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

No annotations are provided, so the description must disclose behavior. It adds context that the database is local and that it checks import status, implying a safe read-only operation, but it doesn't explicitly state side-effect-free behavior, authentication requirements, or rate limits.

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 two crisp sentences: the first states the core function, the second gives a concrete use case. No waste, front-loaded.

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 zero-parameter stats tool with an output schema, the description sufficiently covers purpose, usage context, and domain context (local database, Takeout import). There are no meaningful gaps.

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 tool has zero parameters, so the baseline is 4 per the rubric. The description naturally introduces no parameter confusion, and the output schema handles return value documentation.

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 the tool returns counts and date range for the local activity database, which is a specific action on a specific resource. It differentiates from sibling tools by focusing on aggregate statistics rather than searching (search_activity) or general database info (get_db_info).

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 tells the user to use this tool to check whether Takeout data has been imported and which products exist, providing a clear use case. It doesn't name alternatives, but the context makes it distinct from siblings.

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 supplied, so the description carries the full burden. It discloses a key behavioral trait: no Google network calls are made, which is critical for an agent to know. While it doesn't explicitly state 'read-only' or describe error handling, the simple return of path and existence suggests a safe, non-mutating operation, and offering the no-network detail is valuable beyond the schema.

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 sentence that conveys purpose, scope, and a key constraint without any redundant or extraneous information. It is front-loaded with the primary action and resource.

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 parameters and an output schema present, the description sufficiently explains what the tool does and its distinguishing trait (no network calls). This is complete enough for an agent to select it appropriately among siblings, as it clearly covers the tool's role and usage context.

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 tool has zero parameters, so the description has no parameter semantics to add beyond the empty schema. According to the baseline for 0 params, a score of 4 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 tool's function with a specific verb ('return') and identifies the exact resources: the local DB path and file existence. It distinguishes itself from sibling tools by explicitly noting it makes 'no Google network calls', which contrasts with the likely network-based search and activity 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?

The description provides clear context: this tool is for local database path and existence checking without network calls. It does not explicitly name alternatives or exclusion criteria, but the 'no Google network calls' phrase implies usage when avoiding network calls is desired, giving reasonable guidance relative to siblings.

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 behavioral burden. It clearly indicates this is a search operation, which implies read-only, and adds useful context like 'ingested' data and FTS5. It does not explicitly state non-mutating behavior or edge cases, but overall is transparent for a search tool.

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 appropriately sized for a 5-parameter tool. It opens with a one-sentence purpose, then uses a clear, structured Args list. Every sentence adds value, and there is no 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?

Given the complexity (5 params, 1 required), the description covers all parameters, usage context, and a special case. Since an output schema exists, return values need not be explained. The tool context and sibling names are clear from the description.

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 input schema has 0% description coverage, but the description fully compensates. It explains each parameter in plain language, provides examples for date formats, enumerates allowed product values, and specifies limits/defaults. This is exactly the needed semantic enrichment.

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 a specific verb and resource ('Search the user's ingested Google activity by keyword'), clearly distinguishing it from sibling tools like get_activity_stats and get_db_info. It also notes 'full-text' search, clarifying the method.

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?

Provides explicit context for using the tool, including a specific scenario ('Use empty string with filters to list recent activity'). However, it does not compare to alternatives or state when not to use this tool, such as when statistics or database info would be more appropriate.

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