Rolli MCP

list_agent_schedules

List scheduled reports for Rolli Agents to review daily, weekly, monthly, or one-time cadences and paginate results.

Instructions

List Rolli Agent scheduled reports. Schedules execute on a daily/weekly/monthly/once cadence and produce a new agent run each time.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_agent_schedules"
  }
}

Input Schema

Name	Required	Description	Default
`limit`	No	Page size (default: 50, max: 100)
`offset`	No	Pagination offset (default: 0)

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedv1.5.0Nov 4, 2026
- removedInput schema / additionalProperties
```
Removed value: -false
```
- addedInput schema / properties / offset / maximum
```
Added value: +9007199254740991
```
Addedv1.3.0Jun 3, 2026

TDQS

B3.2/5.0

Behavior3/5

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

With no annotations present, the description carries the full burden, but it does usefully disclose the cadence model (daily/weekly/monthly/once) and that each schedule execution spawns a new agent run. It omits behavior an agent would want: whether paused or deleted schedules are included, ordering, and whether the response is a bare array or wrapped.

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?

Two short sentences, front-loaded with the action and resource, with the second sentence supplying genuinely useful domain context rather than filler. Nothing is redundant with the schema.

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

Completeness3/5

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

For a simple read-only listing with two optional pagination parameters and no output schema, the description covers purpose and domain semantics adequately. It falls short on what a returned schedule contains and whether filtering by status is possible, which an agent must discover empirically.

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%, with limit and offset documented inline including defaults and maxima, so the description need not restate them. It adds no extra meaning about pagination strategy or how many schedules typically exist, which is the correct baseline for a fully documented two-parameter schema.

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 gives a specific verb and resource ("List Rolli Agent scheduled reports") and clarifies what a schedule is (a recurring job producing agent runs). It does not distinguish this from siblings like get_agent_schedule or list_agent_schedule_runs, so the agent must infer the boundary from names alone.

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

Usage Guidelines2/5

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

There is no explicit when-to-use guidance, no mention of when not to use it, and no routing to alternatives such as get_agent_schedule (single schedule) or list_agent_schedule_runs (executions). The only cue is the word "List", which implies enumeration but leaves selection up to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.