Segment Automation V2

Segment Automation via Rube MCP

Overview

This public intake copy packages plugins/antigravity-awesome-skills/skills/segment-automation from https://github.com/sickn33/antigravity-awesome-skills into the native Omni Skills editorial shape without hiding its origin.

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses the external_source block in metadata.json plus ORIGIN.md as the provenance anchor for review.

Segment Automation via Rube MCP Automate Segment customer data platform operations through Composio's Segment toolkit via Rube MCP.

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Prerequisites, Common Patterns, Known Pitfalls, Limitations.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

• This skill is applicable to execute the workflow or actions described in the overview.
• Use when the request clearly matches the imported source intent: Automate Segment tasks via Rube MCP (Composio): track events, identify users, manage groups, page views, aliases, batch operations. Always search tools first for current schemas.
• Use when the operator should preserve upstream workflow detail instead of rewriting the process from scratch.
• Use when provenance needs to stay visible in the answer, PR, or review packet.
• Use when copied upstream references, examples, or scripts materially improve the answer.
• Use when the workflow should remain reviewable in the public intake repo before the private enhancer takes over.

Operating Table

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. Verify Rube MCP is available by confirming RUBESEARCHTOOLS responds
2. Call RUBEMANAGECONNECTIONS with toolkit segment
3. If connection is not ACTIVE, follow the returned auth link to complete Segment authentication
4. Confirm connection status shows ACTIVE before running any workflows
5. SEGMENT_TRACK - Send a single track event [Required]
6. userId: User identifier (required if no anonymousId)
7. anonymousId: Anonymous identifier (required if no userId)

Imported Workflow Notes

Imported: Setup

Get Rube MCP: Add https://rube.app/mcp as an MCP server in your client configuration. No API keys needed — just add the endpoint and it works.

1. Verify Rube MCP is available by confirming RUBE_SEARCH_TOOLS responds
2. Call RUBE_MANAGE_CONNECTIONS with toolkit segment
3. If connection is not ACTIVE, follow the returned auth link to complete Segment authentication
4. Confirm connection status shows ACTIVE before running any workflows

Imported: Core Workflows

1. Track Events

When to use: User wants to send event data to Segment for downstream destinations

Tool sequence:

1. SEGMENT_TRACK - Send a single track event [Required]

Key parameters:

• userId: User identifier (required if no anonymousId)
• anonymousId: Anonymous identifier (required if no userId)
• event: Event name (e.g., 'Order Completed', 'Button Clicked')
• properties: Object with event-specific properties
• timestamp: ISO 8601 timestamp (optional; defaults to server time)
• context: Object with contextual metadata (IP, user agent, etc.)

Pitfalls:

• At least one of userId or anonymousId is required
• event name is required and should follow consistent naming conventions
• Properties are freeform objects; ensure consistent schema across events
• Timestamp must be ISO 8601 format (e.g., '2024-01-15T10:30:00Z')
• Events are processed asynchronously; successful API response means accepted, not delivered

2. Identify Users

When to use: User wants to associate traits with a user profile in Segment

Tool sequence:

1. SEGMENT_IDENTIFY - Set user traits and identity [Required]

Key parameters:

• userId: User identifier (required if no anonymousId)
• anonymousId: Anonymous identifier
• traits: Object with user properties (email, name, plan, etc.)
• timestamp: ISO 8601 timestamp
• context: Contextual metadata

Pitfalls:

• At least one of userId or anonymousId is required
• Traits are merged with existing traits, not replaced
• To remove a trait, set it to null
• Identify calls should be made before track calls for new users
• Avoid sending PII in traits unless destinations are configured for it

3. Batch Operations

When to use: User wants to send multiple events, identifies, or other calls in a single request

Tool sequence:

1. SEGMENT_BATCH - Send multiple Segment calls in one request [Required]

Key parameters:

• batch: Array of message objects, each with:
  • type: Message type ('track', 'identify', 'group', 'page', 'alias')
  • userId / anonymousId: User identifier
  • Additional fields based on type (event, properties, traits, etc.)

Pitfalls:

• Each message in the batch must have a valid type field
• Maximum batch size limit applies; check schema for current limit
• All messages in a batch are processed independently; one failure does not affect others
• Each message must independently satisfy its type's requirements (e.g., track needs event name)
• Batch is the most efficient way to send multiple calls; prefer over individual calls

4. Group Users

When to use: User wants to associate a user with a company, team, or organization

Tool sequence:

1. SEGMENT_GROUP - Associate user with a group [Required]

Key parameters:

• userId: User identifier (required if no anonymousId)
• anonymousId: Anonymous identifier
• groupId: Group/organization identifier (required)
• traits: Object with group properties (name, industry, size, plan)
• timestamp: ISO 8601 timestamp

Pitfalls:

• groupId is required; it identifies the company or organization
• Group traits are merged with existing traits for that group
• A user can belong to multiple groups
• Group traits update the group profile, not the user profile

