TENET — Documentation

TENET’s memory system ensures nothing is forgotten between sessions. Every journal entry, code change, and decision is indexed, embedded, and searchable.

What Gets Remembered

Source	What’s Indexed	How Often
Journal entries	Features, fixes, decisions, discoveries, pivots	Every 60 seconds
Code headers	`@purpose` annotations from source files	Every 5 minutes
Manual memories	Insights, notes, decisions via `tenet_memory_add`	On demand

How Search Works

TENET uses hybrid search — combining lexical and semantic approaches for best results:

Query: "CLI startup optimization"
         |
    +----+----+
    |         |
  BM25+    Embedding
  (lexical) (semantic)
    |         |
    +----+----+
         |
   Reciprocal Rank
      Fusion (RRF)
         |
    Ranked Results

BM25+ (Always Available)

Term-frequency scoring with:

Stopword removal and phrase detection
Adaptive document length normalization
Query term weighting based on IDF
Positive IDF floor (BM25+ variant) — common terms still contribute

Semantic Search (When Embeddings Available)

Cosine similarity on text-embedding-3-small vectors:

1536 dimensions
OpenAI or OpenRouter fallback
Auto-backfill: if key was missing when indexed, embeddings are added later

Reciprocal Rank Fusion

Merges BM25 and embedding results by rank position, not raw scores. More robust than linear interpolation because it doesn’t require score normalization.

Current Stats

tenet memory status

total_memories: 349
by_type: {feature: 96, milestone: 96, decision: 55, fix: 40, ...}
embeddings: {available: true, count: 349, model: "openrouter/text-embedding-3-small"}

349/349 memories embedded — zero gaps.

Graph Edges

Memories aren’t isolated. They connect to each other:

Edge Type	Meaning	Example
`updates`	New info supersedes old	”CLI speed now 98ms” updates “CLI speed was 6.7s”
`contradicts`	New finding invalidates old	”Connection pooling helps” contradicts “Keep connections short”
`related_to`	Topically connected	Memory about eval system → related to agent config
`caused_by`	Causal relationship	”Test failures” caused_by “Dependency upgrade”
`part_of`	Hierarchical grouping	Session memories → part_of project milestone

# Add a link via API
curl -X POST http://localhost:4360/api/memory/link \
  -H "Content-Type: application/json" \
  -d '{"from": 42, "to": 17, "type": "updates"}'

Code Header Indexing

Files with @purpose annotations are automatically indexed:

/**
 * Memory Indexer Module
 *
 * @purpose Automatic indexing of journal entries and code headers
 */

This creates a searchable memory entry:

Source: file
Type: code-header
Content: src/lib/memory-indexer.ts: Automatic indexing of journal entries and code headers

Scans: src/, packages/, scripts/, eval/ Updates if @purpose changes. Deduped by file path.

Knowledge Doc Lifecycle

Knowledge docs (VISION.md, THESIS.md, etc.) are audited for staleness:

tenet organize

  Doc Health

  ✓  VISION              0d old  drift:   20%  mentions: 221
  ✓  THESIS              0d old  drift:   20%  mentions: 223
  ✓  NARRATIVE            0d old  drift:   20%  mentions: 206

  0 of 5 docs need attention

When docs drift from journal evidence, tenet organize generates a PENDING.md with proposed updates and open questions for human review.

Search

BM25+ hybrid search internals and query optimization.

Graph Edges

Structured relationships between memories.

Embeddings

Auto-backfill, model selection, and fallback behavior.

Code Headers

Indexing @purpose annotations from source files.

Getting Started

Agent Harness

Learning System

Memory

Context Hub

Integrations

Guides

API Reference

Memory System

What Gets Remembered

How Search Works

BM25+ (Always Available)

Semantic Search (When Embeddings Available)

Reciprocal Rank Fusion

Current Stats

Graph Edges

Code Header Indexing

Knowledge Doc Lifecycle

Search

Graph Edges

Embeddings

Code Headers

​What Gets Remembered

​How Search Works

​BM25+ (Always Available)

​Semantic Search (When Embeddings Available)

​Reciprocal Rank Fusion

​Current Stats

​Graph Edges

​Code Header Indexing

​Knowledge Doc Lifecycle

Search

Graph Edges

Embeddings

Code Headers

What Gets Remembered

How Search Works

BM25+ (Always Available)

Semantic Search (When Embeddings Available)

Reciprocal Rank Fusion

Current Stats

Graph Edges

Code Header Indexing

Knowledge Doc Lifecycle