This record as markdown: /tools/io-github-kivanccakmak-yaver/jobs-retry.md
What jobs_retry does on Yaver
AI agents invoke jobs_retry 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 |
|---|---|---|---|
id | string | Yes |
Parameters from the server's own tool schema.
Why jobs_retry is rated High
Retrying/requeueing a dead-letter queue job triggers re-execution of a previously failed job. This is an operational action that causes external side effects (running the job again), placing it in the Execute category. Severity is medium because misuse could cause unintended job executions, but it's limited to reprocessing already-queued work.
From the tool's definition Requeue a DLQ job
Attacks that exploit this kind of access
The rule that runs jobs_retry 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 jobs_retry, this is the rule to start with:
jobs_retry 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 jobs_retry call is checked against it from then on.
Questions about jobs_retry
Requeue a DLQ job. 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.
jobs_retry accepts 1 parameter: id. Required: id. 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 jobs_retry: 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.
jobs_retry 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 jobs_retry 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 jobs_retry. 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.
jobs_retry 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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