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Alert Events Feed

sonar_alert_events
Read-only

The detected alert events for your workspace, newest first — the same feed as the in-app Recent Alerts panel and the email digest: rank drops/gains, top-10 entries/exits, new rankings, rating drops, review spikes, and competitor changes, each with a type-specific payload (app/keyword names, old vs new values). Events only exist for alert types you've enabled rules for (sonar_set_alert); detection runs once daily. Poll with since to react to changes programmatically. Requires an Indie plan (trial counts).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoFilter to one alert type. Omit for all types.
limitNoMax events to return (1-200). Default 50.
sinceNoOnly events created at/after this ISO 8601 timestamp (e.g. "2026-08-01T00:00:00Z"). Use your last poll time to fetch only new events.
app_idNoFilter to events about one tracked app (Sonar app UUID or store id).

TDQS

A4.1/5.0
Behavior5/5

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

With only readOnlyHint:true in annotations, the description carries full weight and exceeds expectations by disclosing the feed's identity (same as the in-app Recent Alerts panel and email digest), the once-daily detection cadence, the type-specific payload shape (app/keyword names, old vs. new values), and the dependency on enabled alert rules. This gives the agent a realistic model of data freshness and availability that annotations could never convey.

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

Conciseness3/5

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

Every clause is information-dense and earns its place, but the entire description is essentially one 80-word run-on sentence held together by colons and em-dashes. It would benefit from breaking into 2-3 sentences to improve scannability, though the front-loading is decent since it leads with the core resource and ordering.

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?

Given there is no output schema and only minimal annotations, the description covers an impressive amount of necessary ground: what the payloads contain, when data becomes available (once daily), prerequisites (alert rules enabled), ordering semantics, and authentication requirements (Indie plan). This is nearly complete for an agent to use the tool effectively without additional discovery.

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?

The input schema provides 100% param coverage with clear documentation (enum values for type, 1-200 and default 50 for limit, ISO 8601 format with examples for since, and filtering semantics for app_id), which holds the baseline at 3. The description adds only marginal param value beyond the schema, such as reinforcing the since polling pattern ('Use your last poll time to fetch only new events' in the schema vs. 'Poll with since' in the description). No contradictions, but no meaningful semantic lift either.

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 clearly identifies the resource (workspace alert events), the ordering (newest first), and enumerates the distinct event types (rank drops/gains, top-10 entries/exits, rating drops, etc.), which effectively differentiates it from sibling alert tools. It loses a point because the lead is a noun phrase ('The detected alert events for your workspace') rather than an explicit imperative verb+resource construction like 'Lists the alert events...', making the invocation intent slightly less immediate.

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?

The description provides strong contextual guidance: events only exist for alert types with enabled rules (referencing sonar_set_alert), detection runs once daily (setting cadence expectations), and it prescribes the 'Poll with since' pattern for programmatic reaction. It also flags the Indie-plan requirement as a prerequisite. However, it never explicitly names an alternative tool for when NOT to use this one, missing the chance to contrast with siblings like sonar_list_alerts or the alert configuration tools.

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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TDQS

A3.9/5.0
Disambiguation5/5

Each tool targets a distinct action or data aspect within the ASO domain. Keyword-related tools are clearly separated by purpose (tracked keywords vs. research vs. suggestions vs. metrics), and competitive tools differentiate between reading landscape and generating new analysis. No two tools have overlapping functionality that would confuse an agent.

Naming Consistency3/5

Naming is a mix of verb-first (e.g., sonar_add_screenshot, sonar_create_product) and noun-first patterns (e.g., sonar_app_keywords, sonar_competitor_landscape). While all use snake_case and the 'sonar_' prefix is consistent, the lack of a uniform verb_noun structure makes it harder to predict tool names. The pattern is readable but inconsistent.

Tool Count2/5

With 47 tools, the server is over-scoped for a typical MCP server. Although the ASO domain is broad, many tools are granular (e.g., 10 screenshot tools, 10 keyword tools). This quantity exceeds the 25+ threshold for 'too many' as defined in the calibration, making it heavy for an agent to navigate comprehensively.

Completeness5/5

The tool surface covers the full ASO lifecycle: app discovery, keyword research, tracking and ranking, competitor analysis, revenue estimation, screenshot creation and export, alerts, and product management. There are no obvious gaps—every necessary operation for monitoring and optimizing app store presence is present, including both read and write actions.