Limitless MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Most tools have distinct purposes, such as analyze_speaker for person-specific analytics, detect_meetings for meeting extraction, and get_by_natural_time for time-based queries. However, there is some overlap between get_full_transcript and get_raw_transcript, as both handle transcript data, which could cause confusion about when to use each.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern with the 'limitless_' prefix, such as limitless_analyze_speaker, limitless_detect_meetings, and limitless_get_daily_summary. This uniformity makes the set predictable and easy to navigate.
Tool Count5/5
With 14 tools, the count is well-scoped for a lifelog analysis server, covering key operations like retrieval, analysis, search, and summarization. Each tool serves a clear purpose without feeling excessive or insufficient.
Completeness5/5
The tool set provides comprehensive coverage for lifelog management, including CRUD-like operations (e.g., get_by_id, list_by_date), analysis (e.g., detailed_analysis, daily_summary), search (e.g., search_conversations_about), and specialized functions (e.g., extract_action_items). No obvious gaps are present for the domain.
Average 3.6/5 across 14 of 14 tools scored. Lowest: 2.9/5.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 2 community issues answered or closed in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
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If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions analytics but doesn't specify whether this is a read-only operation, what permissions are required, how data is sourced, or any rate limits. For a tool that analyzes conversations (potentially sensitive data), this lack of transparency is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads key information ('Detailed analytics for conversations with a specific person') and lists specific metrics. It avoids unnecessary words, though it could be slightly more structured by separating metrics with commas or bullet points for readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of analyzing conversations with metrics like 'relationship insights,' no annotations, and no output schema, the description is incomplete. It doesn't explain what the analytics output looks like, how data is processed, or any limitations (e.g., data availability, privacy considerations). For a tool with behavioral and output uncertainty, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 three parameters (participant_name, time_expression, timezone) with clear descriptions. The description adds no additional parameter semantics beyond what's in the schema, such as examples for 'time_expression' or clarifications on 'participant_name' format. 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Detailed analytics for conversations with a specific person' with specific metrics like 'speaking time, topics, interaction patterns, and relationship insights.' It uses a specific verb ('analyze') and resource ('conversations'), but doesn't explicitly differentiate from siblings like 'limitless_get_detailed_analysis' or 'limitless_search_conversations_about' which might have overlapping functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 any prerequisites, exclusions, or compare it to sibling tools such as 'limitless_get_detailed_analysis' or 'limitless_search_conversations_about,' leaving the agent to infer usage context based solely on the tool name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'intelligent analysis' but doesn't specify what that entails (e.g., AI processing, accuracy, or limitations). It lacks details on output format (e.g., structured data vs. raw text), error handling, or performance characteristics (e.g., processing time). For a tool with no annotations, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core functionality. It avoids redundancy and wastes no words, making it easy to parse. However, it could be slightly more structured by separating key points (e.g., detection vs. analysis), but this is minor.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (intelligent analysis tool with no annotations and no output schema), the description is incomplete. It doesn't explain what the output looks like (e.g., list of meetings with details), behavioral traits, or how it interacts with sibling tools. For a tool that performs extraction and analysis, more context is needed to guide effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 three parameters (time_expression, timezone, min_duration_minutes) with descriptions. The tool description adds no additional parameter semantics beyond what's in the schema, such as examples or constraints. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but doesn't need to.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Automatically detect and extract meetings/conversations from lifelogs with intelligent analysis of participants, topics, action items, and key information.' It specifies the verb ('detect and extract'), resource ('meetings/conversations from lifelogs'), and scope of analysis. However, it doesn't explicitly differentiate from sibling tools like 'limitless_search_conversations_about' or 'limitless_get_detailed_analysis', which might have overlapping functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 prerequisites (e.g., needing lifelogs to exist), exclusions, or comparisons to siblings like 'limitless_list_lifelogs_by_date' (which might list logs) or 'limitless_extract_action_items' (which might focus on specific aspects). Usage is implied but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'intelligently extract' and 'smart pattern recognition,' which hint at AI-driven processing, but lacks details on error handling, rate limits, authentication needs, or output format. For a tool with no annotations and complex functionality, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded: the first sentence states the core functionality, and the second adds context. Both sentences are relevant, with no wasted words. However, it could be slightly more structured (e.g., separating capabilities from use cases).