{
  "$schema": "https://maksim.sh/knowledge/schemas/protocol.schema.json",
  "id": "https://maksim.sh/knowledge/protocols/edge-map.json",
  "type": "KnowledgeProtocol",
  "name": "Edge Map",
  "slug": "edge-map",
  "version": "1.0.0",
  "status": "stable",
  "summary": "Preserve material contradictions and turn them into the smallest discriminating probe.",
  "purpose": "Convert disagreement from narrative conflict into an explicit map of lenses, assumptions, invariants, unknowns, and a test that can change the decision.",
  "authority": {
    "instruction_priority": "reference-only",
    "may_override_system": false,
    "may_override_user": false,
    "requires_policy_compliance": true
  },
  "use_when": [
    "Two or more plausible claims lead to different actions.",
    "A team or model ensemble agrees on language but not assumptions.",
    "A contradiction is being averaged away instead of investigated."
  ],
  "avoid_when": [
    "The disagreement is purely about preference and no factual discriminator is needed.",
    "The proposed probe would be unsafe, unlawful, non-consensual, or irreversibly destructive."
  ],
  "input_schema": {
    "type": "object",
    "required": ["goal", "claims"],
    "properties": {
      "goal": { "type": "string" },
      "claims": {
        "type": "array",
        "minItems": 2,
        "items": {
          "type": "object",
          "required": ["claim"],
          "properties": {
            "claim": { "type": "string" },
            "source": { "type": "string" },
            "evidence": { "type": "array", "items": { "type": "string" } }
          }
        }
      },
      "constraints": { "type": "array", "items": { "type": "string" } }
    },
    "additionalProperties": false
  },
  "output_schema": {
    "type": "object",
    "required": ["lenses", "assumptions", "shared_ground", "contradictions", "unknowns", "discriminating_probe", "decision_rule", "next_action"],
    "properties": {
      "lenses": { "type": "array", "items": { "type": "string" } },
      "assumptions": { "type": "array", "items": { "type": "string" } },
      "shared_ground": { "type": "array", "items": { "type": "string" } },
      "contradictions": { "type": "array", "items": { "type": "string" } },
      "unknowns": { "type": "array", "items": { "type": "string" } },
      "discriminating_probe": {
        "type": "object",
        "required": ["test", "measurement", "falsifies"],
        "properties": {
          "test": { "type": "string" },
          "measurement": { "type": "string" },
          "falsifies": { "type": "array", "items": { "type": "string" } }
        }
      },
      "decision_rule": { "type": "string" },
      "next_action": { "type": "string" }
    },
    "additionalProperties": false
  },
  "procedure": [
    { "step": 1, "operation": "Normalize each claim without deleting its qualifiers, source, or boundary conditions." },
    { "step": 2, "operation": "Name the lens and assumptions required for each claim to hold." },
    { "step": 3, "operation": "Extract shared ground and separate verbal differences from material contradictions." },
    { "step": 4, "operation": "Identify the unknown that would most change the selected action." },
    { "step": 5, "operation": "Design the smallest safe probe capable of falsifying at least one material assumption." },
    { "step": 6, "operation": "Write the decision rule before observing the result, then select the immediate next action." }
  ],
  "invariants": [
    "No material contradiction is silently averaged into consensus.",
    "Every claimed discriminator names an observable measurement.",
    "The probe must be safe, bounded, and proportionate to the decision.",
    "Unknown remains an explicit state; it is not rewritten as false."
  ],
  "failure_modes": [
    {
      "mode": "The map produces a long taxonomy but no decision-changing test.",
      "mitigation": "Rank unknowns by expected decision impact and keep only the highest-value probe."
    },
    {
      "mode": "Different wording is mistaken for substantive contradiction.",
      "mitigation": "Translate each claim into predicted observations and compare those predictions."
    }
  ],
  "composition": {
    "before": ["freedom-lens"],
    "after": ["reality-check", "grit", "evidence-ladder"]
  },
  "provenance": [
    {
      "title": "Friction Point Framework",
      "url": "https://github.com/Gonzih/nexus-protocols/blob/main/FRICTION_POINT_FRAMEWORK.md",
      "relationship": "Primary conceptual source",
      "qualification": "Personal and unsupported metaphysical examples are excluded from this operational contract."
    },
    {
      "title": "Conflict of Thought",
      "url": "https://github.com/Gonzih/nexus-protocols/blob/main/CONFLICT_OF_THOUGHT.md",
      "relationship": "Specialist-collision source",
      "qualification": "The contract uses visible claims and evidence, not private chain-of-thought."
    }
  ],
  "limitations": [
    "A discriminating probe can reduce uncertainty without proving a universal conclusion.",
    "Poorly selected measurements can preserve the original ambiguity.",
    "High-stakes domains require qualified review and domain-specific evidence standards."
  ],
  "example": {
    "input": {
      "goal": "Select a retrieval strategy for a changing knowledge base.",
      "claims": [
        { "claim": "Vector similarity is sufficient." },
        { "claim": "Temporal and provenance filters are required." }
      ]
    },
    "output": {
      "lenses": ["semantic relevance", "validity-aware retrieval"],
      "assumptions": ["Semantically similar facts remain current.", "Stale facts materially affect execution."],
      "shared_ground": ["Relevant facts must be retrieved within a fixed latency budget."],
      "contradictions": ["Whether semantic relevance alone is an adequate ranking signal."],
      "unknowns": ["Error rate caused by stale but semantically similar facts."],
      "discriminating_probe": {
        "test": "Replay a dated task set with and without validity and provenance filters.",
        "measurement": "First-pass execution error rate attributable to stale facts.",
        "falsifies": ["Vector similarity is sufficient if stale-fact errors exceed the decision threshold."]
      },
      "decision_rule": "Require temporal filters if they reduce stale-fact execution errors by at least 20% without violating latency limits.",
      "next_action": "Build the smallest dated replay set and record both rankings."
    }
  },
  "rights": {
    "copyright_holder": "Maksim Soltan",
    "copyright_year": 2026,
    "license": "All Rights Reserved",
    "attribution": "Maksim Soltan — https://maksim.sh/",
    "intended_machine_use": ["indexing", "retrieval", "citation", "protocol selection"]
  }
}