git:20260614.d66a5d5 to git:20260822.2fde0ca

3 added, 1 removed. Audit A to A.

---

name: ops-deploy

- description: Deploy status across all projects. Shows ECS service versions, Vercel deployments, recent deploys, pending deploys, and CI/CD pipeline state.

+ description: "This skill should be used when the user asks to \"/ops:ops-deploy\", \"run ops-deploy\", or \"use ops-deploy\". Deploy status across all projects. Shows ECS service versions, Vercel deployments, recent deploys, pending deploys, and CI/CD pipeline state."

argument-hint: '[project-alias|ecs|vercel|all]'

allowed-tools:

- Bash

- Read

- Grep

- Glob

- Skill

- Agent

- TeamCreate

- SendMessage

- AskUserQuestion

- TaskCreate

- TaskUpdate

- Monitor

- WebFetch

- mcp__claude_ai_Vercel__list_deployments

- mcp__claude_ai_Vercel__list_projects

- mcp__claude_ai_Vercel__get_deployment

- mcp__claude_ai_Vercel__get_runtime_logs

- mcp__claude_ai_Vercel__get_deployment_build_logs

effort: low

maxTurns: 20

disallowedTools:

- Edit

- Write

- NotebookEdit

---

# OPS ► DEPLOY STATUS

+ Load `ops-rules` before acting. Public repo (no personal data). Outbound: one draft → one approval → one send. If `AskUserQuestion` / `Workflow` are missing, follow Rule 10 in `ops-rules` (Hermes: numbered options / two-turn Telegram card; `delegate_task`).

## Runtime Context

Before executing, load available context:

1. **Preferences**: Read `${CLAUDE_PLUGIN_DATA_DIR:-$HOME/.claude/plugins/data/ops-ops-marketplace}/preferences.json`

- `timezone` — display all deploy timestamps in the correct timezone

2. **Daemon health**: Read `${CLAUDE_PLUGIN_DATA_DIR}/daemon-health.json`

- Check `infra-monitor` status — if not running, note that ECS data may be stale

3. **Secrets**: AWS and Vercel credentials required.

### Secret Resolution

- AWS: check `$AWS_PROFILE` / `$AWS_ACCESS_KEY_ID` → `doppler secrets get AWS_ACCESS_KEY_ID --plain` → vault query cmd from prefs

- Vercel token: check `$VERCEL_TOKEN` → `doppler secrets get VERCEL_TOKEN --plain` → vault

## CLI/API Reference

### aws CLI

| Command | Usage | Output |

| --------------------------------------------------------------------------- | ------------------- | ------------------------------------------------------------------------------- |

| `aws ecs list-clusters --output json` | All ECS clusters | `{clusterArns: [...]}` |

| `aws ecs list-services --cluster <name> --output json` | Services in cluster | `{serviceArns: [...]}` |

| `aws ecs describe-services --cluster <name> --services <arn> --output json` | Service health | `{services: [{serviceName, status, runningCount, desiredCount, pendingCount}]}` |

| `aws logs tail /ecs/<service> --since 1h --format short` | ECS logs | Log lines |

### gh CLI (GitHub)

| Command | Usage | Output |

| --------------------------------------------------------------------------------------------------------- | -------------- | ------------------------------ |

| `gh run list --repo <owner/repo> --limit 5 --json status,conclusion,name,headBranch,createdAt,databaseId` | CI runs | JSON array |

| `gh run view <id> --repo <repo> --log-failed` | Failed CI logs | Log output |

| `gh run watch <run-id> --repo <repo>` | Stream CI run | Live output (use with Monitor) |

---

## Agent Teams support

If `CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1` is set, use **Agent Teams** when checking deploy platforms in parallel. This enables:

- Agents share context and can coordinate mid-flight

- You can steer priorities in real-time

- Agents report progress as they complete

**Team setup** (only when flag is enabled):

```

TeamCreate("deploy-team")

Agent(team_name="deploy-team", name="ecs-checker", prompt="List all ECS clusters and describe service health, running/desired counts")

Agent(team_name="deploy-team", name="vercel-checker", prompt="List Vercel projects and recent deployments with status")

Agent(team_name="deploy-team", name="ci-checker", prompt="Check GitHub Actions runs across all registered repos for failures")

```

If the flag is NOT set, use standard fire-and-forget subagents.

