Timmy bf003cd944 feat: measurer.py — compounding intelligence metrics engine
Implements issue #14: 7 metrics that prove knowledge compounding.

Metrics:
- Knowledge velocity: new facts/day (from index.json)
- Knowledge coverage: % domains with 10+ facts (from YAML files)
- Hit rate: % sessions referencing bootstrap knowledge
- Error recurrence: same errors across sessions (should decrease)
- Task completion: % sessions with successful end_reason
- First-try success: actions without backtracking (tool/msg ratio)
- Knowledge age: staleness of facts (freshness score)

Data sources:
- knowledge/index.json + YAML files for fact metrics
- ~/.hermes/state.db sessions + messages tables

Features:
- JSON and markdown output formats
- --since, --repo, --format flags
- 7-day trend tracking via snapshot persistence
- Runs in 33ms on 11.9K sessions / 192K messages
- Dashboard auto-generation with --save-snapshot

Closes #14
2026-04-14 14:16:31 -04:00

Compounding Intelligence

Turn 1B+ daily tokens into durable, compounding fleet intelligence.

The Problem

20,991 sessions on disk. Each one starts at zero. Every agent rediscover the same HTTP 405 is a branch protection issue. The intelligence from a million tokens of work evaporates when the session ends.

The Solution

Three pipelines that form a compounding loop:

SESSION ENDS → HARVESTER → KNOWLEDGE STORE → BOOTSTRAPPER → NEW SESSION STARTS SMARTER
                              ↓
                         MEASURER → Prove it's working

Architecture

Pipeline 1: Harvester

Reads finished session transcripts. Extracts durable knowledge: facts, pitfalls, patterns, tool quirks. Stores in knowledge/.

Pipeline 2: Bootstrap

Before a session starts, queries knowledge store for relevant facts. Assembles compact 2k-token context. Injects into session so it starts with full situational awareness.

Pipeline 3: Measure

Tracks whether compounding is happening. Knowledge velocity, error reduction, hit rate, task completion. Daily report proves the loop works.

Directory Structure

├── knowledge/
│   ├── index.json          # Machine-readable fact index
│   ├── global/             # Cross-repo knowledge
│   ├── repos/{repo}.md     # Per-repo knowledge
│   └── agents/{agent}.md   # Agent-type notes
├── scripts/
│   ├── harvester.py        # Post-session knowledge extractor
│   ├── bootstrapper.py     # Pre-session context loader
│   ├── measurer.py         # Compounding metrics
│   └── session_reader.py   # JSONL parser
├── metrics/
│   └── dashboard.md        # Human-readable status
└── templates/
    ├── bootstrap-context.md
    └── harvest-prompt.md

The 100x Path

Month 1:  15,000 facts, sessions 20% faster
Month 2:  45,000 facts, sessions 40% faster, first-try success up 30%
Month 3:  90,000 facts, fleet measurably smarter per token

Each new session is better than the last. The intelligence compounds.

Issues

See all issues for the full roadmap.

Epics:

  • EPIC 1: Session Harvester (#2)
  • EPIC 2: Knowledge Store & Bootstrap (#3)
  • EPIC 3: Compounding Measurement (#4)
  • EPIC 4: Retroactive Harvest (#5)
Description
System for turning 1B+ daily tokens into durable, compounding fleet intelligence
Readme 4.8 MiB
Languages
Python 100%