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Save Usage settings

save_usage
Destructive

PARTIAL SAVE: writes ONLY the 'Usage' field of TitlePublicConfigurationModel; all other v1/v2 fields stay untouched. Retention policy for the player's activity history (Usage). The engine keeps a rolling window of per-day records and folds everything older into monthly totals, then months of finished years into yearly totals — otherwise the per-day map grows forever inside the hottest document on the platform. WARNING: the fold is IRREVERSIBLE, per-day detail outside the window is gone for good. Do not lower DailyWindowDays below 400 without also lowering the analytics range cap: publisher analytics (DAU/WAU/MAU, retention cohorts, funnels) is computed lazily from those very per-day records, accepts ranges of up to 366 days, and needs 30 extra preceding days per requested day for MAU. Also holds SessionIdleTimeoutMinutes: how many minutes of silence end a session (default 30, the same rule Firebase/GA4 use, so the two reports stay comparable). The session boundary is decided by the SERVER from the player's last activity — the client's IsNewSession flag is not trusted for counting. Leave every field null unless you have a specific reason — the defaults (enabled, 400-day window, 30-minute session gap) are what the analytics horizon was sized against.

Input Schema

NameRequiredDescriptionDefault
valueYesNew value for the Usage field.
title_idYesTitleID, для которого сохраняются данные.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already declare destructiveHint=true, but the description goes well beyond by explaining that the fold is irreversible, per-day detail is lost for good, analytics depends on those records, and session boundaries are server-decided rather than client-trusted. It provides rich context about side effects, default behavior, and operational constraints without contradicting the annotations.

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?

The critical 'PARTIAL SAVE' scope and irreversible WARNING are front-loaded, and the length is justified by the destructive, analytics-coupled behavior. Some sentences duplicate schema text and the paragraph is dense, but every sentence earns its place.

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

Completeness5/5

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

With no output schema, the description carries the full burden and succeeds: it explains mutation scope, irreversibility, analytics coupling, session semantics, and default posture. An agent has everything needed to decide and safely invoke this destructive save.

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 coverage is 100% and each nested field is fully described in the input schema, including defaults, warnings, and consequences. The description largely repeats that same field-level information, adding only the blanket instruction to leave fields null, so the baseline of 3 is appropriate.

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?

States a specific verb and resource with precise scope: writes ONLY the 'Usage' field while leaving other v1/v2 fields untouched. This distinguishes it from broader save_* siblings such as save_title_data and clearly communicates exactly what is being saved.

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

Usage Guidelines4/5

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

Provides a clear default posture ('leave every field null unless you have a specific reason') and warns against lowering DailyWindowDays without adjusting the analytics cap. However, it does not name the read-only sibling get_usage or explicitly compare itself to save_title_data, so routing remains implied rather than explicitly stated.

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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