# Hermes on Atlas: operator guide

This is the mental model and demonstration script for the operator instance at
`triage.hermes.bstein.dev`. Read it once, then prove each section in the live UI. The
consumer instance at `chat.hermes.bstein.dev` is intentionally separate and is not the
place to perform infrastructure triage.

## Consumer chat and Telegram

`chat.hermes.bstein.dev` uses the pinned Hermes WebUI rather than the operator
dashboard. Keycloak still authenticates every browser request, and the tenant
router permanently assigns each Keycloak subject to one Hermes process and one
PVC. The four slots are an isolation pool, not a provider round robin: every
user starts with the same automatic provider/fallback policy and may change the
model or reasoning effort for their own conversation. The WebUI and API reject
reasoning levels above `xhigh`.

Telegram is optional. The Keycloak bootstrap creates
`kv/atlas/hermes/chat-telegram` with a generated relay key and an empty
`bot_token`. After creating the shared bot with BotFather, set only that field:

```sh
vault kv patch kv/atlas/hermes/chat-telegram bot_token='<telegram bot token>'
```

Restart or reconcile `hermes-chat-router` after changing the token. A user then
signs in to the WebUI, selects `Telegram`, creates a ten-minute code, and sends
the displayed `/link` command to the bot. The router accepts only direct chats,
stores hashed Keycloak and Telegram identities, and forwards the message to
that user's tenant API with the shared relay key. `/unlink` works from Telegram
or the WebUI. Browser chat remains available when `bot_token` is empty.

The bot token and relay key must never be added to Git or a Kubernetes Secret.
The router does not log prompt bodies, raw Telegram IDs, link codes, or tokens.

## The one-sentence explanation

Hermes is the persistent agent runtime and control surface; Codex or the local
GPU model supplies reasoning, while Hermes supplies sessions, tools, skills,
approval rules, identity, and the repeatable procedure that connects the model
to Atlas evidence.

Hermes is not the model. Replacing `gpt-5.6-terra` with `gpt-oss:20b` changes the
reasoning engine, but it does not replace the Hermes sessions, tools, skills,
files, permission boundary, or workflow.

## Request and evidence path

```text
browser
  -> Keycloak login
  -> oauth2-proxy exact-user check
  -> operator Hermes pod and persistent workspace
  -> SOUL.md + AGENTS.md + selected skill
  -> Codex primary model
       -> read-only terminal/web/file tools
       -> Ariadne deterministic evidence
       -> retained Jenkins logs and artifacts
       -> Gitea commits and Flux state
       -> Kubernetes workloads, events, logs, and dependencies
       -> Pushgateway data queried through VictoriaMetrics
       -> Grafana query and alert context
  -> structured finding and proposed repo-side change
  -> human review and approval
  -> Git/Flux delivery outside Hermes

provider failure
  -> hermes-model-gate
       -> Hermes owns titan-24: Ollama serves gpt-oss:20b
       -> Wolf owns titan-24: gate returns 503; local inference yields
```

The operator agent pod runs on an ARM worker and does not reserve the GPU.
Ollama is the component on `titan-24` that owns GPU memory. The Lease
`hermes/titan-24-gpu-owner` controls whether the model gate admits local
inference. Normal operator conversations use independently authenticated Codex
first, so Wolf ownership does not need to block the web agent.

## Who does what

| Component | Responsibility | What it does not prove |
| --- | --- | --- |
| Hermes | Maintains the conversation, chooses tools/skills, reasons over evidence, saves reports, and enforces the approval experience | It is not the inference model and does not automatically have cluster-admin access |
| Ariadne | Collects and normalizes deterministic cluster, Jenkins, and quality evidence into a timestamped bundle; may optionally run a local diagnosis | Its diagnosis is not authoritative when stale, empty, or contradicted by the bundle |
| Jenkins | Runs the suites and retains console/artifact evidence | A final `exit 1` alone does not identify the first failed gate |
| Pushgateway | Receives suite/build quality telemetry | A cumulative counter is not the current build result |
| VictoriaMetrics | Stores and answers PromQL for quality and environment telemetry | A Grafana color is not direct proof of root cause |
| Grafana | Visualizes and alerts on VictoriaMetrics data | A red panel must be traced to its query, labels, time range, and raw series |
| Flux | Applies reviewed Git state to the cluster | A recent reconciliation is correlation until the changed path matches the failure |
| Kubernetes | Supplies workload, event, log, node, storage, and dependency evidence | An unrelated unhealthy pod is not proof that CI failed because of the cluster |

