Opsgenie is an incident response control plane, so letting an enterprise agent touch it without hard controls is a fast way to create missed pages, noisy escalations, or tampered timelines. With Claw EA, you run the agent on the OpenClaw baseline runtime and connect Opsgenie via official API with enterprise buildout controls, then gate every write or admin-like action behind policy-as-code.
Prompt-only guardrails are not enough because the model can be induced to “do the right thing” for the wrong reason under pressure, ambiguity, or prompt injection. A permissioned execution layer uses a WPC = Work Policy Contract (signed, hash-addressed policy artifact; served by clawcontrols) and CST = scoped token (issued by clawscope) so the agent cannot exceed an explicitly approved action surface, even if the prompt asks it to.
Step-by-step runbook
Use this to set up a permissioned Opsgenie tool for agents that triage and assist, without giving them free rein. This assumes you will integrate via Opsgenie’s official API using OAuth, API key, or a service account, based on your enterprise requirements.
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Define the minimum job to automate. Start with read-only triage: list current alerts, fetch alert details, and post an internal summary elsewhere. Only add write operations (acknowledge, add note, close) after you have an approval story and on-call owner buy-in.
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Write a WPC for Opsgenie actions. Specify allowed operations, which teams or services are in scope, time bounds, and required approval gates for any state-changing operation. Publish the WPC to the WPC registry so it can be fetched and verified during runs.
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Issue a CST pinned to the policy. Use clawscope to issue a CST whose scope hash matches the intended tool permissions, with optional policy hash pinning to the WPC. Bind the CST to a single job to reduce replay risk.
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Run the agent with tool policy enforced in OpenClaw. In OpenClaw, allow only the Opsgenie tool and the minimum supporting tools (for example, HTTP client plus structured logging), and keep the rest denied. If you enable sandboxing, keep binds and workspace access minimal so an injected prompt cannot easily reach secrets or host resources.
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Route model calls through clawproxy. When the agent calls its model provider, route those calls through clawproxy so you get Gateway receipts = signed receipts emitted by clawproxy for model calls. This makes the model interaction auditable alongside the tool actions it caused.
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Require explicit approvals for risky writes. For example, closing an alert or changing priority should require a WPC approval gate that checks the requested change, the target team, and the current incident context. If the gate fails, the agent should fall back to drafting a recommendation instead of executing.
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Export the Proof bundle after each run. Store the Proof bundle (harness artifact bundling receipts and related metadata for audit/verification) with the incident record or your internal ticket, and optionally publish a Trust Pulse for easy viewing during post-incident review.
Threat model
Opsgenie is high impact because small write actions can change who gets paged and what evidence exists later. The table below lists common failure modes for agent-based Opsgenie automation and how to contain them with permissioned execution.
| Threat | What happens | Control |
|---|---|---|
| Prompt injection causes alert suppression | The agent is tricked into closing or downgrading alerts to reduce noise, creating a silent failure during an incident. | WPC restricts “close” and “priority change” to approval-gated operations; CST is pinned to that WPC so the tool cannot execute unapproved writes. |
| Mis-scoped credentials allow broad org changes | A token with overly broad privileges can mutate teams, schedules, routing rules, or escalation policies if the agent or plugin is compromised. | Least-privilege auth scopes and separate service accounts; WPC denies admin category operations; OpenClaw tool allow/deny prevents loading unrelated tools that could exfiltrate credentials. |
| Replay of a prior “ack” or “close” request | An attacker reuses an old authorization artifact to repeat a sensitive action against a different alert or at a later time. | Marketplace anti-replay binding using job-scoped CST binding; short CST TTLs; WPC includes tight time and resource constraints. |
| Model hallucination routes action to wrong team | The agent posts notes, acknowledges, or escalates on the wrong alert or wrong service based on partial context. | WPC includes allowlisted team/service identifiers; approvals required when the target is not confidently in scope; require tool-side validation of IDs before write. |
| Audit gaps during incident review | You cannot prove what the model saw or why an Opsgenie change happened, so postmortems become opinion-based. | Route model calls through clawproxy for Gateway receipts; export a Proof bundle per run; store or share via Trust Pulse for consistent viewing. |
Policy-as-code example
This is a JSON-like sketch of a WPC that allows read access and tightly gates a small set of write operations. Keep it concrete: enumerate operations, scope the resources, and add explicit approval requirements for state-changing actions.
