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get_temporal_context

Analyze Bitcoin halving cycles to determine current positioning, historical analogs from cycles 1-3, and provide cycle-based guidance for financial decision-making.

Instructions

Get Bitcoin halving cycle positioning: days since last halving, estimated cycle phase, historical analogs from cycles 1-3, and cycle-based guidance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Main handler function for get_temporal_context. Retrieves or computes the Bitcoin cycle temporal context, including halving dates, phase identification, and guidance.
    export async function getTemporalContext(cache: CacheService): Promise<TemporalContextOutput | ErrorOutput> {
      const cached = cache.get<TemporalContextOutput>(CACHE_KEY);
      if (cached) return cached.data;
    
      try {
        const cycleInfo = getTemporalCycleInfo();
        const analogs = getCycleAnalogs(cycleInfo.daysSinceLastHalving);
        const guidance = generateTemporalGuidance(cycleInfo.estimatedCyclePhase, cycleInfo.daysSinceLastHalving, cycleInfo.cycleProgressPercentage);
    
        const durationRemaining = estimateTypicalDuration(cycleInfo.estimatedCyclePhase, cycleInfo.daysSinceLastHalving);
    
        const result: TemporalContextOutput = {
          current_date: new Date().toISOString().split('T')[0],
          last_halving_date: cycleInfo.lastHalvingDate,
          next_halving_estimated: cycleInfo.nextHalvingEstimated,
          days_since_last_halving: cycleInfo.daysSinceLastHalving,
          days_until_next_halving: cycleInfo.daysUntilNextHalving,
          cycle_progress_percentage: cycleInfo.cycleProgressPercentage,
          estimated_cycle_phase: cycleInfo.estimatedCyclePhase,
          phase_confidence: cycleInfo.phaseConfidence,
          historical_pattern: analogs.historicalPattern,
          cycle_1_analog: analogs.cycle1,
          cycle_2_analog: analogs.cycle2,
          cycle_3_analog: analogs.cycle3,
          typical_duration_remaining: durationRemaining,
          agent_guidance: guidance,
        };
    
        cache.set(CACHE_KEY, result, getCacheTtl(BASE_TTL));
        return result;
      } catch (err) {
        return {
          error: true,
          error_source: 'get_temporal_context',
          agent_guidance: 'Temporal cycle data unavailable. Bitcoin cycle positioning is a critical context layer — delay strategic positioning decisions until this data is restored.',
          last_known_data: cache.get<TemporalContextOutput>(CACHE_KEY)?.data ?? null,
          data_warnings: ['Temporal context temporarily unavailable. Retry shortly.'],
        };
      }
    }
Behavior3/5

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

With no annotations provided, the description carries full burden. It adequately discloses what data is returned (days since halving, cycle phase, analogs, guidance) but omits operational characteristics like whether this is a read-only operation, rate limits, or data freshness/staleness.

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?

Single dense sentence with zero waste. Front-loaded with action verb ('Get'), followed by resource specification, then colon-delimited list of specific return components.

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 zero-parameter tool without output schema, the description sufficiently enumerates return value components (days, phase, analogs, guidance). Minor gap: does not indicate if tool covers only Bitcoin or if it retrieves data for other assets with halving mechanics.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Zero parameters present; baseline 4 applies per rubric. No parameter explanation required or provided.

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?

Excellent specificity: 'Get Bitcoin halving cycle positioning' uses concrete verb and resource, clearly distinguishing this from sibling tools like get_historical_context or get_macro_context by focusing specifically on halving cycle data rather than general price history or macro indicators.

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?

Provides no guidance on when to invoke this tool versus alternatives like get_historical_context or get_asset_context, nor does it specify prerequisites (e.g., Bitcoin-only analysis scope).

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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