sonar_delete_productWRITE tool — delete a product and untrack its apps in the caller's Sonar workspace. Requires an Indie plan (trial counts) and an API key with the write scope.
| Name | Required | Description | Default |
|---|---|---|---|
| product_id | Yes | Sonar product UUID — the `id` returned by sonar_list_products or sonar_create_product. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare destructiveHint=true and readOnlyHint=false, so the description's 'WRITE tool' label is redundant. However, it does add valuable behavioral context about the side effect of untracking apps and the plan/scope requirements, which goes beyond annotations. No contradiction.
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 concise and front-loaded, with the essential info in the first sentence and additional requirements given succinctly in the second. Every sentence contributes value without fluff.
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 destructive tool with one parameter and no output schema, the description covers the purpose, side effects, and prerequisites. It could benefit from a note on what happens after deletion (e.g., irreversibility), but annotations already signal destructiveness, so this is 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?
The schema already covers the single parameter product_id with a clear description, and schema description coverage is 100%. The description does not add anything new about the parameter (e.g., format or validation details), so it stays at the baseline.
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 states the action: 'delete a product and untrack its apps in the caller's Sonar workspace.' It specifies the resource (product) and the side effect (untracking apps), properly framing the tool as a WRITE/destructive operation in context.
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 mentions requirements (Indie plan, write scope) and explicitly labels it a 'WRITE tool', but does not provide explicit guidance on when NOT to use it or when to use alternative tools (e.g., sonar_delete_alert, sonar_untrack_app). The requirement is useful context but lacks exclusions or comparisons.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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 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.
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.
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.