Direct Jenkins artifact requests currently require authorization and can return
HTTP 403. That does not break the workflow: Ariadne retains selected Jenkins
console tails and named artifact contents in its deterministic bundle. A report
must say `retained Ariadne evidence` when that fallback is used; it must not
pretend direct Jenkins access succeeded.

## The actual supervised triage algorithm

1. Classify the request as test/build triage, service health, or alert tuning.
2. Read the latest Ariadne diagnosis and deterministic bundle with HTTP GET.
3. Compare their timestamps. The deterministic bundle remains authoritative.
4. Select a terminal failed build. Keep running or unknown builds out of the
   terminal-failure list.
5. Identify the first enforced failed gate in this order:
   `style -> loc -> coverage -> tests -> gate_glue -> sonarqube -> supply_chain`.
6. Cite the smallest decisive Jenkins log/artifact evidence. State whether it
   came directly from Jenkins or from Ariadne retention.
7. Query the matching build/check/test series in VictoriaMetrics. Distinguish a
   current gauge from a cumulative counter and ignore zero-valued failure
   series.
8. Correlate recent Gitea commits and the relevant Flux revision by timestamp
   and affected path. Recency alone is not causation.
9. Check only the Kubernetes resources capable of explaining that failure.
   Classify observations as direct, contributing candidate, or background.
10. Return `Finding`, `Confidence`, `Evidence`, `Likely cause`, `Blast radius`,
    `Next checks`, `Repo-side fix`, and `Approval required`.
11. Stop at a proposal. A human reviews the patch or action; Git and Flux remain
    the delivery path.

## What Hermes can read and what it cannot do

The live `hermes-triage` ServiceAccount can get/list/watch ordinary workload,
log, event, ingress, storage, Flux, and image-automation metadata. It cannot
read Kubernetes Secret values, create exec sessions, patch Deployments, or
patch Flux Kustomizations. The configured command deny list also blocks common
Kubernetes and Flux mutations.

The security boundary is layered:

1. Keycloak authenticates the person.
2. oauth2-proxy restricts the operator surface to Brad.
3. The operator has a separate namespace, PVC, configuration, and ServiceAccount.
4. Kubernetes RBAC is the hard API authorization boundary.
5. NetworkPolicy limits reachable paths where configured.
6. Hermes approvals and instructions provide a user-facing safety layer.

A skill is procedure and context, not a permission grant. Adding a sentence to
a skill cannot bypass Kubernetes RBAC.

## What “Hermes learns the workflow” means

It does not silently retrain model weights on cluster data. Learning here means
that a successful repeated procedure is written as a reusable skill on the
operator PVC or versioned in Git. The skill describes when it should trigger,
the evidence order, interpretation rules, output contract, and safety boundary.

The current workflow has a versioned top-level skill and persisted specialist
skills for:

- orchestration and evidence reporting;
- retained Jenkins evidence;
- quality metrics;
- Gitea/Flux correlation;
- Kubernetes failure classification;
- Grafana metric provenance;
- Soteria backup health;
- approval-required actions.

The model still evaluates fresh variable evidence on every incident. The skill
makes the process repeatable; it does not freeze the answer.

## The four operator skills to remember

- `triage-titan-test-failures`: CI, tests, builds, quality gates, and suspected
  test-environment regressions.
- `triage-atlas-service-health`: active service or cluster incidents and red
  high-level health panels.
- `tune-atlas-alerts`: noisy alerts, impossible metrics, bad PromQL, and
  generator-owned Grafana corrections.
- `master-hermes-on-atlas`: hands-on training, assessments, architecture, and
  claim audits.

Do not start by choosing raw tools. State the operational question and let the
skill route to the narrow evidence source.