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (AI-driven extraction with 4 parameters), no annotations, and no output schema, the description is incomplete. It doesn't explain what the output looks like (e.g., list of action items with details), error conditions, or how extraction works with the parameters. More context is needed for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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. The description doesn't add any parameter-specific information beyond what's in the schema (e.g., it doesn't explain how 'time_expression' interacts with extraction). Baseline 3 is appropriate as the schema handles parameter semantics adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'extract action items and tasks from conversations' with specific capabilities like 'context, priority analysis, and smart pattern recognition.' It distinguishes from siblings by focusing on task extraction rather than analysis, detection, or retrieval of transcripts/lifelogs. However, it doesn't explicitly differentiate from all siblings (e.g., 'limitless_analyze_speaker' might also involve conversation analysis).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides minimal usage guidance: 'Perfect for getting your todo list from meetings' implies use in meeting contexts, but it doesn't specify when to use this tool versus alternatives like 'limitless_get_detailed_analysis' or 'limitless_search_conversations_about' for similar purposes. No explicit when-not-to-use or prerequisite information is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states 'Retrieves' implying a read-only operation, but doesn't disclose behavioral traits such as authentication requirements, rate limits, error handling, or what happens if the ID is invalid. For a tool with no annotations, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core action, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
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., the structure of a lifelog, what 'markdown' or 'headings' content entails), leaving the agent uncertain about the response format. For a retrieval tool with rich data, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 the three parameters. The description adds no additional meaning beyond implying retrieval by ID, which is already covered in the schema. This meets the baseline of 3 where the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 understandable. However, it doesn't explicitly differentiate from sibling tools like 'limitless_get_full_transcript' or 'limitless_get_detailed_analysis' that might also retrieve lifelog content but with different scopes or formats.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 scenarios like needing a specific ID, nor does it reference sibling tools (e.g., 'limitless_list_lifelogs_by_date' for listing multiple lifelogs), leaving the agent without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. While it mentions the tool 'preserves precision without generalization', it doesn't describe what the analysis returns, how results are structured, whether it processes transcripts or other data sources, or any performance characteristics. Significant behavioral aspects remain undocumented.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured in two sentences with zero wasted words. The first sentence defines the analysis focus, and the second specifies ideal use cases. Every phrase adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 4-parameter analysis tool with no annotations and no output schema, the description is incomplete. It doesn't explain what data source is analyzed (transcripts? lifelogs?), what format the analysis returns, or how results are presented. The technical focus is clear, but operational context is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, providing complete parameter documentation. The description adds minimal value beyond the schema, mentioning 'technical details' and 'exact figures' which loosely relate to the 'focus_area' and 'preserve_precision' parameters but without additional semantic context. Baseline 3 is appropriate given the comprehensive schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs 'deep analysis focused on technical details, exact figures, scientific terminology, and specific information' with a verb+resource pattern. It distinguishes itself from siblings by emphasizing precision and technical focus, though it doesn't explicitly name alternative tools for different analysis types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides implied usage context ('ideal for extracting exact specifications, measurements, and technical discussions') but doesn't explicitly state when to use this tool versus alternatives like 'limitless_get_daily_summary' or 'limitless_get_full_transcript'. No explicit exclusions or comparisons to sibling tools are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. While it mentions the tool 'preserves technical terminology' and avoids formatting/summarization, it doesn't address critical behavioral aspects like whether this is a read-only operation, potential rate limits, authentication requirements, error conditions, or what happens when multiple parameters conflict. The description provides some context about output characteristics but lacks operational transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured in two sentences that directly convey the tool's purpose and key characteristics. Every phrase earns its place by specifying the extraction target, optimization purpose, and preservation policy. While slightly dense, it avoids redundancy and gets straight to the point without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 8 parameters with 100% schema coverage but no annotations and no output schema, the description provides adequate context about what the tool produces ('clean, unformatted transcripts optimized for AI processing') but lacks information about return format, error handling, or operational constraints. For a tool with this many parameters and no structured safety/behavior annotations, the description should provide more complete operational context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 8 parameters thoroughly. The description adds marginal value by emphasizing the 'clean, unformatted' nature of the output and the preservation of technical terms, which relates to the 'preserve_technical_terms' parameter and 'format' options. However, it doesn't provide additional parameter semantics beyond what the comprehensive schema descriptions already offer.