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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is clear. The description adds behavioral context beyond that by specifying 'both sides' and 'ordered oldest to newest', which are not present in annotations or schema. No contradictions exist.

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 is front-loaded with the verb and resource, avoids redundancy, and contains no filler. Every word contributes meaning.

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 that the output schema exists, annotations cover the safety profile, and the schema fully describes parameters, the description provides complete context for a simple read operation. It covers purpose and adds the crucial ordering detail, making it sufficient for the tool's complexity.

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%, so all parameters (chat_id, after, limit, before) are already documented. The description does not add semantic meaning beyond reinforcing that chat_id is the identifier; it does not explain parameter syntax or usage details.

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 uses a specific verb ('Read') and resource ('both sides of one LINE conversation by chat ID') with an additional detail about ordering ('ordered oldest to newest'). This directly distinguishes it from sibling tools like list_chats, search_messages, and get_recent_activity.

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 clearly implies the tool is for retrieving a full conversation given a chat ID, but it does not explicitly mention alternatives or when not to use it. Context from sibling names helps fill this gap, earning a 4 rather than a 5.

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?

Annotations already establish readOnlyHint and destructiveHint, but the description adds value beyond them by disclosing the default exclusion of official accounts and the grouped-by-chat return structure. This gives the agent practical expectations without needing to inspect the schema. While pagination/limits are not mentioned, the read-only nature and output schema reduce the need.

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?

Two sentences, perfectly front-loaded: first the main action, then a use case, then a default behavior. Every sentence contributes unique information with no redundancy, achieving high informational density in minimal space.

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 query tool with full parameter documentation, an output schema, and safety annotations, the description covers the core purpose, a concrete use case, and a key behavioral default. It does not describe pagination or the specific payload of messages, but the output schema and parameter descriptions cover those details. It is sufficiently complete for an agent to invoke correctly.

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 each parameter clearly described. The description only reinforces the include_official default ('Official accounts are excluded by default') without adding new parameter semantics or usage details beyond what the schema already provides. 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 opens with a specific verb+resource: 'Return recent conversations with both sides of their messages, grouped by chat.' It clearly identifies what the tool does and differentiates it from siblings like get_messages or list_chats by emphasizing grouping and the inclusion of both message sides. The note about official accounts being excluded by default adds a distinguishing behavioral detail.

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?

'Use this for daily or weekly briefs' provides a clear contextual use case, which guides when the agent should select this tool. However, it does not explicitly state when not to use it or name alternative tools for other scenarios, so exclusions are only implicit.

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?

Annotations already declare read-only and non-destructive behavior. The description adds context by specifying what is checked (readability and freshness), which goes beyond the annotations. 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 a single, concise sentence that starts with the action verb and directly states what the tool does. It is efficient with no wasted words.

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's simplicity and the presence of an output schema, the description sufficiently covers what the tool does. It includes the key behavior (readability and freshness) without needing to explain return values, which are handled by the output schema.

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 does not need to explain them. The baseline for 0 params is 4, and the description adds no irrelevant parameter information.

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 checks whether the local LINE Desktop database is readable and how fresh it is. It uses a specific verb ('check') and resource (database), and it distinguishes itself from data-retrieval siblings like get_messages and list_chats.

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 implies usage for verifying database accessibility and freshness, but it does not explicitly state when to use this tool versus the sibling tools. It gives context but lacks explicit guidance or exclusions.

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?

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description adds valuable behavioral context: it returns stable chat IDs and excludes official accounts by default, which are not inferable from annotations alone.

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?

Three sentences, all informative and front-loaded. No redundant phrasing or filler; every sentence contributes purpose, usage, or an important exclusion.

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?

The tool has a rich input schema (5 params, all documented), an output schema, and annotations. The description covers purpose, usage timing, and key filtering behavior, making it complete for effective tool selection and invocation.

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 100% coverage with each parameter described (limit, unread_only, name_contains, updated_after, include_official). The description adds no additional parameter syntax or format details, so 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 states a specific verb ('Find') and resource ('LINE conversations'), and clarifies that it returns stable chat IDs, which directly distinguishes it from sibling tools like get_messages and search_messages.

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?

Explicitly instructs to use this tool before get_messages when the chat ID is unknown, providing clear when-to-use guidance. It also notes the exclusion of official accounts unless requested, which sets expectations for filtering behavior.

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?

Annotations already declare readOnlyHint and destructiveHint false. The description adds the behavioral fact that official accounts are excluded by default, and clarifies the scope as both sent and received messages. This goes beyond the structured annotations.

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 three short sentences that front-load the core purpose and quickly cover optional restrictions and default behavior. No unnecessary words.

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 schema fully documents all six parameters and an output schema exists, the description sufficiently covers purpose, scope, and default filtering. It doesn't need to explain return values, though it could have noted the literal-text behavior, which is in the schema anyway.

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 coverage is 100%, so parameters are fully described in the schema. The description only restates 'chat and time' restrictions without adding new meaning to individual parameters, earning the baseline 3.

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 it searches message text across both sent and received LINE messages, providing a specific verb and resource. It also notes the default exclusion of official accounts, which distinguishes it from more general message tools like get_messages.

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 does not explicitly say when to use this tool instead of siblings like get_messages or get_recent_activity. It implies use for text searching with optional filters, but lacks explicit exclusions or alternative recommendations.

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