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。
Cross-platform issue triage. Pulls from Sentry (MCP), Linear (MCP), GitHub Issues (gh). Cross-references against code to find already-fixed issues. Auto-resolves fixed ones. Dispatches agents for active issues.
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 triaging, load:
cat ${CLAUDE_PLUGIN_DATA_DIR:-$HOME/.claude/plugins/data/ops-ops-marketplace}/preferences.json — read project registry for repo pathscat ${CLAUDE_PLUGIN_DATA_DIR}/daemon-health.json — ensure services healthymcp__doppler__*) → env → Doppler CLI fallback → password manager: SENTRY_AUTH_TOKEN, LINEAR_API_KEY, GITHUB_TOKEN${CLAUDE_PLUGIN_DATA_DIR}/memories/topics_active.md for issue context| Command | Usage | Output |
|---|---|---|
gh issue list --state open --json number,title,body,labels,assignees,createdAt,url --limit 50 | Open issues | JSON array |
gh issue list --repo <owner/repo> --state open --json number,title,labels,createdAt --limit 20 | Repo issues | JSON array |
gh pr list --state merged --search "#<N>" | PRs referencing issue | JSON array |
gh issue close <N> --comment "<msg>" | Close issue | Confirmation |
| Command | Usage | Output |
|---|---|---|
sentry-cli issues list --project <slug> --status unresolved | Unresolved issues | Issue list |
curl -H "Authorization: Bearer $SENTRY_AUTH_TOKEN" "https://sentry.io/api/0/projects/<org>/<proj>/issues/?query=is:unresolved" | API fallback when MCP unavailable | JSON array |
| Command | Usage | Output |
|---|---|---|
curl -X POST https://api.linear.app/graphql -H "Authorization: $LINEAR_API_KEY" -H "Content-Type: application/json" -d '{"query":"{ issues(filter: {state: {type: {in: [\"started\",\"unstarted\"]}}}) { nodes { id title state { name } priority assignee { name } } } }"}' | Active issues | JSON |
If CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1 is set, use Agent Teams when dispatching fix agents for multiple issues. This enables:
Team setup (only when flag is enabled, Phase 4 dispatch):
TeamCreate("triage-fixers")
Agent(team_name="triage-fixers", name="fix-[issue-id]", subagent_type="ops:triage-agent", ...)
Use broadcast(content="Root cause found: missing index on users.email — check if your issue is related") to share discoveries.
If the flag is NOT set, fall back to standard parallel subagents.
Run all of these simultaneously:
gh issue list --state open --json number,title,body,labels,assignees,createdAt,url --limit 50 2>/dev/null
REGISTRY="${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 "=== $repo ==="
gh issue list --repo "$repo" --state open --json number,title,labels,createdAt --limit 20 2>/dev/null
done
If Sentry MCP is connected, fetch unresolved issues for all projects.
Otherwise run: echo "Sentry MCP not available"
Use mcp__linear__list_teams to get team IDs, then mcp__linear__list_issues with filter: {state: {type: {in: ["unstarted", "started"]}}} for each team.
For each Sentry issue, check if it's already fixed:
grep for the relevant code in the affected repo.git log --oneline --all -- [file] 2>/dev/null | head -20For each GitHub Issue:
gh pr list --state merged --search "#[N]")For issues confirmed fixed in code AND deployed, show the full list and use AskUserQuestion:
Found N issues confirmed fixed and deployed:
[Sentry] [title] — fix in [commit], deployed [time ago]
[Linear] [title] — fix in [commit], deployed [time ago]
[GitHub] #[N] [title] — referenced in merged PR #[M]
[Resolve all N] [Review each one] [Skip — don't auto-resolve]
If user picks "Review each one", show each issue individually with [Resolve] / [Skip] via AskUserQuestion.
For confirmed issues:
mcp__linear__update_issue with state: "Done"gh issue close [N] --comment "Auto-closed: fix confirmed deployed"Log all resolutions.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
OPS ► TRIAGE — [date]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
AUTO-RESOLVED (already fixed)
✓ [Sentry] [title] — fix in [commit]
✓ [Linear] [title] — closed
✓ [GitHub] #[N] [title] — closed
ACTIVE ISSUES (needs work)
CRITICAL [source] [title] [age] [assigned?]
HIGH [source] [title] [age] [assigned?]
MEDIUM [source] [title] [age] [assigned?]
──────────────────────────────────────────────────────
Use batched AskUserQuestion calls (max 4 options each):
AskUserQuestion call 1:
[Dispatch agent for [top critical issue]]
[Dispatch agent for [second issue]]
[Assign issue to sprint (Linear)]
[More...]
AskUserQuestion call 2 (only if "More..."):
[Bulk-assign all HIGH to current sprint]
[Done]
When dispatching for an issue, spawn an Agent using agents/triage-agent.md with:
Filter to $ARGUMENTS project/source if specified.
Use TaskCreate for each issue being investigated. Update with TaskUpdate as issues are resolved/dispatched/skipped. Gives the user a live triage checklist.
When Sentry MCP hits quota limits, fall back to WebFetch with https://sentry.io/api/0/projects/<org>/<project>/issues/?query=is:unresolved (using SENTRY_AUTH_TOKEN header). Same for GitHub issue details when gh is slow.
Use WebSearch to find known solutions for recurring errors (e.g., "AWS RDS connection reset", "ECS task stopped reason"). Include findings in the triage board as context.
When dispatching fix agents, use LSP to find symbol definitions, references, and call hierarchies. This helps agents navigate unfamiliar codebases faster than grep.
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。