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Extract clean, unformatted transcripts') and resource ('transcripts'), with explicit optimization for AI processing. It distinguishes from siblings like 'limitless_get_full_transcript' by emphasizing the 'unformatted' and 'optimized for AI processing' aspects, and from 'limitless_get_detailed_analysis' by focusing on raw extraction rather than analysis.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context through phrases like 'optimized for AI processing' and 'without markdown formatting or summarization', suggesting this tool is for downstream AI tasks rather than human-readable output. However, it doesn't explicitly state when to use this versus alternatives like 'limitless_get_full_transcript' or 'limitless_get_detailed_analysis', nor does it mention any prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 effectively describes key traits: 'auto-truncation for token limits' and 'Large responses auto-truncated' inform about output handling and potential data loss. It also implies the tool is read-only (generates summaries) and mentions constraints, though it lacks details on rate limits, authentication needs, or error conditions. This adds substantial value beyond the minimal schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: it starts with the core purpose, lists inclusions, states constraints, and ends with an example. Each sentence adds value, though the example could be more integrated. There's no wasted text, making it efficient for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (generates summaries with truncation), no annotations, and no output schema, the description is somewhat complete but has gaps. It covers purpose, constraints, and parameters, but lacks details on output format, error handling, or how truncation works. For a tool with behavioral nuances like auto-truncation, more context would be beneficial to ensure correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 both parameters fully. The description adds minimal value: it repeats the date format and default, and mentions timezone as optional without extra context. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, as the description doesn't significantly enhance parameter understanding beyond what's in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Generate daily summary with auto-truncation for token limits. INCLUDES: meetings, action items, participants, topics.' This specifies the verb (generate), resource (daily summary), and content scope. However, it doesn't explicitly differentiate from sibling tools like 'limitless_get_full_transcript' or 'limitless_get_detailed_analysis', which might also provide summaries or related content.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides some implied usage guidance: 'use smaller date ranges if needed' suggests this tool is for daily summaries and may require adjustment for large outputs. However, it doesn't explicitly state when to use this tool versus alternatives like 'limitless_get_by_natural_time' or 'limitless_list_lifelogs_by_date', nor does it mention prerequisites or exclusions. The guidance is helpful but incomplete.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 'advanced search' with 'intelligent context, relevance scoring' but doesn't clarify critical behaviors like whether this is a read-only operation, potential performance impacts of searching 'ALL lifelogs,' rate limits, authentication requirements, or what the output format looks like. For a search tool with no annotation coverage, this leaves significant gaps in understanding how it behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured in two sentences: the first states the core functionality with key features, and the second provides usage context. Every phrase adds value, with no redundant information. It could be slightly more front-loaded by leading with 'Search across ALL lifelogs' more explicitly, but it's well-constructed overall.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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 annotations, no output schema), the description is adequate but incomplete. It clearly explains the purpose and hints at advanced features, but without annotations or output schema, it fails to disclose behavioral aspects like safety, performance, or result format. For a search tool with many parameters and no structured safety hints, more descriptive guidance on limitations or output would be beneficial.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 adds marginal value by emphasizing the 'ALL lifelogs' scope for the search_term parameter and hinting at 'comprehensive filtering options,' but it doesn't provide additional semantic context beyond what's in the schema descriptions. This meets the baseline of 3 when schema coverage is high.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs 'advanced search across ALL lifelogs' with specific capabilities like 'intelligent context, relevance scoring, and comprehensive filtering.' It explicitly distinguishes from siblings by emphasizing 'not just recent' and being 'perfect for finding historical discussions,' which differentiates it from tools like limitless_list_recent_lifelogs or limitless_search_lifelogs that might have narrower scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
