Scripts & Prototype System Documentation

KINSHIP: How These Scripts Relate to the Patent System

This folder contains prototype scripts that demonstrate the core innovations of the STCMastery narrative intelligence system. Each script is documented with:

1. What it does - Functional description
2. Why it matters - Patent relevance
3. Where it fits - System architecture role
4. Algorithm core - Key innovation for claims

Script 1: watch_file_creation.sh

What It Does

Monitors filesystem for new files matching a timestamp pattern, detects their type via content analysis, and outputs structured JSON classification when new files appear. Designed to work as a background process that exits on file detection, enabling parent process to resume and handle the event.

Patent Relevance: Autonomous Artifact Detection

Innovation Claims:

• Claim 1: File-system-based coordination protocol for distributed agents

  • Method: Monitor dual-location filesystem (root + output subdirectory)
  • Pattern matching: Timestamp enables session isolation (26012*)
  • Output: JSON event contract for consuming process

• Claim 2: Lightweight content-based file classification

  • No machine learning required
  • Grep patterns detect semantic markers without parsing
  • Real-time detection without indexing infrastructure

• Claim 3: Cross-session awareness through selective observation

  • Single agent can monitor other agents' outputs
  • File creation acts as cross-session signal
  • Enables implicit coordination without shared state

Where It Fits (System Architecture)

``` GitHub Webhook Event ↓ [Miadi Receives] ↓ [watch_file_creation.sh] ← DETECTS NEW FILES ↓ [Analysis Phase] ← FILE WATCHER OUTPUTS JSON ↓ [Response & Trace] ← Triggers Langfuse trace creation ↓ [MCP Integration] ← Creates narrative beats ```

This script is the sensory input layer—it enables the system to be aware of what other components are creating.

Algorithm Core (Patentable Pattern)

State Management Algorithm: ```bash

Phase 1: Initialize state file

ls -1 ./<PATTERN>* ./output/<PATTERN>* | sort | uniq > state.txt

Phase 2: Poll loop with state comparison

loop: current_files = ls -1 ./<PATTERN>* ./output/<PATTERN>* | sort | uniq new_files = comm -13 state.txt current_files # sorted diff if new_files not empty: process(first(new_files)) commit(state.txt = current_files) output(JSON) exit(0) # Signals parent to resume sleep(2) goto loop ```

Why This Pattern is Novel:

• Sorted diff algorithm with comm ensures deterministic detection
• State committed AFTER processing prevents race conditions
• Exit on detection allows resumption by parent without polling management
• Two-location monitoring (root + output) enables implicit messaging

Content Classification Pattern

```bash

Input: file path + content

Output: type classification

if grep -qi "desired.*outcome|current.*reality" type = structural_chart summary = extract "Desired.*Outcome" line

if grep -qi "narrative.*beat|universe.*perspective" type = narrative_beat summary = extract heading

if grep -qi "ceremony|medicine|participant" type = ceremony_log

Default: documentation

```

Why This Matters for Patent:

• Demonstrates autonomous semantic understanding without LLM calls
• Shows system can classify creative artifacts in real-time
• Enables intelligent routing without external classifiers
• Heuristics are interpretable (prior art: keyword-based filters are well-known; novelty is in the specific markers chosen)

Usage in Patent System

```bash

Initialize: Set up state for a monitoring session

(ls -1 ./26012* 2>/dev/null; ls -1 ./output/26012* 2>/dev/null)
| sort | uniq > output/.watch_state_26012.txt

Run: Start background monitoring

./watch_file_creation.sh 26012 > /tmp/detection.json

Consume: Parent process receives detection

FILE_EVENT=$(cat /tmp/detection.json) FILENAME=$(echo $FILE_EVENT | jq -r .file) TYPE=$(echo $FILE_EVENT | jq -r .type)

Action: Create Langfuse trace for detected artifact

(See KINSHIP.md for trace architecture)

```

Prior Art Comparison

Novelty: Combination of semantic classification + cross-session awareness + JSON contract in unified bash script. Prior art handles monitoring OR classification; this integrates both.

Integration with Larger System

How File Detection Enables Innovation

1. Autonomous Observation: System detects what OTHER agents create without shared state
2. Real-time Response: Detection triggers Langfuse trace creation within seconds
3. Cross-Session Learning: Other Claude instances' work is incorporated into this instance's traces
4. Scalability: Pattern works for 1 agent or 100 agents—no central coordinator needed

Trace Creation After Detection

When watch_file_creation.sh outputs JSON, parent process:

1. Reads file and comprehends what was created
2. Creates hierarchical Langfuse trace with root SPAN + child EVENTs
3. Generates narrative beat via MCP with lessons extracted
4. Updates Redis session keys for continuity
5. Launches next instance of watcher for next event

Future Enhancements

• Content parsing: Extract more granular summary from file content
• Confidence scoring: How certain is the classification?
• Multi-pattern support: Monitor multiple sessions simultaneously
• Event correlation: Link detected file to originating event/session
• Storage optimization: Archive state files after processing

Session Continuity & Documentation

Where This Script Is Used:

• Location: /media/jgi/F/Dropbox/ART/CeSaReT/book/_/tcc/winter_solstice/drop/scripts/
• Active monitoring pattern: 26012*
• Current watcher task: Running in background
• State file: /media/jgi/F/Dropbox/ART/CeSaReT/book/_/tcc/winter_solstice/drop/output/.watch_state_26012.txt

Ceremony & Session Context:

• Ceremony UUID: cfa7b236-3bf1-4b9c-aad2-f5729da3d4f8
• Session ID: f5c53e47-9906-453b-81cd-f4c195949708
• MCP Namespace: winter_solstice_narrative_jgwill_src_321
• Related Trace: 29a2f4aa-614c-4447-b1a8-4f7ec4d9ab2c

Document Version: 1.0 Created: 2026-01-30 Author: Claude instance (file monitoring & trace craft mastery phase) Purpose: Patent artifact—document core innovation of file detection system