Surgically edit a pending approval timeline's eventContent or metadata fields without rerunning the upstream step. EXCEPTION-ONLY tool. Use cases: - Fix a malformed email.to / subject / body in a pending email-draft step (no need to re-run the LLM) - Update metadata.pendingReasonTag for UI annota...
Risk signalsAccepts file system path (patches[].path) · High parameter count (11 properties) · Admin/system-level operation
Part of the Agentled server.
Free to start. No card required.
AI agents use patch_timeline_fields to create or modify resources in Agentled. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.
Without a policy, an AI agent could call patch_timeline_fields repeatedly, creating or modifying resources faster than any human could review. PolicyLayer's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Agentled.
Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.
{
"version": "1",
"default": "deny",
"tools": {
"patch_timeline_fields": {
"limits": [
{
"counter": "patch_timeline_fields_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}See the full Agentled policy for all 119 tools.
These attack patterns abuse exactly the kind of access patch_timeline_fields gives an agent. Each links to the full case and the policy that stops it:
Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.
Surgically edit a pending approval timeline's eventContent or metadata fields without rerunning the upstream step. EXCEPTION-ONLY tool. Use cases: - Fix a malformed email.to / subject / body in a pending email-draft step (no need to re-run the LLM) - Update metadata.pendingReasonTag for UI annotation - Recover a failed timeline back to pending (status transition: failed → pending) DO NOT use for day-to-day data fixes — most edits should happen by re-running the step or updating the workflow definition. This tool exists for incident response, not regular workflow operation. Required: - API key with admin:patch scope (Stage 2 — without it returns 403 FORBIDDEN_SCOPE) - reason: non-empty string (≤500 chars), persisted in the audit row - expectedUpdatedAt: timeline.updatedAt from a fresh read — guards against lost-update races Allowed paths (status === 'pending'): - eventContent (wholesale replace; reserved keys _* rejected) - eventContent.email.subject | body | bodyType | to | cc | bcc - eventContent.<any> (any AI-output field, except _*-prefixed reserved keys) - metadata.pendingReasonTag - status (only failed → pending) Forbidden: - Any path containing an underscore-prefixed segment (_timelineId, _metadata, _pointer, _continuation, etc. — runtime-internal markers) - Any write to a completed/approved/rejected timeline - Identity fields, provider send results, audit fields Returns: { patched, dryRun, auditId, diff: [{path, before, after}], record } On error: { error, code, path? } — codes: FORBIDDEN_SCOPE | FORBIDDEN_PATH | FORBIDDEN_TRANSITION | INVALID_VALUE | NOT_FOUND | CONCURRENCY_CONFLICT | STATUS_MISMATCH | PRECONDITION_FAILED. It is categorised as a Write tool in the Agentled MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Agentled MCP server in PolicyLayer and add a rule for patch_timeline_fields: 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 Agentled. Nothing to install.
patch_timeline_fields 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 patch_timeline_fields 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 patch_timeline_fields. 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.
patch_timeline_fields is provided by the Agentled MCP server (@agentled/mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 119 Agentled tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
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