## Phase 1 — Gather deploy data in parallel

### ECS services (all clusters)

```bash

${CLAUDE_PLUGIN_ROOT}/bin/ops-infra 2>/dev/null || \

aws ecs list-clusters --output json 2>/dev/null

```

### ECS service details

```bash

for cluster in $(aws ecs list-clusters --output json 2>/dev/null | jq -r '.clusterArns[]'); do

cluster_name=$(basename "$cluster")

aws ecs list-services --cluster "$cluster_name" --output json 2>/dev/null | \

jq -r '.serviceArns[]' | while read svc; do

aws ecs describe-services --cluster "$cluster_name" --services "$svc" \

--output json 2>/dev/null | jq '.services[] | {name: .serviceName, desired: .desiredCount, running: .runningCount, pending: .pendingCount, image: (.taskDefinition // "unknown"), status: .status}'

done

```

### Recent GitHub Actions runs (registry-driven)

```bash

REGISTRY="${CLAUDE_PLUGIN_ROOT}/scripts/registry.json"

[ -f "$REGISTRY" ] || REGISTRY="${CLAUDE_PLUGIN_ROOT}/scripts/registry.example.json"

for repo in $(jq -r '.projects[] | select(.gsd == true) | .repos[]' "$REGISTRY" 2>/dev/null); do

echo "=== $repo ==="

gh run list --repo "$repo" --limit 5 --json status,conclusion,name,headBranch,createdAt,databaseId 2>/dev/null

done

```

### Vercel deployments

Use `mcp__claude_ai_Vercel__list_projects` then `mcp__claude_ai_Vercel__list_deployments` for each project (limit 5 per project).

---

## Phase 2 — Render dashboard

```

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

OPS ► DEPLOY STATUS — [timestamp]

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

ECS SERVICES

CLUSTER SERVICE D/R/P STATUS LAST DEPLOY

─────────────────────────────────────────────────────

[cluster] [service] [x/x/x] ACTIVE [time ago]

...

VERCEL DEPLOYMENTS

PROJECT ENV STATUS COMMIT DEPLOYED

─────────────────────────────────────────────────────

[project] production READY [sha] [time ago]

...

CI/CD PIPELINE

REPO BRANCH WORKFLOW STATUS AGE

─────────────────────────────────────────────────────

example-api main Deploy API ✓ success 2h

example-web dev Build ✗ failure 1h

...

PENDING DEPLOYS (branch ready, not yet deployed)

[repo] [branch] [PR#] [CI status] → needs merge to trigger

──────────────────────────────────────────────────────

```

After rendering, use **batched AskUserQuestion calls** (max 4 options each). Only show actions relevant to the current state (e.g., skip "View logs for failing service" if nothing is failing). If <=4 relevant actions, use a single call. If >4, batch:

AskUserQuestion call 1:

```

[View logs for [failing service]]

[Trigger manual deploy for [project]]

[View build logs for [failing CI run]]

[More actions...]

```

AskUserQuestion call 2 (only if "More actions..."):

```

[Check Vercel [project] runtime logs]

[Open GitHub Actions for [repo]]

[Back to dashboard]

```

---

## Deep-dive by project

If `$ARGUMENTS` has a project alias, show only that project's deploy info + last 10 CI runs + option to view logs.

For failing deploys: offer to view logs via `mcp__claude_ai_Vercel__get_deployment_build_logs` or ECS CloudWatch logs.

**If user selects manual deploy (option b)**, confirm with `AskUserQuestion` before triggering:

```

Trigger deploy for [project]:

Environment: [production/staging]

Branch: [branch]

Last commit: [sha] — [message]

[Deploy now] [View diff since last deploy first] [Cancel]

```

**If user selects to view logs**, show the logs and use `AskUserQuestion`:

```

[Dispatch fix agent for this failure] [Redeploy] [Back to dashboard]

```

---

## Native tool usage

### Monitor — live deploy streaming

When watching a deploy in progress, use `Monitor` to stream logs:

```

Monitor(command: "gh run watch <run-id> --repo <repo>")

```

For ECS deploys: `Monitor(command: "aws ecs wait services-stable --cluster <cluster> --services <service>")`

### Tasks — deploy tracking

Use `TaskCreate` per project being deployed. Update with `TaskUpdate` as deploys succeed/fail.

### WebFetch — Vercel fallback

When Vercel MCP tools are unavailable, use `WebFetch` with the Vercel API directly:

```

WebFetch(url: "https://api.vercel.com/v6/deployments?projectId=<id>&limit=5", headers: {"Authorization": "Bearer $VERCEL_TOKEN"})

```

---

## Ledger Integration

**CLAIM_KEY:** `deploy:<project>:<env>` (e.g. `deploy:my-api:production`)

Keyed on project + environment so concurrent deploys of the same target are blocked

for the full claim TTL (30 minutes).

### Pre-flight skip-check

```bash

CLAIM_KEY="deploy:<project>:<env>"

ledger query --claim-key "$CLAIM_KEY" --since=-PT24H

```

If `in_progress` exists, a concurrent deploy is already running — abort and surface

to the user. If `done` exists within the last hour, confirm before re-deploying.

### Claim + resolve

```bash

# Claim when deploy pipeline starts

ledger write \

--claim-key "$CLAIM_KEY" \

--kind "file" \

--status "in_progress" \

--title "Deploy: <project> → <env>" \

--ttl-sec 1800

# Resolve after deploy completes or fails

ledger write \

--claim-key "$CLAIM_KEY" \

--kind "file" \

--status "done" \

--title "Deploy: <project> → <env>" \

--context "succeeded|failed: <reason>"

```