util_seeded_schedule_offset
Seeded Schedule Offset selects a reproducible offset inside a scheduling window from bounded caller-supplied values without an external provider. Call Seeded Schedule Offset when an agent needs a reproducible decision that another run can independently replay. Returns the deterministic selection ...
This record as markdown: /tools/io-github-davidmosiah-delx-protocol/util-seeded-schedule-offset.md
What util_seeded_schedule_offset does on Delx Protocol — Agent Recovery & Continuity
AI agents use util_seeded_schedule_offset to create or update resources in Delx Protocol — Agent Recovery & Continuity, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Delx Protocol — Agent Recovery & Continuity environment.
| Parameter | Type | Required | Description |
|---|---|---|---|
seed | string | Yes | Seed supplied to Seeded Schedule Offset; used only for this bounded calculation and processed in memory without retention. |
window_seconds | integer | Yes | Window Seconds supplied to Seeded Schedule Offset; used only for this bounded calculation and processed in memory without retention. |
Parameters from the server's own tool schema.
Why util_seeded_schedule_offset is rated Medium
An AI agent can call util_seeded_schedule_offset faster than any human can review: one bad instruction and it creates or modifies resources in Delx Protocol — Agent Recovery & Continuity by the hundred, each call as confident as the last.
Attacks that exploit this kind of access
The rule that runs util_seeded_schedule_offset safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Delx Protocol — Agent Recovery & Continuity, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For util_seeded_schedule_offset, this is the rule to start with:
util_seeded_schedule_offset stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Delx Protocol — Agent Recovery & Continuity, apply this rule, and every util_seeded_schedule_offset call is checked against it from then on.
Questions about util_seeded_schedule_offset
Seeded Schedule Offset selects a reproducible offset inside a scheduling window from bounded caller-supplied values without an external provider. Call Seeded Schedule Offset when an agent needs a reproducible decision that another run can independently replay. Returns the deterministic selection plus seed provenance, population bounds, and the operation-specific outcome for Seeded Schedule Offset as versioned deterministic JSON. Limitation: Uses Python pseudorandomness for reproducibility, not cryptography, lotteries with value, security tokens, gambling, or custody. It is categorised as a Write tool in the Delx Protocol — Agent Recovery & Continuity MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
util_seeded_schedule_offset accepts 2 parameters: seed, window_seconds. Required: seed, window_seconds. The full parameter table on this page comes from the server's own tool schema.
Register the Delx Protocol — Agent Recovery & Continuity MCP server in PolicyLayer and add a rule for util_seeded_schedule_offset: 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 Delx Protocol — Agent Recovery & Continuity. Nothing to install.
util_seeded_schedule_offset is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the util_seeded_schedule_offset 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 util_seeded_schedule_offset. 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.
util_seeded_schedule_offset is provided by the Delx Protocol — Agent Recovery & Continuity MCP server (https://api.delx.ai/v1/mcp?src=registry). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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