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Alpha4-Labs

Loyalteez MCP Server

by Alpha4-Labs

loyalteez_log_activity

Log voice time, messages, reactions, or presence to track daily caps and return rewards earned, progress, and cap status.

Instructions

Track voice time, messages, reactions with daily caps. Returns reward earned, daily progress, and cap status.

See also: loyalteez://docs/shared-services/activity-service

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNoCount of activities (for messages/reactions)
brandIdNoYour brand wallet address. If not provided, uses LOYALTEEZ_BRAND_ID environment variable.
platformYesPlatform: "discord" | "telegram" | "web" | etc.
activityTypeYesType of activity to log
userIdentifierYesUser identifier (platform_userId@loyalteez.app or email)
durationMinutesNoDuration in minutes (for voice activity)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, the description carries the full burden, and it does disclose two useful behavioral traits: activities are subject to daily caps and the call returns reward, progress, and cap status. It omits other important traits for a mutation tool, such as authentication requirements, idempotency, or what happens when the cap is already reached.

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

Conciseness4/5

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

Two tight sentences plus a doc link, with the core purpose and the return shape front-loaded and no wasted prose. The trailing 'See also' is compact and does not pad the definition.

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

Completeness3/5

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

Because there is no output schema, the description correctly compensates by naming the return fields (reward earned, daily progress, cap status). With no annotations and no sibling differentiation, though, it leaves gaps around permissions, error/cap-exceeded behavior, and how it relates to the other tracking tools.

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?

Schema description coverage is 100%, so all six parameters are already documented in the schema, including which activity types take count vs durationMinutes. The description adds no syntax or format detail beyond the schema, which is the correct baseline of 3 when the schema does the heavy lifting.

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

Purpose4/5

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

States a specific verb ('Track') and the resources it applies to (voice time, messages, reactions), which is more than a restatement of the name. However, it does not distinguish itself from the near-identical sibling loyalteez_track_event or loyalteez_process_third_party_event, so an agent cannot route between them from the description alone.

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

Usage Guidelines2/5

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

The description mentions 'daily caps' as a context clue but never states when to use this tool versus loyalteez_track_event or the other event-tracking siblings. The 'See also' pointer to external docs is a reference, not usage guidance, so an agent must infer selection criteria.

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