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 ('Perfect for finding historical discussions'), implying it's for comprehensive searches across all lifelogs rather than limited scopes. However, it doesn't explicitly state when NOT to use it or name specific alternatives among the sibling tools, such as when to choose limitless_search_lifelogs instead.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 adds valuable context about 'automatic pagination' and handling 'large datasets by fetching all pages internally', which goes beyond what the input schema provides. However, it doesn't mention potential rate limits, authentication requirements, error conditions, or what the return format looks like (though there's no output schema).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly concise with two sentences that each earn their place. The first sentence explains what the tool does and its key features. The second sentence provides clear usage guidance. There's zero wasted language or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (6 parameters, no annotations, no output schema), the description provides adequate but incomplete context. It explains the core functionality and when to use it, but doesn't describe the return format or potential limitations. For a data-fetching tool with no output schema, the description should ideally mention what kind of data structure to expect.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 6 parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema. It mentions 'date/range' which aligns with the date/start/end parameters, but provides no additional syntax or format details. The baseline of 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool 'fetches complete transcript data for a date/range with automatic pagination', which is a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'limitless_get_raw_transcript' or 'limitless_list_lifelogs_by_range', which might have overlapping functionality. The purpose is clear but lacks sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
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: 'Use this when you need complete transcript data without worrying about token limits.' This gives explicit guidance on the primary use case. However, it doesn't mention when NOT to use it or name specific alternatives among the many sibling tools, which would be needed for a perfect score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 effectively describes key behaviors: pagination ('Returns paginated results to avoid token limits. Use cursor to fetch next page.') and the nature of returned data ('raw log data'). It doesn't mention rate limits, authentication needs, or error handling, but covers essential operational aspects well for a read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured in three sentences: purpose statement, pagination behavior, and usage recommendation. Each sentence adds distinct value without redundancy. It's appropriately sized and front-loaded with the core functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read operation with 9 parameters and no output schema, the description provides good context about pagination and data format. It doesn't explain return values or error cases, but given the tool's complexity and lack of annotations, it covers the essential operational aspects adequately. The gap in output details prevents a perfect score.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no parameter-specific information beyond what's already in the schema (which has 100% coverage). It mentions 'cursor' and 'date/time range' generally, but doesn't provide additional context about parameter interactions, default behaviors, or semantic nuances. With complete schema coverage, the baseline is 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 within a date/time range.' It specifies the resource (logs/recordings) and verb (lists) with a scope (date/time range). However, it doesn't explicitly differentiate from sibling tools like 'limitless_list_lifelogs_by_date' or 'limitless_list_recent_lifelogs', which likely have overlapping functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
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) and suggests alternatives (like analysis-specific tools among siblings). However, it doesn't explicitly state when NOT to use it or 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.
Behavior4/5
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 effectively describes key behavioral traits: 'Returns paginated results to avoid token limits. Use cursor to fetch next page.' This covers pagination behavior and token limit avoidance, which are crucial for understanding how to handle large datasets. However, it does not mention permissions, rate limits, 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: the first sentence states the core purpose, followed by pagination details and usage guidance. Every sentence earns its place by adding 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.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (8 parameters, pagination, no output schema, and no annotations), the description is mostly complete. It covers purpose, pagination behavior, and usage context. However, it lacks details on response format (e.g., what fields are returned) and error scenarios, which would enhance completeness for a tool with many parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 8 parameters thoroughly. The description does not add any parameter-specific semantics beyond what the schema provides (e.g., it does not explain the 'date' parameter's format or 'cursor' usage in more detail). 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.
