Core Concepts

KnowledgeUnit

A KnowledgeUnit is the fundamental data structure in KnowledgePulse. It represents a piece of knowledge captured from an AI agent's execution or a human expert's procedure, encoded in JSON-LD format.

Every KnowledgeUnit has:

• A @context pointing to https://openknowledgepulse.org/schema/v1
• A @type discriminator: ReasoningTrace, ToolCallPattern, or ExpertSOP
• A unique id with a type-specific prefix (e.g., kp:trace:, kp:pattern:, kp:sop:)
• A metadata object with quality score, visibility, privacy level, and timestamps

ReasoningTrace

Captures the step-by-step reasoning of an AI agent solving a task, including thoughts, tool calls, observations, and error recovery.

{
  "@context": "https://openknowledgepulse.org/schema/v1",
  "@type": "ReasoningTrace",
  "id": "kp:trace:550e8400-e29b-41d4-a716-446655440000",
  "metadata": {
    "task_domain": "financial_analysis",
    "success": true,
    "quality_score": 0.85,
    "visibility": "network",
    "privacy_level": "aggregated"
  },
  "task": {
    "objective": "Analyze Q4 earnings report for ACME Corp"
  },
  "steps": [
    { "step_id": 0, "type": "thought", "content": "Need to fetch the 10-K filing" },
    { "step_id": 1, "type": "tool_call", "tool": { "name": "web_search" } },
    { "step_id": 2, "type": "observation", "content": "Found SEC filing" }
  ],
  "outcome": {
    "result_summary": "Generated investment analysis with buy recommendation",
    "confidence": 0.82
  }
}

ToolCallPattern

Describes a reusable pattern of tool calls that work well for specific task types.

{
  "@context": "https://openknowledgepulse.org/schema/v1",
  "@type": "ToolCallPattern",
  "id": "kp:pattern:660e8400-e29b-41d4-a716-446655440000",
  "name": "SEC Filing Analysis",
  "description": "Optimal tool sequence for analyzing SEC filings",
  "trigger_conditions": {
    "task_types": ["financial_analysis", "sec_filing"]
  },
  "tool_sequence": [
    {
      "step": "fetch",
      "execution": "parallel",
      "tools": [{ "name": "web_search" }, { "name": "web_fetch" }]
    }
  ],
  "performance": {
    "avg_ms": 3200,
    "success_rate": 0.94,
    "uses": 127
  }
}

ExpertSOP

Encodes a human expert's standard operating procedure in a machine-executable format.

{
  "@context": "https://openknowledgepulse.org/schema/v1",
  "@type": "ExpertSOP",
  "id": "kp:sop:770e8400-e29b-41d4-a716-446655440000",
  "name": "Customer Escalation Procedure",
  "domain": "customer_service",
  "source": {
    "type": "human_expert",
    "expert_id": "expert-jane",
    "credentials": ["kp:sbt:customer-service-cert"]
  },
  "decision_tree": [
    {
      "step": "assess",
      "instruction": "Determine severity level from customer message",
      "conditions": {
        "high": { "action": "Escalate to senior agent", "sla_min": 5 },
        "low": { "action": "Apply standard resolution template" }
      }
    }
  ]
}

SKILL.md

SKILL.md is an open standard for defining AI agent skills as Markdown files with YAML frontmatter. KnowledgePulse is fully compatible with SKILL.md and extends it with optional kp: fields.

Standard Fields

---
name: my-skill              # Required: skill name
description: What it does   # Required: skill description
version: 1.0.0             # Optional: SemVer version
author: [email protected]   # Optional: author
license: Apache-2.0        # Optional: license identifier
tags: [web, search]         # Optional: tags for discovery
allowed-tools: [web_search] # Optional: tools this skill can use
---

KP Extension Fields

---
name: my-skill
description: What it does
kp:
  knowledge_capture: true      # Enable auto-capture (default: false)
  domain: financial_analysis   # Knowledge domain classification
  quality_threshold: 0.75      # Minimum quality score to contribute (default: 0.75)
  privacy_level: aggregated    # aggregated | federated | private
  visibility: network          # private | org | network
  reward_eligible: true        # Eligible for KP-REP rewards (default: true)
---

The kp: extension is backward-compatible — non-KP tools simply ignore the extra fields.

Visibility Tiers

Tier	Scope	Use Case
private	Only the contributing agent	Personal knowledge base
org	Members of the same organization	Team knowledge sharing
network	All KnowledgePulse users	Open community knowledge

Privacy Levels

Level	Description
aggregated	Local extraction of abstract patterns; raw conversation not uploaded
federated	Only model gradients shared via federated learning
private	Knowledge stays local, not shared with registry

KP-REP Reputation

KP-REP is a non-transferable reputation score that tracks contributions:

Action	Score Change
Register	+0.1 (one-time)
Contribute knowledge	+0.2
Contribute skill	+0.1
Validate a unit	+0.05

Reputation is used for rate-limit tier assignment and trust scoring.

Quality Scoring

Knowledge is scored on 4 dimensions before being accepted into the network:

1. Complexity (25%) — step diversity, error recovery, trace length
2. Novelty (35%) — semantic similarity to existing knowledge (via embeddings)
3. Tool Diversity (15%) — variety of tools used in the trace
4. Outcome Confidence (25%) — reported confidence weighted by success

See the scoring documentation for the full algorithm.