util_seeded_backoff_schedule
Seeded Backoff Schedule builds a reproducible jittered exponential backoff schedule from bounded caller-supplied values without an external provider. Call Seeded Backoff Schedule when an agent needs a reproducible decision that another run can independently replay. Returns the deterministic selec...
This record as markdown: /tools/io-github-davidmosiah-delx-mcp-a2a/util-seeded-backoff-schedule.md
What util_seeded_backoff_schedule does on Delx Mcp A2a
AI agents use util_seeded_backoff_schedule 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.
| Parameter | Type | Required | Description |
|---|---|---|---|
seed | string | Yes | Seed supplied to Seeded Backoff Schedule; used only for this bounded calculation and processed in memory without retention. |
factor | number | Yes | Factor supplied to Seeded Backoff Schedule; used only for this bounded calculation and processed in memory without retention. |
base_ms | integer | Yes | Base Ms supplied to Seeded Backoff Schedule; used only for this bounded calculation and processed in memory without retention. |
attempts | integer | Yes | Attempts supplied to Seeded Backoff Schedule; used only for this bounded calculation and processed in memory without retention. |
jitter_fraction | number | Yes | Jitter Fraction supplied to Seeded Backoff Schedule; used only for this bounded calculation and processed in memory without retention. |
Parameters from the server's own tool schema.
Why util_seeded_backoff_schedule is rated Medium
An AI agent can call util_seeded_backoff_schedule 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.
Attacks that exploit this kind of access
The rule that runs util_seeded_backoff_schedule safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Delx Mcp A2a, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For util_seeded_backoff_schedule, this is the rule to start with:
util_seeded_backoff_schedule 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 Mcp A2a, apply this rule, and every util_seeded_backoff_schedule call is checked against it from then on.
Questions about util_seeded_backoff_schedule
Seeded Backoff Schedule builds a reproducible jittered exponential backoff schedule from bounded caller-supplied values without an external provider. Call Seeded Backoff Schedule 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 Backoff Schedule 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.
util_seeded_backoff_schedule accepts 5 parameters: seed, factor, base_ms, attempts, jitter_fraction. Required: seed, factor, base_ms, attempts, jitter_fraction. The full parameter table on this page comes from the server's own tool schema.
Register the Delx Mcp A2a MCP server in PolicyLayer and add a rule for util_seeded_backoff_schedule: 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.
util_seeded_backoff_schedule 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_backoff_schedule 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_backoff_schedule. 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_backoff_schedule 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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