Purpose5/5
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'), resource ('logs/recordings'), and scope ('for a specific date'), distinguishing it from siblings like 'limitless_list_lifelogs_by_range' (date range) and 'limitless_list_recent_lifelogs' (recent logs).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for usage: 'Best for getting raw log data which you can then analyze for summaries, action items, topics, etc.' This implicitly suggests when to use it (for raw data analysis) versus alternatives like 'limitless_get_daily_summary' or 'limitless_extract_action_items', but it does not explicitly name alternatives or state exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 effectively describes the search scope ('recent logs'), limitations ('limited scope'), and search type ('keywords/phrases'), which are crucial behavioral traits. However, it lacks details on permissions, rate limits, or error handling, which would be valuable for a search tool with 7 parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured in two sentences. The first sentence states the purpose and scope, while the second provides critical usage guidelines. Every sentence earns its place with no redundant or vague language.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
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, search functionality) and lack of annotations or output schema, the description is reasonably complete. It clarifies the tool's purpose, usage boundaries, and behavioral scope. However, it could improve by mentioning the return format or pagination behavior, especially since there's no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 adds minimal parameter semantics beyond the schema, only implying the 'recent' scope which relates to 'fetch_limit'. Since the schema does the heavy lifting, the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool 'performs a simple text search for specific keywords/phrases within the title and content of *recent* logs/Pendant recordings.' It specifies the verb (search), resource (recent logs/Pendant recordings), and scope (title and content). It also distinguishes from siblings by emphasizing keyword-based search rather than conceptual analysis like 'limitless_analyze_speaker' or 'limitless_extract_action_items'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage guidelines: 'Use ONLY for keywords, NOT for concepts like 'action items' or 'summaries'. Searches only recent logs (limited scope).' This clearly defines when to use this tool versus alternatives like 'limitless_extract_action_items' or 'limitless_get_daily_summary', and sets boundaries on its applicability.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 effectively describes key traits: the limit constraint ('max 10 per request'), pagination behavior ('use cursor for more'), and input constraints (supported/unsupported expressions). However, it doesn't mention authentication needs, rate limits, or error handling, leaving some gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is highly concise and well-structured, with every sentence earning its place. It front-loads the purpose, lists supported expressions, states constraints, gives examples, and clarifies exclusions in a compact format without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (7 parameters, no output schema, no annotations), the description is largely complete. It covers purpose, usage, constraints, and examples. However, without an output schema, it doesn't describe return values (e.g., lifelog structure), and with no annotations, it omits behavioral details like side effects or permissions, leaving minor gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 adds minimal value beyond the schema, only implying usage of 'time_expression' and 'limit' in the EXAMPLES section. It doesn't provide additional semantics for parameters like 'timezone' or 'isStarred', meeting the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get lifelogs using natural time expressions.' It specifies the verb ('Get'), resource ('lifelogs'), and unique capability ('natural time expressions'), distinguishing it from siblings like 'limitless_list_lifelogs_by_date' or 'limitless_list_lifelogs_by_range' that likely use different time formats.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool versus alternatives. It lists SUPPORTED expressions (e.g., 'today', 'yesterday') and NOT SUPPORTED ones (e.g., 'Monday July 14'), with a clear alternative: 'use 'July 14 2025' instead.' This helps the agent choose this tool over siblings for natural language time queries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 effectively describes key behaviors: pagination ('Returns paginated results', 'Use cursor to fetch next page'), sorting ('sorted newest first'), and token limit management ('to avoid token limits'). However, it doesn't mention rate limits, authentication requirements, or error conditions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured in three sentences: purpose statement, pagination mechanics, and usage guidance. Every sentence adds value with no redundancy or wasted words. It's appropriately sized for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a list tool with no annotations and no output schema, the description provides good context about behavior (pagination, sorting) and usage. However, it doesn't describe the response format or structure, which would be helpful given the lack of output schema. The sibling tool context is adequately addressed through differentiation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 6 parameters thoroughly. The description adds minimal parameter-specific semantics beyond the schema, only mentioning cursor usage for pagination. This meets the baseline of 3 when schema coverage is high.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
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 ('Lists', 'Returns paginated results') and resources ('most recent logs/recordings'). It distinguishes from siblings by specifying 'most recent' (vs. date/range-based siblings) and 'raw log data' (vs. analysis/summary siblings).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool ('Best for getting raw log data which you can then analyze for summaries, action items, topics, etc.') and implicitly suggests alternatives by mentioning what this tool provides (raw data) versus what other tools might provide (processed analysis). It also explains the pagination use case.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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