sonar_delete_screenshot_setPermanently delete a screenshot set and everything in it (screens, translations). Irreversible — confirm with the user before deleting work they may want. Requires a write-scope API key.
| Name | Required | Description | Default |
|---|---|---|---|
| set_id | Yes | Screenshot set id. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool as destructive (destructiveHint: true) and not read-only (readOnlyHint: false). The description adds critical behavioral context beyond annotations by specifying exactly what gets destroyed ('screenshot set and everything in it (screens, translations)'), emphasizing irreversibility, and noting authentication requirements ('write-scope API key'). No contradictions.
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 at two sentences with zero wasted words. Critical information (purpose, scope, irreversibility, user confirmation requirement, auth scope) is front-loaded in the first sentence, making it easy for an AI agent to quickly extract key decision-making facts.
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?
Given the tool has only one parameter, no output schema, and annotations already provide destructive and idempotent hints, the description is complete. It covers the action, permanent impact, user deliberation necessity, and auth requirements—leaving no gaps for an agent to safely invoke this high-risk tool.
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 100% with only one required parameter (set_id), which the schema already documents as 'Screenshot set id.' The description does not add new semantic meaning beyond what the schema provides, so a baseline score of 3 is appropriate.
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 verb 'permanently delete' and the target resource 'screenshot set and everything in it (screens, translations)', which matches the tool name and distinguishes it from sibling tools like sonar_delete_screenshot (which targets individual screenshots) and sonar_delete_product (which targets products).
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 explicitly warns that the action is irreversible and instructs the agent to 'confirm with the user before deleting work they may want', providing clear when-to-use guidance and cautioning against misuse. It also notes the requirement for a 'write-scope API key', which differentiates it from read-only operations.
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.