demo

name	demo
description	Run a guided, self-paced tour of Resolve using the connected org's live data — surface the environment, resume a chat, fire several in parallel, drill a real RCA with its evidence and a live thread, then investigate something from scratch. Use when someone wants to demo Resolve, give a tour, or show a new user what it can do — phrases like "demo Resolve", "give me a tour", "walk them through Resolve", "show me what Resolve can do", "demo this to <person>".
version	0.1.0
argument-hint	["optional emphasis","or \"start\""]
license	Apache-2.0

Demo Resolve

A guided, checkpointed walkthrough of Resolve using your connected org's live data. You drive each step at your own pace. The arc escalates:

surface → resume a chat → many in parallel → drill a real RCA (evidence + live thread) → turn the findings into a code-fix PR → investigate from scratch.

Every beat stands alone — stop anywhere and it's still a complete demo.

This skill orchestrates with direct tool calls and its own narration. For the streaming beats it follows the stream_command streaming already documented in the ask and investigate skills rather than restating the host-specific mechanics here.

Arguments

If $ARGUMENTS carries an emphasis (e.g. "focus on logs", "keep it short"), bias curation and beat selection toward it. Otherwise run the default arc. Treat a bare start as "begin the tour".

Two run modes

Establish the mode at the start and honor it for every command, every beat:

• Auto (default — today's behavior): you run each command via the tools, pausing at checkpoints for the user's "go" or to let them pick an option.
• Manual (hand-me-the-commands): you do not execute the beat's action. Compose the full command with its args/message filled in and present it for the user to type themselves, then stop and wait for them to run it before moving on. You may still run read-only setup (e.g. overview) so the commands you hand over carry real IDs/values, but every action command (ask, investigate, steer, apply-fix) is theirs to enter. Because they're invoking the real skills, those skills' own run/format behavior (streaming, citations, canvas URLs) applies as-is.

Select via $ARGUMENTS (auto / manual); if unset, ask once at pre-flight.

Two registers in your output

• Tour narration (plain prose): the lines you walk the user through — clean, jargon-light, short.
• Control cue (prefix ▶): meta prompts to the user, not part of the narration. End every beat with a cue that previews exactly what the next step will do, e.g. ▶ Next: open a real RCA and pull the raw telemetry behind its top theory. Say "go", pick from the menu, or tell me what to show.
• Command tag (prefix ▷): name the command for each beat's capability. In auto mode it's just the label, so the user learns it — ▷ Run it yourself: $resolve-ai:overview. In manual mode it's the full runnable command with composed args, and you stop and wait for the user to enter it — e.g. ▷ Type this: $resolve-ai:ask Follow-up: of the error spikes in svc-analysis, which one is most worth acting on first?. Mapping (args from each skill's own argument-hint): surface → $resolve-ai:overview (focused lists $resolve-ai:alerts, $resolve-ai:investigations, $resolve-ai:chats); resume / ask / thread / parallel → $resolve-ai:ask <message>; redirect a live investigation → $resolve-ai:steer <message>; drill or start an RCA → $resolve-ai:investigate <url-or-id | problem>; apply a fix → $resolve-ai:apply-fix.

Pacing — light checkpoints

Pause only at: the start, the post-overview menu, and before any step that sends a message or starts an investigation. Auto-flow narration within a beat. In auto mode, never send a chat or start an investigation without an explicit "go" in that same turn; the read-only beats (overview, RCA drill, evidence) need no consent. In manual mode you never execute an action yourself — you present the full command and wait for the user to run it, which is the natural checkpoint.

Beats

0 · Pre-flight (you only)

On launch, don't start the tour yet. Settle the run mode (auto vs manual — ask if $ARGUMENTS didn't set it) and lay out the agenda for yourself, then ▶ Mode: <auto|manual>. Say "start" when you're ready. Wait.

1 · Orient — what Resolve is

One breath on Resolve: it's an AI SRE for your production incidents. Start with the big picture, then the two primitives everything centers on.

The big picture — $resolve-ai:overview shows investigations, recent alerts, and in-flight chats at a glance. ($resolve-ai:alerts for just the firing feed that auto-triggers investigations; $resolve-ai:help-resolve to get oriented.)

