact field/enum reference. Dense but every clause is load-bearing for interpreting results; the only mild cost is that the enum explanation reads as a block of prose rather than structured text.

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?

There is no output schema, so the description must explain return values — and it does, field by field, including enum semantics and the absence of response bodies. For a three-parameter read tool whose only realistic output is this record shape, nothing an agent needs in order to call or interpret it is missing.

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 explains name, schedule_name and limit. The description adds no parameter-level detail of its own; the only cross-over is '50 are kept', which indirectly justifies the limit maximum of 50.

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 names the resource precisely — the runs of one named schedule — and adds scope qualifiers (newest first, only the last 50 retained), which distinguishes it from list_schedules (schedules themselves) and run_schedule (triggering one). It is a noun phrase rather than an explicit verb, but the intent is unambiguous.

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?

Usage is only implied: an agent can infer this is the tool for inspecting execution history rather than triggering or managing schedules. There is no explicit statement of when to prefer it over siblings, no prerequisites, and no note on what happens if the schedule name does not exist.

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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