read_logs

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

Annotations already mark the tool as read-only (`readOnlyHint: true`). The description adds value by specifying the prerequisite (`driver_session` required for console logs) and listing the supported sources, which is not apparent from annotations alone. No contradictions found.

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 concise: two sentences that front-load the most critical context (`[Tauri Apps Only]`) and efficiently convey the tool's purpose, source options, and prerequisite. No superfluous text.

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 read-only log retrieval tool with six parameters and no output schema, the description covers the essential aspects: what the tool does, the sources, and the prerequisite. It could mention return format or error behavior but the given detail is sufficient for basic understanding.

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 high (83%), with most parameters already explained in the input schema. The description repeats the source options but does not add new semantic details for `lines`, `filter`, `since`, `windowId`, or `appIdentifier`. Baseline 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 identifies the tool as reading logs for Tauri apps, listing all four log sources (`console`, `android`, `ios`, `system`) and explicitly stating its debugging purpose. This distinguishes it from sibling tools like `driver_session` or `webview_execute_js`.

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 provides a prerequisite (`Requires active driver_session for console logs`) and limits usage to Tauri Apps. While it does not explicitly state when not to use this tool or mention alternatives, the context is sufficient for an AI to understand when to invoke it.

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