schedule_self
Schedule a CONTINUATION of your own work to run later — the way to handle recurring or deferred tasks instead of looping in-process or busy-waiting. Pick exactly one cadence: when (one-shot RFC3339 UTC), interval_minutes (every N minutes), or cron (5-field expr; supports */N steps and @daily/@hou...
This record as markdown: /tools/io-github-kivanccakmak-yaver/schedule-self.md
What schedule_self does on Yaver
AI agents invoke schedule_self to trigger actions in Yaver. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
| Parameter | Type | Required | Description |
|---|---|---|---|
cron | string | — | 5-field cron expression (minute hour day month weekday), e.g. '*/30 * * * *' or '@daily'. Use this OR when OR interval_minutes. |
memo | string | — | Optional notes carried verbatim into the next run's prompt (state, findings, where you left off). |
when | string | — | One-shot run time, RFC3339 UTC (e.g. 2026-06-17T09:00:00Z). Use this OR interval_minutes OR cron. |
model | string | — | Optional model override for the next run. |
title | string | — | Optional label. Defaults to a truncation of prompt. |
prompt | string | Yes | The instruction the next run executes. Self-contained — the next process has no memory of the current turn. |
resume | boolean | — | Recurring only: natively resume the previous run's session each fire (claude/glm/codex by session id, opencode by --continue) instead of starting cold. Default |
runner | string | — | Runner for the next run: claude | codex | opencode | glm. Defaults to this agent's default runner. |
max_runs | integer | — | Stop after this many fires (0 = use the 100-fire safety cap for recurring; one-shot ignores this). |
interval_minutes | integer | — | Repeat every N minutes (minimum 1). Use this OR when OR cron. |
Parameters from the server's own tool schema.
Why schedule_self is rated High
This tool schedules future execution of agent processes — potentially recurring indefinitely via cron or interval. It triggers external operations (fresh process launches) whose effects depend on the prompt/memo arguments passed. An AI agent misusing this tool could create runaway recurring tasks, spawn unintended processes, or cause cascading downstream actions, making it high severity in the Execute category.
From the tool's definition 'Schedule a CONTINUATION of your own work to run later', 'next run starts as a FRESH process', supports 'interval_minutes' (every N minutes) or 'cron' (5-field expr)'
Risk signalsHigh parameter count (10 properties) · Bulk/mass operation — affects multiple targets
Attacks that exploit this kind of access
The rule that runs schedule_self safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Yaver, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For schedule_self, this is the rule to start with:
schedule_self stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Yaver, apply this rule, and every schedule_self call is checked against it from then on.
Questions about schedule_self
Schedule a CONTINUATION of your own work to run later — the way to handle recurring or deferred tasks instead of looping in-process or busy-waiting. Pick exactly one cadence: when (one-shot RFC3339 UTC), interval_minutes (every N minutes), or cron (5-field expr; supports */N steps and @daily/@hourly macros). The next run starts as a FRESH process (no memory of this turn) so put everything it needs into prompt and memo. memo is carried verbatim into the next run's prompt. runner defaults to this agent's default; pass it to pin claude/codex/opencode/glm. Recurring schedules without max_runs are capped at 100 fires. It is categorised as a Execute tool in the Yaver MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
schedule_self accepts 10 parameters: cron, memo, when, model, title, prompt, resume, runner, max_runs, interval_minutes. Required: prompt. The full parameter table on this page comes from the server's own tool schema.
Register the Yaver MCP server in PolicyLayer and add a rule for schedule_self: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Yaver. Nothing to install.
schedule_self is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the schedule_self rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for schedule_self. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
schedule_self is provided by the Yaver MCP server (yaver-cli). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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