Step Agents
Identity: A distributed set of specialized analytical agents, each aligned to a distinct operational function across Steps 1 through 11. These agents act as modular processors tailored to extract, refine, and evolve semantic insight.
Function:
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Perform domain-specific operations such as semantic clustering, syntactic parsing, sentiment attribution, classification modeling, relationship inference, or temporal alignment.
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Generate three refinement questions per processing round, each tuned to challenge or deepen current understanding.
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Adjust angle, tone, and difficulty of queries based on memory state, contradiction history, and novelty patterns observed in Keymaker’s trace.
Input Requirements:
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Output artifacts and annotations from prior steps.
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Keymaker’s active working memory object and current MoM trace.
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Domain-specific flags and heuristics (e.g., entity mutation likelihood, pathway priority cues).
Output:
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A structured result package, typically including one or more of:
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Entity matrices
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Inferred relationship maps
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Temporal cluster paths
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Label distributions
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Accompanied by a 3-question challenge set with:
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novelty_score: Measures semantic deviation from prior queries -
vector_distance_to_past: Embedding distance from historical vectors -
difficulty_index: Tuned cognitive complexity factor -
Optional: Contradiction threshold alert if flagged
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Implementation Model:
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Each agent resides in a modular container, isolated for traceability and specialization.
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Execution modes may include:
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Prompt-chained reasoning over LLMs
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Deterministic rule-based scripts
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Fine-tuned ML models or hybrid pipelines
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Agents are designed for composability and can be hot-swapped or extended per mission scope.
Enhancements:
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Provide a worked example: Step 3 Temporal Agent showing sample inputs, outputs, and refinement logic.
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Define explicit escalation thresholds (e.g., contradiction confidence >0.65 across ≥2 steps).
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Add agent self-assessment schema (e.g., question entropy, delta-impact-on-pathway scores).