5. Track Page Views

When to use: User wants to record page view events in Segment

Tool sequence:

1. SEGMENT_PAGE - Send a page view event [Required]

Key parameters:

• userId: User identifier (required if no anonymousId)
• anonymousId: Anonymous identifier
• name: Page name (e.g., 'Home', 'Pricing', 'Dashboard')
• category: Page category (e.g., 'Docs', 'Marketing')
• properties: Object with page-specific properties (url, title, referrer)

Pitfalls:

• At least one of userId or anonymousId is required
• name and category are optional but recommended for proper analytics
• Standard properties include url, title, referrer, path, search
• Page calls are often automated; manual use is for server-side page tracking

6. Alias Users and Manage Sources

When to use: User wants to merge anonymous and identified users, or manage source configuration

Tool sequence:

1. SEGMENT_ALIAS - Link two user identities together [Optional]
2. SEGMENT_LIST_SCHEMA_SETTINGS_IN_SOURCE - View source schema settings [Optional]
3. SEGMENT_UPDATE_SOURCE - Update source configuration [Optional]

Key parameters:

• For ALIAS:
  • userId: New user identifier (the identified ID)
  • previousId: Old user identifier (the anonymous ID)
• For source operations:
  • sourceId: Source identifier

Pitfalls:

• ALIAS is a one-way operation; cannot be undone
• previousId is the anonymous/old ID, userId is the new/identified ID
• Not all destinations support alias calls; check destination documentation
• ALIAS should be called once when a user first identifies (e.g., signs up)
• Source updates may affect data collection; review changes carefully

Imported: Prerequisites

• Rube MCP must be connected (RUBE_SEARCH_TOOLS available)
• Active Segment connection via RUBE_MANAGE_CONNECTIONS with toolkit segment
• Always call RUBE_SEARCH_TOOLS first to get current tool schemas

Examples

Example 1: Ask for the upstream workflow directly

Use @segment-automation-v2 to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @segment-automation-v2 against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @segment-automation-v2 for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @segment-automation-v2 using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

• Keep the imported skill grounded in the upstream repository; do not invent steps that the source material cannot support.
• Prefer the smallest useful set of support files so the workflow stays auditable and fast to review.
• Keep provenance, source commit, and imported file paths visible in notes and PR descriptions.
• Point directly at the copied upstream files that justify the workflow instead of relying on generic review boilerplate.
• Treat generated examples as scaffolding; adapt them to the concrete task before execution.
• Route to a stronger native skill when architecture, debugging, design, or security concerns become dominant.

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in plugins/antigravity-awesome-skills/skills/segment-automation, fails to mention provenance, or does not use any copied source files at all. Solution: Re-open metadata.json, ORIGIN.md, and the most relevant copied upstream files. Check the external_source block first, then restate the provenance before continuing.

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated SKILL.md, but they cannot quickly tell which references, examples, or scripts matter for the current task. Solution: Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Related Skills

• @00-andruia-consultant - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @00-andruia-consultant-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @10-andruia-skill-smith - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @10-andruia-skill-smith-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

Imported Reference Notes

Imported: Quick Reference

Imported: Common Patterns

User Lifecycle

Standard Segment user lifecycle:

1. Anonymous user visits -> PAGE call with anonymousId
2. User interacts -> TRACK call with anonymousId
3. User signs up -> ALIAS (anonymousId -> userId), then IDENTIFY with traits
4. User takes action -> TRACK call with userId
5. User joins org -> GROUP call linking userId to groupId

Batch Optimization

For bulk data ingestion:

1. Collect events in memory (array of message objects)
2. Each message includes type, userId/anonymousId, and type-specific fields
3. Call SEGMENT_BATCH with the collected messages
4. Check response for any individual message errors

Naming Conventions

Segment recommends consistent event naming:

• Events: Use "Object Action" format (e.g., 'Order Completed', 'Article Viewed')
• Properties: Use snake_case (e.g., 'order_total', 'product_name')
• Traits: Use snake_case (e.g., 'first_name', 'plan_type')

Imported: Known Pitfalls

Identity Resolution:

• Always include userId or anonymousId on every call
• Use ALIAS only once per user identity merge
• Identify before tracking to ensure proper user association

Data Quality:

• Event names should be consistent across all sources
• Properties should follow a defined schema for downstream compatibility
• Avoid sending sensitive PII unless destinations are configured for it

Rate Limits:

• Use BATCH for bulk operations to stay within rate limits
• Individual calls are rate-limited per source
• Batch calls are more efficient and less likely to be throttled

Response Parsing:

• Successful responses indicate acceptance, not delivery to destinations
• Response data may be nested under data key
• Check for error fields in batch responses for individual message failures

Timestamps:

• Must be ISO 8601 format with timezone (e.g., '2024-01-15T10:30:00Z')
• Omitting timestamp uses server receive time
• Historical data imports should include explicit timestamps

Imported: Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.