update_external_job
[SUPPORT] Record a new observation for an existing external job. Use job_id or job_key, and pass only fields that changed; every write appends durable history and refreshes the local crash-surviving snapshot. Terminal jobs cannot be reopened or silently replaced. Persistent-state disclosure: on h...
This record as markdown: /tools/io-github-ajc3xc-meridian/update-external-job.md
What update_external_job does on Meridian
AI agents use update_external_job to create or update resources in Meridian, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Meridian environment.
| Parameter | Type | Required | Description |
|---|---|---|---|
phase | string | — | |
detail | string | — | |
job_id | string | — | |
status | string | — | |
job_key | string | — | |
metadata | object | — | |
check_hint | string | — | |
project_id | string | — | |
session_id | string | Yes | |
resume_hint | string | — | |
project_name | string | — | Project name — an alternative to project_id; resolved to the id internally. project_id wins if both are given. |
next_check_at | string | — |
Parameters from the server's own tool schema.
Why update_external_job is rated Medium
An AI agent can call update_external_job faster than any human can review: one bad instruction and it creates or modifies resources in Meridian by the hundred, each call as confident as the last.
Risk signalsHigh parameter count (13 properties) · Bulk/mass operation — affects multiple targets
Attacks that exploit this kind of access
The rule that runs update_external_job safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Meridian, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For update_external_job, this is the rule to start with:
update_external_job 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 Meridian, apply this rule, and every update_external_job call is checked against it from then on.
Questions about update_external_job
[SUPPORT] Record a new observation for an existing external job. Use job_id or job_key, and pass only fields that changed; every write appends durable history and refreshes the local crash-surviving snapshot. Terminal jobs cannot be reopened or silently replaced. Persistent-state disclosure: on hosted Meridian, supplied text and project/session metadata -- including task log entries, pinned decisions, sprint items, notes, handoff/goal state, and HITL queue items -- are sent to and stored in Meridian's service, in an isolated per-tenant Postgres database (Neon); self-hosted deployments keep the same categories in the configured local SQLite/Postgres database. This data is visible in the dashboard and API, and may resurface in later project context or handoffs. Notes and pinned decisions can be deleted individually; task log entries and sprint items can be deleted via the dashboard/API (not exposed as an agent-facing tool); HITL queue items and handoff state have no per-record delete. Full removal of any of this data is available via project or account deletion, using the documented controls. Do not include secrets. It is categorised as a Write tool in the Meridian MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
update_external_job accepts 12 parameters: phase, detail, job_id, status, job_key, metadata, check_hint, project_id, session_id, resume_hint, project_name, next_check_at. Required: session_id. The full parameter table on this page comes from the server's own tool schema.
Register the Meridian MCP server in PolicyLayer and add a rule for update_external_job: 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 Meridian. Nothing to install.
update_external_job 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 update_external_job 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 update_external_job. 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.
update_external_job is provided by the Meridian MCP server (@meridianmcp/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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