Honeycomb Alert Scribe with Hermes
The work is mechanical in a way that suits an open model well: read a trigger, rerun its query across the alert window, rerun it grouped, then report the threshold against the value you measured and the two or three groups holding most of it. There is nobody to persuade and no cause to reason about. Hermes covers that comfortably with your Honeycomb and Slack credentials wired in.
Watch it work before it's live
Run a staged conversation — no account needed. The agent handles it for real while a simulated world answers its tool calls; nothing touches real accounts, and nothing is actually sent.
checkout p99 over 800ms
The trigger evaluates P99(duration_ms) over five minutes against a threshold of 800. The evaluation that fired returned 2,140 at 14:07 UTC, against 310 at 13:30. The trigger has no group by of its own. The dataset carries service.name, http.route, tenant_id and app.cache_hit.
Set up in minutes
Using this template drops you into a guided setup. It asks exactly this, nothing else:
Connect Honeycomb
One sign-in. The agent acts through your account, scoped to what this template uses.
Connect Slack
One sign-in. The agent acts through your account, scoped to what this template uses.
Triage notes
How you want a fired trigger written up - the field worth grouping by in each dataset, the triggers you already know are noisy, plus the opening move you expect on a latency alert, on an error rate alert, and on a query that comes back with nothing in it.
Runs on Hermes
Preselected for this page — connect your Hermes account during setup, or switch to NoClick's built-in models with one click.
Watch it handle a test run
A staged conversation against a simulated world — then it’s live.
Why Hermes for this agent
Retrieval with a little arithmetic
Value against threshold, then each leading group with its own value and its share of the total. Nothing in that asks for the top of any model's range.
Nothing persuasive to write
The note has no argument to make, which removes the register where open models most often wobble. It reports, and the first check comes out of your own triage notes.
Before you fork
How do we check the breakdown is genuinely right?
Open the Test Run that carries the latency alert against a dataset with service, route and tenant fields, then run the same grouped query by hand in Honeycomb and hold the two side by side. Two of those is usually enough to tell whether the field named in your triage notes is the one worth grouping by.
Run it with a different agent
Put Honeycomb Alert Scribe to work on Hermes
Free to start. Guided setup, a test run against staged conversations, and it's live.