App Store Change Intelligence

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

With no annotations, the description carries the full burden and does disclose two useful behavioral facts: a per-item cost of $0.03/app and a hard cap of 50 targets. It says nothing about auth requirements, rate limits, failure handling, or what a scan response contains, leaving the disclosure incomplete for a batch/priced operation.

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

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

A single tight sentence with no waste, and the batch ceiling and cost are front-loaded. The leading price fragment is slightly abrupt but still efficient.

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

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

For a batch tool with one undocumented parameter, no annotations, and no output schema, the description should explain the input identifier format and what the scan returns beyond three field names. The cost and cap disclosures help, but key invocation details are missing.

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

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

The single 'targets' parameter has 0% schema description coverage, so the description must compensate. It implies the array holds App Store apps limited to 50, but never specifies the identifier format (app ID, bundle ID, URL) or whether entries must be unique, so compensation is only partial.

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

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

States a specific verb ('scan') and resource ('App Store apps') with an explicit batch scope of up to 50, and the parenthetical lists what the scan surfaces (version, rating, recent negatives). It does not distinguish itself from siblings like app_snapshot or app_intel_report, so it stops short of a 5.

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

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

The description gives no when-to-use context and never names an alternative among app_intel_report, app_landscape, app_review_changes, or app_snapshot. The pricing note hints at cost sensitivity but is not usage guidance.

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

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

No annotations are provided, so the description carries the full behavioral burden. It usefully discloses the $0.50 cost, but it omits whether the operation is read-only, whether authentication or rate limits apply, and what format or depth the report returns.

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

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

The description is extremely short and front-loads the cost and report type, so it wastes no words. However, it is under-specified for a tool whose schema and annotations provide almost no supporting information.

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

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

With no annotations, no output schema, and 0% schema description coverage, the description should compensate by explaining the target input and output expectations. It only states the cost and report topic, leaving the agent without enough context to invoke the tool confidently.

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

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

The single required parameter 'target' has 0% schema description coverage and is not explained in the description at all. An agent cannot tell whether target expects an app ID, URL, package name, or search phrase.

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

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

The description clearly identifies the report type as sentiment and negative-review focused with takeaways, which is a specific resource. It does not explicitly compare itself to siblings like app_landscape or app_review_changes, but the intended output is distinguishable from those tools.

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

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

There is no guidance on when to use this tool versus the sibling tools such as app_landscape, app_snapshot, or app_review_changes. The price and report type imply a one-off paid analysis, but no explicit usage context or exclusions are provided.

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

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

No annotations are provided, so the description carries the full burden. It discloses the price ($5), the maximum number of apps, and some output content (rating ranking and risk flags), which helps characterize it as a paid analysis report. However, it omits permissions, read-only status, rate limits, and return format details.

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

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

The description is a single, tight sentence with no redundant padding. The price and scope are front-loaded, though the phrase 'app landscape' repeats the tool name rather than leading with a clear action.

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

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

For a simple one-parameter tool with no annotations or output schema, the description provides basic scope, cost, and output hints. It still leaves gaps around target format and when to select this tool over siblings, but it is minimally adequate.

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

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

Schema description coverage is 0% for the single 'targets' parameter. The description partially compensates by implying the targets are apps and that there can be up to 10, but it does not explain the expected string format or what a valid target identifier looks like.

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

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

The description states it produces an 'app landscape' across up to 10 apps with rating ranking and risk flags, which gives a rough sense of scope and output. However, it lacks an explicit verb and leaves 'landscape' undefined, so the tool's exact action is vague. It also does not distinguish itself from siblings such as app_batch_scan or app_intel_report.

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

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

The description gives a cost and a maximum scope ('up to 10 apps') but provides no guidance on when to use this tool versus alternatives. There are no exclusions, prerequisites, or routing hints toward sibling tools.

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

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

With no annotations, the description carries the full burden and handles the most decision-critical trait: it is a paid call ($0.05 USDC on Base via x402), which an agent must know before invoking. It also discloses what it compares against (history) and what triggers a flag. It omits any note on auth setup, rate limits, or whether repeated calls re-charge.

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

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

Front-loads the payment cost first, then the behavioral summary, then use cases in a compact two-sentence structure. Dense and efficient, though the quoted use-case list is slightly padded.

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

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

For a paid, single-parameter tool with no output schema and no annotations, the description covers cost and return content reasonably well, but the schema itself is bare and 'target' is undefined, leaving a critical gap an agent cannot resolve from any structured field.

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

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

There is one parameter, 'target', with 0% schema description coverage, and the description never explains what it accepts (app ID, bundle ID, package name, or URL) or its format. This leaves the only required input entirely undefined for the agent.

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

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

States a specific verb and resource (review change detection vs history) and enumerates concrete outputs: new reviews, removed reviews, and flagged 1-2 star negatives. An agent can distinguish this from app_snapshot or app_landscape without opening their schemas.

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

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

Gives clear triggering contexts: 'did our app get bad reviews', review monitoring, complaint/bug outbreak alerts, reputation-risk tracking after a release. Strong when-to-use guidance, though it never names a sibling alternative or states when NOT to use it.

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

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

With no annotations, the description carries full behavioral burden. It usefully discloses the cost ('Free') and the shape of the returned data, and implies a read-only lookup, but says nothing about auth requirements, rate limits, or failure behavior for a missing/invalid app id.

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

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

Two short, front-loaded sentences with zero filler; the cost qualifier and payload come first, the parameter constraint second.

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

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

For a single-param lookup with no output schema, the description reasonably covers what is returned, but omits auth/rate-limit context and any guidance on the request/response format that an unannotated tool would benefit from.

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

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

Schema coverage is 0% and the single parameter is only typed as a bare string. The description compensates by defining 'target' as a numeric app id, which is essential invocation knowledge the schema omits.

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

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

States a concrete resource (App Store app) and enumerates the payload (current version, rating, recent reviews), so the agent knows exactly what data it yields. It is clear but does not explicitly differentiate itself from siblings like app_intel_report or app_landscape.

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

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

The leading 'Free' hints at a cost-based reason to prefer this over siblings, but there is no explicit when-to-use, when-not-to-use, or named alternative. The agent must infer routing from the sibling names alone.

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