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ttpears

GitLab MCP Server

by ttpears

User Activity Summary

analytics_user_summary
Read-onlyIdempotent

Get aggregated activity counts for a GitLab user over a date range, broken down by action type, project, and day. Replaces raw event feeds with summarized totals.

Instructions

Aggregated activity summary for a user over a time window — totals by action type (pushes, MRs opened/merged, comments, approvals), breakdown by project and by day. Use this instead of list_user_events when you want counts rather than a raw event feed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
userYesUsername (e.g. "alice") or numeric user ID
sinceYesISO date/datetime, inclusive lower bound (e.g. "2026-03-01" or "2026-03-01T00:00:00Z")
untilNoISO date/datetime, inclusive upper bound. Defaults to now.
maxEventsNoCap on events fetched. Defaults to 2000; returned envelope has truncated:true if reached.
userCredentialsNoYour GitLab credentials (optional — falls back to the configured env token if not provided)
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Description explains aggregation behavior, breakdowns, and truncation limit, adding specifics beyond annotations (which already indicate read-only/idempotent). No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two well-structured sentences: first describes purpose and output, second gives usage guidance. No fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For an aggregation tool with 5 params and no output schema, description sufficiently covers behavior and return structure (counts, breakdowns, truncation). Could mention error handling or edge cases but adequate for agent use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

All 5 parameters have good schema descriptions (100% coverage). Description adds contextual value for output but doesn't enhance parameter details beyond schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description explicitly states it provides aggregated activity summary by action type, project, and day. Clearly distinguishes from sibling list_user_events.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly advises to use instead of list_user_events when counts are needed, providing clear when-to-use guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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