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How one app is doing

app_story
Read-only

One app's story for a period in plain words, its key numbers (with ad spend when ads ran), and its highlights (sales, best days, new countries, reviews, problems, ads starting and stopping).

Input Schema

NameRequiredDescriptionDefault
appYesWhich app: its id or part of its name. Known apps: .
periodNo7d (default), 30d, 90d, 12m, today, yesterday, all, 14d, a day like 2026-09-21, or a range like 2026-09-01..2026-09-30.
sourceNoOnly one source's numbers (app_store, google_play, revenuecat, admob, mixpanel, sdk). Leave out for everything together, counted once.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior3/5

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

readOnlyHint=true already tells the agent this is a safe read. The description adds real behavioral value by disclosing the return contents (plain-words narrative, key numbers, highlights) and the conditional ad-spend inclusion, but it does not say what form the output takes (markdown? sections? length) or how sources are reconciled.

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?

A single, front-loaded sentence with every clause contributing (purpose, period, numbers, ad-spend condition, highlights). The parenthetical list is dense but not wasteful; it could be marginally clearer with a comma structure, but nothing is superfluous.

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?

With no output schema, the description must convey what comes back. It enumerates content categories reasonably well, but for a synthesized report tool it leaves open the response shape, length, and how the narrative is structured — gaps an agent may notice when parsing results.

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 all three parameters are documented in the schema, so the schema carries the parameter explanation. The description only echoes 'for a period' and 'one app' without adding syntax, defaults, or source-selection semantics beyond the schema — baseline 3 is appropriate.

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?

The description states what the tool produces: a narrative report for a single app over a period, plus key numbers and highlights. The enumerated contents (sales, best days, new countries, reviews, problems, ads starting/stopping) make the purpose concrete, but it never names a sibling to contrast with, so the distinction from how_are_my_apps (portfolio-wide) and app_topic is only implicit.

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

Usage Guidelines3/5

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

Usage is implied by 'One app's story for a period' — the agent can infer this is the single-app narrative summary versus the portfolio-level how_are_my_apps. However, there is no explicit when-to-use/when-not guidance and no named alternative for agents choosing between this and app_topic or timeline.

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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