diff --git a/research/email-triage-setup.md b/research/email-triage-setup.md
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-# Email Triage Setup for Hermes
-
-**Project:** Tony_tech / research
-**Date:** 2026-06-18
-**Status:** In progress
-**Owner:** Hermes (autonomous collaborator)
-
-## Goals
-- Automate triage of tonyjbala@gmail.com inbox
-- Use AI (Hermes) to classify emails into categories
-- Move emails to appropriate folders/labels
-- Extract action items and integrate with Gitea / workflows
-- Run periodically or on-demand via Hermes
-
-## Current State
-- Himalaya CLI installed (v1.2.0) in ~/.local/bin
-- Config at ~/.config/himalaya/config.toml with gmail account (IMAP/SMTP)
-- **Issue:** Authentication failing (invalid/expired app password)
-- No Google Workspace OAuth set up yet (alternative path)
-
-## Recommended Architecture
-1. **Himalaya** for terminal IMAP operations (list, read, move, flag)
-2. **Hermes agent** for intelligent classification (via terminal calls + reasoning)
-3. **Gmail labels** as triage folders:
-   - Action (needs reply or task)
-   - Waiting (delegated / awaiting response)
-   - FYI / Read (no action)
-   - Archive (or use Gmail archive)
-   - Projects-specific if needed
-4. **Integration points**:
-   - Create Gitea issues in Tony_tech for high-priority action items
-   - Link to daily briefs or opportunity scans
-   - Log triage decisions in artifacts
-
-## Setup Steps (Current)
-
-### 1. Fix Credentials (Himalaya)
-- Go to https://myaccount.google.com/apppasswords
-- Generate new 16-character app password for "Hermes Email" (Mail)
-- Update config:
-  ```bash
-  # Backup first
-  cp ~/.config/himalaya/config.toml ~/.config/himalaya/config.toml.bak
-
-  # Then edit the password line (or tell Hermes the new password securely)
-  sed -i 's/backend.auth.raw = "OLD_PASSWORD"/backend.auth.raw = "NEW_16CHAR_APP_PASSWORD"/' ~/.config/himalaya/config.toml
-  ```
-- Test:
-  ```bash
-  export PATH="$HOME/.local/bin:$PATH"
-  himalaya account list
-  himalaya envelope list --output json --page 1 --page-size 3
-  ```
-
-### 2. Define Triage Categories
-Standard labels to create in Gmail (or use himalaya to move):
-- Action
-- Waiting
-- FYI
-- Someday
-
-Use Gmail web or:
-```bash
-himalaya folder create Action
-# etc.
-```
-
-### 3. Triage Workflow Script
-Create a script (e.g. ~/.local/bin/hermes-email-triage) that:
-- Fetches unseen emails (`himalaya envelope list --unseen --output json`)
-- For each email, extracts from, subject, date, snippet
-- Uses Hermes reasoning or simple rules + LLM call to classify
-- Moves with `himalaya message move <id> <folder>`
-- Optionally creates Gitea issue for Action items via MCP tools
-- Logs to ~/.hermes/profiles/leonard/artifacts/email-triage/
-
-Example skeleton (to be implemented):
-```bash
-#!/bin/bash
-export PATH="$HOME/.local/bin:$PATH"
-emails=$(himalaya envelope list --unseen --output json)
-# parse with jq, then for each: classify, act
-```
-
-### 4. Automation
-- Cron or Hermes cronjob for periodic triage (e.g. every 30m or on new mail trigger)
-- Manual trigger via Telegram: "triage email" or "run email triage"
-
-### 5. Integration with Tony_tech
-- All triage logic/docs in this folder
-- Action items from email -> Gitea issues in Tony_tech
-- Link to other workflows (daily briefs, agent persistence)
-
-## Next Steps
-- [ ] User provides new app password or runs update
-- [ ] Test list/read/move
-- [ ] Create Gmail labels
-- [ ] Write initial triage script
-- [ ] Test classification on sample emails
-- [ ] Schedule via cronjob tool
-- [ ] Add Gitea issue creation for actions
-- [ ] Document results in Tony_tech
-
-## Security Notes
-- App password (not main password)
-- Consider moving to OAuth via google-workspace skill for better long-term auth
-- Never commit passwords to Gitea
-
-## References
-- Himalaya skill docs
-- Gmail IMAP labels mapping
-- Hermes terminal + execute_code for AI classification
-
----
-*Work placed in Tony_tech as requested.*
diff --git a/research/headroom-densification.md b/research/headroom-densification.md
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-# Headroom Evaluation & Densification Implementation for Hermes
-
-**Source**: X post by @teknium (status 2067292705710031117) + detailed Hermes Agent self-evaluation.
-**Date**: 2026-06 (approx from context)
-**Status**: Partial integration - densification cherry-picked; CCR rejected.
-
-## TL;DR
-Headroom (github.com/chopratejas/headroom) is a token compression proxy claiming 60-95% savings. 
-For Hermes agent workloads (search_files JSON, multi-turn tool use, persistent context):
-- CCR (remove + <<marker>> + retrieve) is **net-negative** (duplication + cache disruption).
-- Lossless densification is **useful** (~60% on search_files per original eval).
-
-**Action taken**: Implemented internal lossless densifier for search_files outputs (no external dep).
-
-## Key Implementation
-File: `~/.hermes/profiles/leonard/scripts/densify_search_results.py`
-
-```python
-def densify_search_results(result: dict) -> str:
-    # Converts 
-    # {"total_count": N, "matches": [{"path":.., "line":.., "content":..}, ...]}
-    # to
-    # total:N
-    # path|line|content
-    # ./file.py|10|code here
-```
-
-- Lossless (roundtrip parser included).
-- Escapes | and newlines.
-- Handles truncated, target fields.
-
-## Measured Benefits (tests)
-- Small sample (6 matches): ~20% char savings.
-- Larger realistic (36 matches, long snippets): ~18% savings.
-- Expected higher on pure location searches or many short results (removes repeated JSON keys like "path","line","content" 100+ times).
-
-Rough token impact: 15-30%+ reduction on search_files heavy paths (depends on content length vs structure).
-
-## Why not full Headroom
-- CCR causes agents to re-retrieve → pay twice.
-- Breaks KV/prompt caching.
-- Conflicts with Hermes existing compression/memory.
-- Adds bloat/latency for our loop-heavy use.
-
-## Replicable Ideas
-- Apply similar densification to other JSON tools (mcp_gitea responses, terminal structured output).
-- For search_files specifically: group by file or use minimal schema when context=0.
-
-## Files
-- Densifier: `/home/vpsadmin/.hermes/profiles/leonard/scripts/densify_search_results.py`
-- Usage: After any `search_files(...)` call, `densify_search_results(result)` before injecting to context.
-
-## Next
-- Test in live multi-turn sessions.
-- Add to agent tool response post-processing (optional flag).
-- Extend to other high-volume tools.
-- Monitor real token usage in daily briefs / opportunity scans.
-
-See full evaluation in conversation history for details.