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rnd-pro
by rnd-pro

schedule_task

Schedule CLI agents to run on cron timers or as delayed tasks. Results persist and are retrievable.

Instructions

Schedule a CLI agent to run on a cron schedule or as a delayed one-shot. Default provider: Codex CLI. Spawns a persistent daemon that survives IDE/CLI restarts. Results are saved in local portal project state and can be retrieved with get_scheduled_results.

Cron format: standard 5-field (minute hour day month weekday). Examples: "*/30 * * * *" (every 30 min), "0 9 * * MON-FRI" (9am weekdays), "0 */2 * * *" (every 2 hours).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cwdNoWorking directory for the scheduled task. Defaults to current directory.
cronYesCron expression (5-field). E.g. "0 9 * * *" for daily at 9am.
modelNoModel to use. Leave empty for provider default.
skillNoSkill to activate for each run.
promptYesTask prompt for the CLI agent.
catchupNoIf true, run missed schedules on daemon restart. Default: false (skip missed).
providerNoCLI provider for scheduled runs. Default: codex.
serviceTierNoService tier for Codex. Codex maps to service_tier.
approval_modeNoApproval mode for scheduled runs. Default: yolo.
reasoningEffortNoProvider reasoning effort. Codex accepts the selected model value and maps it to model_reasoning_effort. Claude Code accepts low, medium, high, xhigh, or max and maps it to --effort.
Behavior3/5

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

Without annotations, description covers daemon persistence and result storage. But it lacks details on permissions, resource implications, or side effects of scheduling autonomous tasks. Adequate but not comprehensive.

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?

Five sentences efficiently convey core purpose, behavior, and examples. No redundancy. Slight room for improvement by front-loading the most critical information, but overall well-structured.

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?

With 10 parameters and no output schema, the description covers main functionality but omits return value (e.g., schedule ID) and does not explain 'delayed one-shot' fully. Some advanced parameters like catchup, serviceTier, reasoningEffort are not addressed.

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 covers all parameters (100% coverage), so baseline is 3. Description adds value with cron format guidance, provider defaults, and some mapping details (e.g., model to service_tier).

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?

Description clearly states the verb 'schedule', resource 'CLI agent', and schedule type 'cron or delayed one-shot'. It also specifies the default provider, distinguishing it from siblings like cancel_schedule and get_scheduled_results.

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

Usage Guidelines4/5

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

Description explains when to use the tool (to schedule tasks) and provides cron format examples. However, it does not explicitly state when not to use it or suggest alternatives, though the context of siblings is informative.

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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