Investigations — structured root-cause workspaces (theories, cited evidence, mitigations, tied to the triggering alert):

• $resolve-ai:investigate — open an existing RCA or start a new one
• $resolve-ai:investigations — list recent investigations
• $resolve-ai:ask — ask a question or open a thread on an investigation
• $resolve-ai:steer — redirect a running investigation with a new finding
• $resolve-ai:apply-fix — turn its findings into a code change, right here

Chats — standalone conversations with Resolve — ask anything about your environment:

• $resolve-ai:ask — start or continue a standalone chat
• $resolve-ai:chats — list recent chats

2 · Surface — the environment

Call list_investigations, list_alerts (with limit: 20), list_chats in parallel, org-wide. Present a tight snapshot: counts plus a couple of headline items.

Curate with taste — this is a demo, not a dump. Privately pick three things to use later:

• best RCA to drill (beat 5): a non-triage_only investigation that has theories — prefer ALERT/INCIDENT; skip smoke-tests.
• best existing chat to resume (beat 3): a real question-style chat from list_chats, status complete.
• best alert to investigate cold (beat 7): a genuine recent firing alert.

▶ Menu — where first? (a) resume a chat, (b) ask several at once, (c) drill a real RCA + its evidence, (d) investigate something from scratch. Or say "tour" to go in order.

3 · Resume a chat

Take the existing chat picked in beat 2 and send a follow-up to it — ask with that chat_id (include investigation_id if it's investigation-scoped). The point: chats persist, you resume a real prior conversation instead of starting cold. Stream the reply per the ask skill — run its returned stream_command, which scopes to the new turn. ▶ Send the follow-up to "<chat name>"? Say "go". ← consent before sending

4 · Many in parallel

Fire two or three questions concurrently, each streaming its own stream_command in the background, side by side. The point: Resolve isn't one-at-a-time. (The ask skill blesses parallel streams.)

Use concrete, service-scoped asks, not vague aggregates — vague ones make the agent guess time ranges and stall. Good shapes (substitute a real service from beat 2):

• recent error spikes in <service> logs — grouped by pattern, calling out new or surging ones
• health metrics for <service> for an operational review — error rate, latency p50/p90/p99, saturation
• pod health in <service> metrics — restarts, OOM kills, pods not Ready

Keep one ask deliberately simple — even a plain hi or a one-liner — so its quick reply lands while the heavier scoped ones are still streaming; the contrast makes the parallelism obvious. ▶ Fire <N> in parallel? Say "go".

5 · Drill a real RCA — evidence + a live thread

On the RCA picked in beat 2:

1. Read it (no consent — read-only): get_investigation → narrate status/phase, the top theory and its confidence.
2. Get the evidence: read_file a citation path from that theory to surface the raw telemetry behind the claim — the actual query or log lines the agent used. This is the trust moment: every conclusion traces to real data.
3. Open a thread on it (consent — sends a message): an investigation-scoped ask (pass investigation_id, no chat_id) that asks a sharp follow-up about the finding, then stream the answer per the ask skill — run its returned stream_command. Shows you can converse with a specific RCA, not just read it. ▶ Open a thread on this RCA with "<question>"? Say "go".

6 · Apply the fix in code — close the loop with a PR (opt-in)

Take the root cause and the thread answer from beat 5 and turn them into a local change — Resolve diagnosed it in production; now write the fix in the editor. Run the apply-fix flow: read the theory and its citations, locate the owning code with Grep/Read, propose the change (theory addressed, files touched, why it works), implement on a "go", then open a PR — loading a PR-creation skill if one's available — so the loop ends at a reviewable pull request, not just a dirty tree. If the root cause is infra/config that doesn't live in this repo, say so and show the change you would make rather than forcing an edit. ▷ Run it yourself: $resolve-ai:apply-fix ▶ This edits local code and opens a PR. Apply the fix? Say "go" — or skip.

7 · Investigate from scratch (the climax) — opt-in

Seed a brand-new investigation from the real recent alert picked in beat 2: compose a short markdown prompt from its title/labels, show it to the user ("this fired ~ min ago — watch Resolve take it cold"), and only on explicit yes call start_investigation. Then stream it live per the investigate skill — run its returned stream_command — theory cards and the evidence trail forming in real time. ▶ This starts a real investigation (uses org credits). Start it? Say "go".

8 · Recap + toolbox

One line recapping the loop, then hand over the controls — the skills they can run themselves: $resolve-ai:overview, $resolve-ai:ask, $resolve-ai:investigate, $resolve-ai:alerts / $resolve-ai:investigations / $resolve-ai:chats, $resolve-ai:steer, $resolve-ai:apply-fix.

Notes

• IDs are ephemeral — always select from a fresh overview, never hardcode an investigation/chat/alert ID.
• Preserve [label](path) citations verbatim; always surface canvas URLs.
• Keep each beat to a couple of lines. The live data is the star — let it carry the demo.