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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 ...

SERVERDelx Mcp A2a SOURCEhttps://api.delx.ai/v1/mcp
Medium RISK CLASS
Category Write
Parameters 22 required
Recommended Rate-limitedsee the rule below
Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/io-github-davidmosiah-delx-mcp-a2a/util-seeded-schedule-offset.md

What util_seeded_schedule_offset does on Delx Mcp A2a

AI agents use util_seeded_schedule_offset to create or update resources in Delx Mcp A2a, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Delx Mcp A2a environment.

ParameterTypeRequiredDescription
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 Mcp A2a by the hundred, each call as confident as the last.

Questions about util_seeded_schedule_offset

What does the util_seeded_schedule_offset tool do? +

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 Mcp A2a MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

What parameters does util_seeded_schedule_offset accept? +

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.

How do I enforce a policy on util_seeded_schedule_offset? +

Register the Delx Mcp A2a 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 Mcp A2a. Nothing to install.

What risk level is util_seeded_schedule_offset? +

util_seeded_schedule_offset is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit util_seeded_schedule_offset? +

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.

How do I block util_seeded_schedule_offset completely? +

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.

What MCP server provides util_seeded_schedule_offset? +

util_seeded_schedule_offset is provided by the Delx Mcp A2a MCP server (https://api.delx.ai/v1/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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