rootly-automation

Overview of rootly-automation skill

What rootly-automation does

rootly-automation is a Claude skill for automating Rootly incident-management operations through Composio’s Rube MCP. Its main value is not a fixed Rootly API wrapper; it teaches the agent to discover the currently available Rootly tools with RUBE_SEARCH_TOOLS, verify the Rootly connection, inspect live schemas, and then execute the right Rube MCP action.

Use this skill when you want an AI agent to help with Rootly workflows such as incident operations, service or team lookups, status-related actions, or other Rootly tasks exposed through Composio’s Rootly toolkit.

Best fit for Rootly and Rube MCP users

The rootly-automation skill is best for teams already using Rootly and willing to connect it through Rube MCP. It fits users who need workflow automation inside an AI client rather than a standalone script, especially when Rootly tool schemas may change and the agent must discover current capabilities before acting.

It is less useful if you only need Rootly documentation, do not have permission to connect Rootly, or want a deterministic CI job with no human review.

Key differentiator: schema discovery first

The important design choice in rootly-automation is “search tools first.” Instead of assuming static command names or stale parameters, the skill tells the agent to call RUBE_SEARCH_TOOLS for the specific Rootly task, then use returned tool slugs, schemas, execution plans, and pitfalls.

That makes the skill safer for Workflow Automation where Rootly actions may affect production incident data. It also reduces failed calls caused by outdated examples.

How to Use rootly-automation skill

rootly-automation install and prerequisites

Install the skill from the repository path with your skill manager, for example:

npx skills add ComposioHQ/awesome-claude-skills --skill rootly-automation

Then configure Rube MCP in your AI client by adding the MCP server endpoint:

https://rube.app/mcp

Before expecting the rootly-automation skill to work, confirm three conditions:

• RUBE_SEARCH_TOOLS is available in the client.
• RUBE_MANAGE_CONNECTIONS can manage the rootly toolkit.
• The Rootly connection status is ACTIVE; if not, follow the returned auth link.

The upstream skill has a single main file, SKILL.md, so read that first. There are no supporting scripts, rules, or reference folders to inspect.

Inputs the skill needs for reliable Rootly actions

A vague request like “update Rootly” forces the agent to guess. A stronger prompt gives the business goal, Rootly object type, identifiers, allowed actions, and review requirements.

Good input format:

• Goal: what should change or be retrieved.
• Scope: incident, service, team, user, status page, escalation, or another Rootly domain.
• Known identifiers: incident title, Rootly ID, slug, service name, team name, or date range.
• Safety limits: read-only, draft first, ask before write, or execute if exact match.
• Output format: summary, table, proposed update, or executed action log.

Example prompt:

Use rootly-automation to find the current Rootly tools for incident updates. Check that my Rootly connection is active. Then locate the incident named “API latency degradation” from today, summarize its current status, and propose the exact update payload before making any write action. Do not execute the update until I approve.

Practical rootly-automation usage workflow

A reliable rootly-automation usage flow should look like this:

1. Call RUBE_SEARCH_TOOLS with a specific use case, such as “Rootly incident status update” or “Rootly list services by owner.”
2. Reuse the returned session ID where appropriate.
3. Call RUBE_MANAGE_CONNECTIONS for toolkit rootly and confirm the connection is active.
4. Select the tool slug and parameters from the live schema, not from memory.
5. For write operations, present the planned tool call and payload before execution unless the user explicitly authorized direct execution.
6. Execute, then return the result, affected Rootly record, and any follow-up action needed.

This pattern is the core rootly-automation guide: discover, verify, plan, execute, summarize.

Repository files to read before adoption

Start with composio-skills/rootly-automation/SKILL.md. It contains the prerequisites, MCP setup, tool discovery examples, and the core workflow pattern. Because this skill does not include extra scripts or reference material, the install decision depends mainly on whether your environment supports Rube MCP and whether Rootly is connected through Composio.

Also review Composio’s Rootly toolkit documentation at composio.dev/toolkits/rootly to understand the broader action surface available through the toolkit.

rootly-automation skill FAQ

Is rootly-automation only for incident response?

No. The skill is framed around Rootly operations broadly, not only one incident action. The exact capabilities depend on the Rootly tools returned by RUBE_SEARCH_TOOLS for your connection and current Composio toolkit support.

How is this better than an ordinary prompt?

An ordinary prompt may invent Rootly API fields or assume tool names. The rootly-automation skill explicitly instructs the agent to discover current Rube MCP schemas first, check the Rootly connection, and follow returned execution plans. That is the main practical benefit for automation reliability.

Is rootly-automation beginner friendly?

It is beginner friendly if your AI client already supports MCP tools and you can complete the Rootly authorization flow. It is not a no-code Rootly tutorial. Users should understand that the agent is operating external tools and that write actions may modify live incident-management data.

When should I not use this skill?

Do not use rootly-automation when you lack Rootly permissions, cannot connect Rube MCP, need offline documentation only, or require a fully audited automation pipeline with hard-coded approvals outside the AI client. For high-risk incident workflows, use it with explicit confirmation steps.

How to Improve rootly-automation skill

Improve prompts with Rootly-specific context

The fastest way to improve rootly-automation results is to provide enough Rootly context for precise tool discovery. Instead of “create an incident,” say:

Search the available Rootly tools for incident creation. I need a new incident for checkout errors affecting production. Severity should be high, service is “Payments API,” team is “Platform,” and I want to review the payload before creation.

This gives the agent a clear use case for RUBE_SEARCH_TOOLS and reduces ambiguous tool selection.

Prevent common failure modes

Common problems include inactive Rootly connections, stale assumptions about schemas, missing identifiers, and unsafe write operations. Avoid them by requiring the agent to:

• Confirm rootly connection status before tool execution.
• Use live schemas from RUBE_SEARCH_TOOLS.
• Ask for clarification when multiple incidents or services match.
• Show proposed payloads before writes.
• Report the exact Rootly object changed.

These safeguards matter more than adding longer prompts.

Iterate after the first output

After the first response, improve the workflow by asking for narrower actions:

• “Filter to incidents created in the last 24 hours.”
• “Only include services owned by the Platform team.”
• “Convert this into an approval-first runbook.”
• “Retry using the returned schema field names exactly.”

Iteration is especially useful because rootly-automation for Workflow Automation depends on discovered tools. The first pass should establish available actions; the second pass should make the operation precise.

Improve the skill itself for team use

If you maintain a local copy of rootly-automation, consider adding team-specific guardrails: default read-before-write behavior, required approval language for incident updates, naming conventions for Rootly services, and examples for your most common workflows. Keep those additions separate from tool schemas, because schemas should still come from RUBE_SEARCH_TOOLS at runtime.