Automate ActiveCampaign tasks via Rube MCP (Composio): manage contacts, tags, list subscriptions, automation enrollment, and tasks. Always search tools first for current schemas.
日本語の概要は準備中です。原文の説明を表示しています。
Business-level "what should I do next". Priority stack — fires > unread comms > ready-to-merge PRs > Linear sprint > revenue-generating GSD work. Uses pre-gathered data and routes to the right skill.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Before advising, load:
cat ${CLAUDE_PLUGIN_DATA_DIR:-$HOME/.claude/plugins/data/ops-ops-marketplace}/preferences.json — read owner, primary_project, default_channelscat ${CLAUDE_PLUGIN_DATA_DIR}/daemon-health.json — flag any action_needed as priority${CLAUDE_PLUGIN_DATA_DIR}/memories/topics_active.md for ongoing work context| Command | Usage | Output |
|---|---|---|
gh pr list --state open --json number,title,statusCheckRollup,reviewDecision | Open PRs with CI/review status | JSON array |
If CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1 is set, use Agent Teams when gathering priority data in parallel. This enables:
Team setup (only when flag is enabled):
TeamCreate("next-team")
Agent(team_name="next-team", name="fires-checker", prompt="Check infra health and CI for production fires")
Agent(team_name="next-team", name="comms-checker", prompt="Check unread messages across all channels")
Agent(team_name="next-team", name="prs-checker", prompt="Find PRs ready to merge — CI green, reviews approved")
Agent(team_name="next-team", name="sprint-checker", prompt="Check Linear sprint for highest-priority in-progress issues")
If the flag is NOT set, use standard fire-and-forget subagents.
${CLAUDE_PLUGIN_ROOT}/bin/ops-infra 2>/dev/null || echo '{"clusters":[]}'
${CLAUDE_PLUGIN_ROOT}/bin/ops-prs 2>/dev/null || echo '[]'
${CLAUDE_PLUGIN_ROOT}/bin/ops-ci 2>/dev/null || echo '[]'
${CLAUDE_PLUGIN_ROOT}/bin/ops-unread 2>/dev/null || echo '{}'
for d in $(jq -r '.projects[] | select(.gsd == true) | .paths[]' "${CLAUDE_PLUGIN_ROOT}/scripts/registry.json" 2>/dev/null); do
expanded="${d/#\~/$HOME}"
if [ -f "$expanded/.planning/STATE.md" ]; then
alias=$(basename "$expanded")
cat "$expanded/.planning/STATE.md" 2>/dev/null | head -30
echo "---NEXT---"
fi
done
Apply the priority stack to all pre-gathered data:
Check infra data for: unhealthy ECS tasks, stopped services, failed deployments.
Check CI for: broken main or dev branches.
If any fires exist → recommend /ops-fires immediately.
Check unread counts. If WhatsApp or email has unread messages from humans (not automated):
/ops-inbox [channel]Check PRs for: CI green + no unresolved review comments + not draft.
If any ready → recommend reviewing that PR now.
Check: gh pr list --state open --json number,title,statusCheckRollup,reviewDecision 2>/dev/null
Fetch current sprint issues: use mcp__linear__list_issues filtered to current cycle (use Linear GraphQL fallback for cycle queries if needed).
Find highest-priority issue that is in progress or unstarted.
From GSD state, find the highest revenue-impact active phase across all projects.
Revenue weighting: read revenue.stage and priority from scripts/registry.json — projects with lower priority numbers (higher priority) and revenue stage of growth or active outrank pre-launch or development. Within the same tier, prioritize closest-to-done phases.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
OPS ► NEXT ACTION
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
TOP PRIORITY: [fires|comms|PR|sprint|gsd]
▶ [specific action in one sentence]
WHY: [1-2 sentence rationale]
──────────────────────────────────────────────────────
Full priority stack:
1. [action] — [why] → [/skill or command]
2. [action] — [why] → [/skill or command]
3. [action] — [why] → [/skill or command]
4. [action] — [why] → [/skill or command]
5. [action] — [why] → [/skill or command]
──────────────────────────────────────────────────────
a) Do #1 now
b) Do #2 now
c) Show me everything (/ops-go)
d) I'll decide — just show the briefing
→ Pick or describe what you want
──────────────────────────────────────────────────────
Use AskUserQuestion. When user selects an option, invoke the corresponding skill directly — don't describe it, do it.
If $ARGUMENTS contains context (e.g., "focus on <project-alias>"), constrain the analysis to that context.
After the user selects an action, use TaskCreate to track it. When routing to the corresponding skill, the task persists as a reminder of what the user chose to focus on.
When pre-gathered data is stale or incomplete, use WebFetch to pull fresh data from APIs (Linear GraphQL, Sentry, GitHub) directly.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Automate ActiveCampaign tasks via Rube MCP (Composio): manage contacts, tags, list subscriptions, automation enrollment, and tasks. Always search tools first for current schemas.
日本語の概要は準備中です。原文の説明を表示しています。
Analytics your AI agent can actually use. Track, analyze, run A/B experiments, and optimize across all your projects via CLI. Includes a growth playbook so your agent knows HOW to grow, not just what to track.
日本語の概要は準備中です。原文の説明を表示しています。
Teaches when to recall from long-term memory before acting and when to save durable decisions, corrections and failures afterwards. Use when a memory tool or MCP memory server is connected but the agent is not using it consistently, when the user complains that the assistant forgets preferences, conventions or past decisions between sessions, or when setting up persistent memory for a project. Works with any memory backend: a folder of Markdown files, a local MCP server, or a managed service.
日本語の概要は準備中です。原文の説明を表示しています。
Audit local AI coding-agent sessions with agenttrace for cost, tokens, tool failures, latency, anomalies, health, diffs, and CI gates.
日本語の概要は準備中です。原文の説明を表示しています。
Audit whether a website can be found, crawled, and cited by AI answer engines such as ChatGPT Search, Perplexity, Google AI Overviews, and Microsoft Copilot. Use when someone asks why their brand is missing from AI answers, whether AI crawlers can read their site, how to get cited by ChatGPT or Perplexity, or asks for a GEO or AEO (generative / answer engine optimization) review. Produces a citation baseline across buyer-intent prompts, a crawler-access check, a citability review of named pages, and a ranked fix list. Not for keyword rank tracking, paid search, or pages behind a login.
日本語の概要は準備中です。原文の説明を表示しています。
Automate Airtable tasks via Rube MCP (Composio): records, bases, tables, fields, views. Always search tools first for current schemas.
日本語の概要は準備中です。原文の説明を表示しています。