## Two live, repeatable proof cases

### Proof 6: Soteria build 272

- Terminal result: failure.
- Tests: 318 passed, zero failed.
- Local coverage: 96.195 percent.
- First enforced failure: SonarQube `new_coverage=0.0` against threshold 80.
- Runtime: Soteria remained Ready.
- Correct conclusion: a Sonar new-code policy/reporting problem, not a test or
  Kubernetes capacity failure.
- Correct restraint: do not weaken the policy until scanner import and baseline
  evidence identifies whether the issue is configuration or legitimate new
  uncovered code.

### Proof 7: Ananke build 242

- Terminal result: failure.
- Local coverage gate: 61.8 percent and failed.
- Other checks: tests, SonarQube, supply-chain, LOC, docs naming, and gate glue
  were healthy.
- Sonar new-code coverage: 93.1 percent, which is a different scope.
- Correct conclusion: local coverage input/scope caused the enforced failure;
  do not call the Sonar number contradictory without comparing inputs.
- Correct restraint: do not lower the threshold until the retained local gate
  inputs are readable.

The full sessions and redacted Markdown exports are in Sessions and
`Files/triage-proof`.

## Five-minute demonstration

1. Open Models and show `openai-codex/gpt-5.6-terra` as primary and
   `gpt-oss:20b` as local fallback.
2. Open Skills and show the four operator skills plus the persisted component
   skills.
3. Open `Proof 6 - Soteria 272 Sonar new coverage triage` in Sessions.
4. Point out the timestamped bundle, exact build/artifact evidence, metric
   corroboration, healthy runtime, fact/inference separation, and approval
   boundary.
5. Open Proof 7 and explain why local coverage and Sonar new-code coverage can
   differ without either number being fabricated.
6. End by showing that Hermes proposes a repo-side correction but cannot patch
   the Deployment or Flux Kustomization with its ServiceAccount.

Use this short explanation:

> Hermes is the persistent, permissioned workflow layer around the model. In
> this cluster Ariadne collects deterministic evidence, Hermes correlates it
> with retained Jenkins artifacts, Git/Flux state, Kubernetes health, and
> quality metrics, and then returns a supervised proposal. Repeated procedures
> become explicit skills. Kubernetes RBAC prevents the agent from turning a
> diagnosis into an unreviewed infrastructure change.

## Prompts that exercise the real system

- `Use $triage-titan-test-failures. Triage the worst current terminal CI failure and link every decisive piece of evidence.`
- `Use $triage-titan-test-failures. Triage Ananke build 242. Separate local coverage from Sonar new-code coverage.`
- `Use $triage-atlas-service-health. Explain the VictoriaMetrics outage from current state and retained events; separate recovered impact from current impact.`
- `Use $tune-atlas-alerts. Trace one currently firing alert to its generated source and raw PromQL, but do not edit it.`
- `Use $master-hermes-on-atlas. Assess me on the request path and permission boundary. One question at a time.`

## Honest limits

- Hermes does not currently apply production or cluster changes autonomously.
- Direct Jenkins console/artifact access may be forbidden; Ariadne retention is
  the current fallback and must be named as provenance.
- Local `gpt-oss:20b` is useful for bounded work but is slower and less reliable
  for multi-source triage than Codex.
- The current Ariadne local diagnosis can return an empty model response. That
  does not invalidate the deterministic bundle or prevent Codex-backed Hermes
  from triaging it.
- A single successful case demonstrates capability, not mastery. Mastery means
  leading different real incidents, improving the skill after failures, and
  teaching the architecture without prompts.

## Your shortest path to fluency

1. Explain the request diagram without looking.
2. Explain why Ariadne and Hermes are separate components.
3. Reproduce Proof 6 from the raw bundle and metrics.
4. Reproduce Proof 7 and explain the two coverage scopes.
5. Produce the live RBAC allow/deny matrix with `kubectl auth can-i`.
6. Create one small writable skill from a repeated sub-workflow, test a trigger
   and non-trigger case, then improve it.
7. Lead one new incident while Hermes coaches rather than answers for you.
8. Teach the five-minute demonstration to another person.

At that point the interview claims are demonstrable. Continue repeating real
incidents before describing yourself as fully autonomous or the system as
self-correcting.
