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

No annotations are provided, so the description carries the full burden. It states it 'retrieves' data, implying a read-only operation, but doesn't disclose behavioral traits like authentication needs, rate limits, error handling, or what happens if the ID is invalid. This is a significant gap for a tool with no annotation coverage.

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, efficient sentence with zero waste. It's front-loaded with the core purpose and appropriately sized for a simple retrieval tool.

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 no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., lifelog details, format), error conditions, or prerequisites. For a retrieval tool with three parameters, this leaves the agent with insufficient 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?

Schema description coverage is 100%, so the schema fully documents all parameters. The description adds no additional meaning beyond what the schema provides, such as explaining the purpose of 'includeMarkdown' or 'includeHeadings' in context. Baseline 3 is appropriate when the schema does the heavy lifting.

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 ('retrieves') and resource ('a single lifelog or Pendant recording'), making the purpose evident. However, it doesn't explicitly differentiate from sibling tools like 'limitless_list_lifelogs_by_date' or 'limitless_search_lifelogs', which also retrieve lifelogs but with different filtering mechanisms.

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 no guidance on when to use this tool versus alternatives. It doesn't mention that this is for retrieving a specific lifelog by ID, whereas siblings retrieve lists or search results, leaving the agent to infer usage from the name alone.

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 provided, so the description carries the full burden. It mentions the tool is for 'getting raw log data' and analysis, but doesn't disclose behavioral traits like whether it's read-only, has rate limits, authentication needs, or what the response format looks like. The description adds minimal context beyond the basic purpose.

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 core purpose in the first sentence. The second sentence adds useful context about usage. Both sentences earn their place, though it could be slightly more structured (e.g., explicitly mentioning sibling tools).

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 no annotations and no output schema, the description is moderately complete for a list tool. It covers the purpose and usage context but lacks details on behavioral traits (e.g., pagination, error handling) and output format, which are important for a tool with 6 parameters and no structured output documentation.

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 the schema already documents all parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema, such as explaining how 'date' interacts with 'timezone' or the implications of 'includeMarkdown'. Baseline 3 is appropriate when the schema does the heavy lifting.

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 purpose: 'Lists logs/recordings for a specific date.' It specifies the verb ('Lists') and resource ('logs/recordings'), but doesn't explicitly differentiate from siblings like 'limitless_list_lifelogs_by_range' or 'limitless_list_recent_lifelogs' beyond the date specificity.

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 some usage guidance: 'Best for getting raw log data which you can then analyze for summaries, action items, topics, etc.' This implies when to use it (for raw data analysis), but doesn't explicitly state when not to use it or name alternatives among the sibling tools.

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 provided, the description carries the full burden of behavioral disclosure. It mentions the tool is for listing raw log data, implying a read-only operation, but does not specify permissions, rate limits, or response format details. The description adds some context about data analysis use but lacks comprehensive behavioral traits like pagination or error handling.

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 front-loaded with the core purpose in the first sentence and adds a concise usage guideline in the second. Both sentences earn their place by providing clear value without redundancy, making it efficient and well-structured.

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 complexity (7 parameters, no output schema, no annotations), the description is moderately complete. It covers purpose and usage but lacks details on behavioral aspects like response format, error cases, or prerequisites. Without annotations or output schema, more context on what the tool returns would be beneficial for full completeness.

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 description coverage is 100%, so the schema already documents all 7 parameters thoroughly. The description does not add any parameter-specific semantics beyond what the schema provides, such as explaining interactions between parameters or default behaviors. Baseline 3 is appropriate as the schema handles parameter documentation adequately.

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 ('Lists') and resource ('logs/recordings') with specific scope ('within a date/time range'). It distinguishes from siblings by emphasizing raw log data for analysis, unlike tools like 'limitless_get_lifelog_by_id' (single log) or 'limitless_list_lifelogs_by_date' (date-specific).

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 for when to use this tool ('Best for getting raw log data which you can then analyze for summaries, action items, topics, etc.'). However, it does not explicitly state when not to use it or name specific alternatives among the siblings, such as 'limitless_list_recent_lifelogs' for recent logs without date ranges.

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 provided, so the description carries the full burden. It mentions sorting ('newest first') and the nature of the data ('raw log data'), which adds useful context. However, it lacks details on permissions, rate limits, pagination, or what the response format looks like (e.g., structure of returned logs). This leaves gaps for a tool with no annotation coverage.

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 well-structured with two sentences: the first states the core functionality, and the second provides usage guidance. Every sentence adds value without redundancy, making it easy to parse and front-loaded with key information.

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 no annotations and no output schema, the description is moderately complete. It covers purpose and usage but lacks behavioral details (e.g., response format, error handling) and doesn't fully compensate for the absence of structured output information. For a list tool with 4 parameters, it's adequate but has clear gaps in transparency.

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 the schema fully documents all 4 parameters (limit, timezone, includeMarkdown, includeHeadings). The description doesn't add any parameter-specific information beyond what's in the schema, such as explaining how 'limit' interacts with 'recent' or the implications of the boolean flags. Baseline 3 is appropriate when schema does the heavy lifting.

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 purpose: 'Lists the most recent logs/recordings (sorted newest first).' It specifies the verb ('lists'), resource ('logs/recordings'), and sorting behavior. However, it doesn't explicitly differentiate from siblings like 'limitless_list_lifelogs_by_date' or 'limitless_list_lifelogs_by_range' beyond mentioning 'recent' and 'newest first.'

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 usage context: 'Best for getting raw log data which you can then analyze for summaries, action items, topics, etc.' This implies when to use it (for raw data analysis) but doesn't explicitly state when not to use it or name alternatives among the sibling tools, such as when date-based filtering is needed.

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 provided, the description carries full burden. It discloses important behavioral traits: the search is limited to recent logs, it searches both title and content, and it's keyword-based (not conceptual). However, it doesn't mention authentication requirements, rate limits, error conditions, or what the response format looks like. For a search tool with 6 parameters, this leaves significant behavioral aspects undocumented.

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 concise sentences with zero waste. Each sentence adds distinct value: first states the core function, second provides critical usage restrictions, third clarifies scope limitation. The description is appropriately sized and front-loaded with essential information.

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 search tool with 6 parameters and no output schema, the description provides good purpose and usage guidance but lacks behavioral details about authentication, rate limits, error handling, and response format. The absence of annotations means the description should compensate more for behavioral transparency, which it only partially addresses. It's adequate but has clear gaps for a tool of this 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 the schema already documents all parameters thoroughly. The description adds some context about 'recent' logs which relates to fetch_limit's scope, but doesn't provide additional parameter semantics beyond what's in the schema. This meets the baseline expectation when schema coverage is complete.

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 purpose with specific verbs ('performs a simple text search') and resources ('within the title and content of *recent* logs/Pendant recordings'). It distinguishes from siblings by specifying it's for keyword searches only, unlike list/retrieve siblings like limitless_list_lifelogs_by_date or limitless_get_lifelog_by_id.

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 states when to use ('Use ONLY for keywords, NOT for concepts like 'action items' or 'summaries'') and provides context about scope ('Searches only recent logs (limited scope)'). This gives clear guidance on appropriate vs. inappropriate use cases, though it doesn't name specific alternative tools.

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