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adjust run report

adjust_run_report

Read-onlyIdempotent

Read an Adjust attribution and performance report for one allowlisted app, preserving native totals, warnings, currency, UTC offset, and explicit truncation.

Instructions

Read an attribution/performance report for one allowlisted Adjust app. Preserves native totals, warnings, attribution options, currency and UTC offset. Missing metrics are null; ratios are native fractions. A truncated or partial result is not a complete extraction.

Input Schema

Name	Required	Description	Default
`limit`	No	Display row limit only; truncation is explicit and native totals are preserved.
`endDate`	Yes	Last date of the reporting period, in YYYY-MM-DD format, on or after startDate.
`filters`	No	Filters combined according to this tool's query schema. Use provider field names and the declared operators.
`metrics`	No	Native or documented calculated metric names to request. Check compatibility with the selected dimensions.
`osNames`	No	Operating system filter, for example ios or android. Keep os_name in dimensions to compare platforms.
`appToken`	Yes	Exact Adjust application token from ADJUST_APP_TOKENS. Applications are separate from advertising accounts.
`currency`	No	Explicit ISO currency for money metrics. Keep the same currency across comparisons.
`startDate`	Yes	First date of the reporting period, in YYYY-MM-DD format.
`utcOffset`	No	Fixed UTC offset; +00:00 by default. Split local-date comparisons if the offset changes during the period.	+00:00
`dimensions`	No	Native reporting dimensions. Validate compatibility with the selected metrics.
`adSpendMode`	No	Native source of ad spend. Keep the same mode across comparisons and avoid counting overlapping spend twice.	network
`reattributed`	No	Include all users, reattributed users only, or users without reattribution.	all
`cohortMaturity`	No	Include current cohort values or use mature-only mode, which may zero immature cohorts.	immature
`iapRevenueMode`	No	In-app revenue percentage. Retain the same setting across comparisons.	GROSS_100
`attributionTypes`	No	Optional engagement filter. Omit for an unfiltered report including native organic data. Empty types in output means no engagement filter.
`attributionSource`	No	Assign activity to the first install source or the native dynamic reattribution source.	dynamic

Output Schema

Name	Required	Description	Default
`result`	Yes	Original tool result: parsed JSON when the text is JSON, otherwise the text or multiple MCP content blocks. Provider fields depend on the selected query.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Oct 23, 2026

TDQS

A3.5/5.0

Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, open-world), so the description does not need to. It goes further by disclosing result semantics that matter operationally: native totals and warnings are preserved, missing metrics are null rather than zero, ratios are native fractions, and truncation is explicit so a partial result must not be treated as a complete extraction.

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?

Four tight sentences with the core purpose front-loaded and no filler. A couple of the sentences (null handling, native fractions) read as output-contract statements that partly duplicate what an output schema would express, but they are not wasted.

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?

With a full schema, rich annotations and an output schema present, the description covers the genuinely risky behaviors an agent needs: truncation, nulls, ratio units, and consistent settings across comparisons. The remaining gap is routing guidance against adjust_compare_periods, which no structured field supplies.

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 every parameter already carries a description, including limit-vs-truncation, filter operators, and dimension/metric compatibility, so the schema does the heavy lifting. The description only reinforces the currency/UTC-offset and attribution-option defaults; it adds little parameter-specific meaning beyond that.

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?

"Read an attribution/performance report" names a specific verb and resource, and "for one allowlisted Adjust app" fixes the scope to a single app token. It never distinguishes itself from the closest sibling, adjust_compare_periods, which is the tool an agent most plausibly confuses it with.

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 only usage cue is the implicit scope (one allowlisted app), with no statement of when to choose this over adjust_compare_periods or the catalog/listing siblings. No exclusions, no preconditions such as app-token allowlisting or dimension/metric compatibility are stated in the description.

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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