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199-mcp

Limitless MCP Server

by 199-mcp

limitless_get_daily_summary

Generate a daily summary of meetings, action items, participants, and topics from Limitless Pendant recordings with automatic truncation for token limits.

Instructions

Generate daily summary with auto-truncation for token limits. INCLUDES: meetings, action items, participants, topics. CONSTRAINTS: Large responses auto-truncated, use smaller date ranges if needed. ARGS: date (YYYY-MM-DD format, defaults today), timezone (optional). EXAMPLE: date='2025-07-14'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNoDate in YYYY-MM-DD format (defaults to today).
timezoneNoIANA timezone for date calculations.

Implementation Reference

  • src/server.ts:797-821 (registration)
    Registration of the 'limitless_get_daily_summary' tool, including description, schema, and wrapper handler that calls the core DailySummaryGenerator.
    server.tool("limitless_get_daily_summary",
        "Generate daily summary with auto-truncation for token limits. INCLUDES: meetings, action items, participants, topics. CONSTRAINTS: Large responses auto-truncated, use smaller date ranges if needed. ARGS: date (YYYY-MM-DD format, defaults today), timezone (optional). EXAMPLE: date='2025-07-14'.",
        DailySummaryArgsSchema,
        async (args, _extra) => {
            try {
                // Validate constraints
                const validation = validateApiConstraints(args);
                if (!validation.valid) {
                    return { content: [{ type: "text", text: validation.error! }], isError: true };
                }
                
                const date = args.date || new Date().toISOString().split('T')[0];
                const summary = await DailySummaryGenerator.generateDailySummary(
                    limitlessApiKey,
                    date,
                    args.timezone
                );
                
                return createSafeResponse(summary, `Daily summary for ${date}`);
            } catch (error) {
                const errorMessage = error instanceof Error ? error.message : String(error);
                return { content: [{ type: "text", text: `Error generating daily summary: ${errorMessage}` }], isError: true };
            }
        }
    );
  • Input schema validation using Zod for tool arguments: date (optional YYYY-MM-DD) and timezone.
    const DailySummaryArgsSchema = {
        date: z.string().optional().describe("Date in YYYY-MM-DD format (defaults to today)."),
        timezone: z.string().optional().describe("IANA timezone for date calculations."),
    };
  • Primary handler implementation in DailySummaryGenerator.generateDailySummary: fetches lifelogs for the date, detects meetings and action items using helpers, computes metrics (recording/speaking time, top participants, topics), generates insights, returns structured DailySummary.
    /**
     * Generate comprehensive daily summary with insights and analytics
     */
    static async generateDailySummary(
        apiKey: string,
        date: string,
        timezone?: string
    ): Promise<DailySummary> {
        
        // Get the full day range for the specified date
        const parser = new NaturalTimeParser({ timezone });
        const targetDate = new Date(date + 'T00:00:00');
        const timeRange = {
            start: date + ' 00:00:00',
            end: date + ' 23:59:59',
            timezone: timezone || parser['timezone']
        };
        
        // Fetch all lifelogs for the day
        const lifelogs = await getLifelogs(apiKey, {
            date,
            timezone,
            limit: 1000,
            includeMarkdown: true,
            includeHeadings: true,
            direction: 'asc'
        });
        
        if (lifelogs.length === 0) {
            return this.createEmptyDailySummary(date, timezone || 'UTC');
        }
        
        // Detect meetings
        const meetings = MeetingDetector.detectMeetings(lifelogs);
        
        // Extract all action items
        const allActionItems: ActionItem[] = [];
        for (const lifelog of lifelogs) {
            if (lifelog.contents) {
                const items = ActionItemExtractor.extractFromNodes(lifelog.contents, lifelog.id);
                allActionItems.push(...items);
            }
        }
        
        // Calculate metrics
        const totalRecordingTime = this.calculateTotalRecordingTime(lifelogs);
        const totalSpeakingTime = this.calculateTotalSpeakingTime(lifelogs);
        const topParticipants = this.getTopParticipants(meetings);
        const keyTopics = this.extractKeyTopics(lifelogs);
        
        // Generate insights
        const insights = this.generateInsights(lifelogs, meetings);
        
        return {
            date,
            timezone: timezone || 'UTC',
            meetings,
            totalRecordingTime,
            totalSpeakingTime,
            topParticipants,
            keyTopics,
            actionItems: allActionItems,
            insights
        };
    }
  • TypeScript interface defining the structure of the daily summary output returned by the tool.
    export interface DailySummary {
        date: string;
        timezone: string;
        meetings: Meeting[];
        totalRecordingTime: number;
        totalSpeakingTime: number;
        topParticipants: MeetingParticipant[];
        keyTopics: string[];
        actionItems: ActionItem[];
        insights: {
            mostProductiveHours: string[];
            longestMeeting: Meeting | null;
            mostFrequentParticipant: string | null;
            topicsDiscussed: number;
        };
    }
  • MeetingDetector.detectMeetings: helper used in daily summary to identify meetings from lifelogs based on time proximity, multiple speakers, and duration.
    static detectMeetings(lifelogs: Lifelog[]): Meeting[] {
        if (!lifelogs.length) return [];
        
        // Group lifelogs by continuous time periods
        const timeGroups = this.groupByTimeProximity(lifelogs);
        
        // Analyze each group for meeting characteristics
        const meetings: Meeting[] = [];
        
        for (const group of timeGroups) {
            const meeting = this.analyzePotentialMeeting(group);
            if (meeting) {
                meetings.push(meeting);
            }
        }
        
        return meetings.sort((a, b) => new Date(a.startTime).getTime() - new Date(b.startTime).getTime());
    }
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.

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