{
"tool": "opsgenie",
"connection": { "mode": "official_api", "auth": ["oauth", "api_key", "service_account"] },
"allow": [
{ "op": "alerts.list", "filters": { "teams": ["oncall-platform"], "status": ["open", "acknowledged"] } },
{ "op": "alerts.get", "resource": { "team": "oncall-platform" } },
{ "op": "alerts.notes.add", "resource": { "team": "oncall-platform" } }
],
"gated": [
{
"op": "alerts.acknowledge",
"requires": { "approval": "oncall_primary", "reason": "must reference current incident channel or ticket" }
},
{
"op": "alerts.close",
"requires": { "approval": "incident_commander", "reason": "must include resolution summary and link" }
}
],
"deny": [
{ "op": "schedules.*" },
{ "op": "teams.*" },
{ "op": "escalations.*" },
{ "op": "integrations.*" }
],
"token": {
"cst": {
"ttl_minutes": 30,
"scope_hash": "derived_from_allow_gated_deny",
"policy_hash_pinning": "enabled"
}
},
"audit": { "require_proof_bundle": true }
}
The important part is that the policy is enforceable outside the prompt. Even if the model outputs “close the alert now,” the tool call will be blocked unless the WPC gates are satisfied and the CST is valid for that exact scope.
What proof do you get?
For each run, Claw EA can produce a Proof bundle that includes the run metadata and the verification material needed for audit. When model calls are routed through clawproxy, you also receive Gateway receipts for those calls, so reviewers can see what the model was asked and what it returned, tied to the job context.
Operationally, you use this proof to answer questions like: which WPC was in force, which CST authorized the tool calls, which model interactions occurred, and whether the run was bound to a single job (anti-replay). If you store the artifact in Trust Pulse, you get a consistent viewer for audits and incident postmortems.
Rollback posture
When an agent run goes wrong in Opsgenie, you need rollback that is fast and has clear evidence. The goal is to stop further writes first, then correct state in Opsgenie, then preserve a defensible record of what happened.
| Action | Safe rollback | Evidence |
|---|---|---|
| Stop the agent from writing to Opsgenie | Revoke the CST and rotate the underlying Opsgenie credential (API key or OAuth grant). Disable the Opsgenie tool in OpenClaw tool policy until review completes. | CST issuance and revocation history; OpenClaw configuration change record; Proof bundle for the offending run. |
| Prevent recurrence of the same class of action | Update the WPC to deny or gate the operation and require policy hash pinning so older tokens cannot keep using the old policy. | WPC hash and signature; run logs showing which WPC hash was enforced; job-scoped CST binding signals. |
| Reconstruct what the model influenced | Review the Proof bundle and correlate tool calls with the incident timeline. If needed, run the same inputs in a non-writing “dry-run” mode for analysis. | Gateway receipts for model calls; Proof bundle metadata; Opsgenie audit trail and timestamps. |
| Repair incident state | Manually correct the affected alerts (re-open, re-assign, re-escalate) using standard on-call procedures. Treat repair as a human-owned change, not an agent follow-up, until controls are revalidated. | Opsgenie change history plus the internal postmortem reference to the Proof bundle. |
FAQ
Is this a native Opsgenie connector in Claw EA today?
No. Opsgenie can be connected via official API with enterprise buildout controls, and you should treat it as an integration you harden and validate before production use.
Why is prompt-only control not sufficient for Opsgenie?
Because prompts do not enforce privileges. A permissioned execution layer blocks the actual tool call unless the WPC allows it and the CST is scoped correctly, even when the model is coerced or confused.
What should agents be allowed to do first in Opsgenie?
Start with read-only listing and retrieval, plus drafting notes for a human to post. Add acknowledge and close only after you have approval gates and clear ownership of on-call risk.
How do you audit what the model did versus what the tool did?
Route model traffic through clawproxy to get Gateway receipts for model calls, and package them with run metadata into a Proof bundle. Reviewers can then correlate model outputs to the exact Opsgenie tool actions that were authorized.
Can we enforce network egress allowlists for the agent?
Egress allowlists enforced outside clawproxy are optional and can be implemented, depending on your deployment. Even with egress controls, you still want WPC and CST enforcement so permissions are correct at the execution layer.