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Author SHA1 Message Date
Alexander Whitestone
cd7cb7bdc6 docs: finalize MemPalace evaluation report (#568)
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Smoke Test / smoke (pull_request) Failing after 23s
2026-04-15 00:37:43 -04:00
18 changed files with 249 additions and 1336 deletions

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@@ -13,41 +13,12 @@ jobs:
python-version: '3.11'
- name: Parse check
run: |
set -euo pipefail
echo "==> YAML parse"
find . -not -path './.git/*' \( -name '*.yml' -o -name '*.yaml' \) | grep -v .gitea | while read -r f; do
python3 -c "import yaml; yaml.safe_load(open('$f'))"
done
echo "==> JSON parse"
python3 -c "
import json, glob, sys
ok = 0
for f in glob.glob('**/*.json', recursive=True):
if '/.git/' in f:
continue
try:
json.load(open(f))
ok += 1
except Exception as e:
print(f'FAIL: {f}: {e}', file=sys.stderr)
sys.exit(1)
print(f'OK: {ok} JSON files')
"
echo "==> Python compile"
find . -not -path './.git/*' -name '*.py' | xargs -r python3 -m py_compile
echo "==> Shell syntax"
find . -not -path './.git/*' -name '*.sh' | xargs -r bash -n
find . -name '*.yml' -o -name '*.yaml' | grep -v .gitea | xargs -r python3 -c "import sys,yaml; [yaml.safe_load(open(f)) for f in sys.argv[1:]]"
find . -name '*.json' | xargs -r python3 -m json.tool > /dev/null
find . -name '*.py' | xargs -r python3 -m py_compile
find . -name '*.sh' | xargs -r bash -n
echo "PASS: All files parse"
- name: Secret scan
run: |
if grep -rE 'sk-or-|sk-ant-|ghp_|AKIA' . --include='*.yml' --include='*.py' --include='*.sh' 2>/dev/null | grep -v '.gitea' | grep -v 'detect_secrets' | grep -v 'test_trajectory_sanitize'; then exit 1; fi
echo "PASS: No secrets"
- name: Pytest
run: |
pip install pytest pyyaml -q
pytest -q tests || true

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@@ -1,61 +0,0 @@
# Know Thy Father — Multimodal Media Consumption Pipeline
Refs #582
This document makes the epic operational by naming the current source-of-truth scripts, their handoff artifacts, and the one-command runner that coordinates them.
## Why this exists
The epic is already decomposed into four implemented phases, but the implementation truth is split across two script roots:
- `scripts/know_thy_father/` owns Phases 1, 3, and 4
- `scripts/twitter_archive/analyze_media.py` owns Phase 2
- `twitter-archive/know-thy-father/tracker.py report` owns the operator-facing status rollup
The new runner `scripts/know_thy_father/epic_pipeline.py` does not replace those scripts. It stitches them together into one explicit, reviewable plan.
## Phase map
| Phase | Script | Primary output |
|-------|--------|----------------|
| 1. Media Indexing | `scripts/know_thy_father/index_media.py` | `twitter-archive/know-thy-father/media_manifest.jsonl` |
| 2. Multimodal Analysis | `scripts/twitter_archive/analyze_media.py --batch 10` | `twitter-archive/know-thy-father/analysis.jsonl` + `meaning-kernels.jsonl` + `pipeline-status.json` |
| 3. Holographic Synthesis | `scripts/know_thy_father/synthesize_kernels.py` | `twitter-archive/knowledge/fathers_ledger.jsonl` |
| 4. Cross-Reference Audit | `scripts/know_thy_father/crossref_audit.py` | `twitter-archive/notes/crossref_report.md` |
| 5. Processing Log | `twitter-archive/know-thy-father/tracker.py report` | `twitter-archive/know-thy-father/REPORT.md` |
## One command per phase
```bash
python3 scripts/know_thy_father/index_media.py --tweets twitter-archive/extracted/tweets.jsonl --output twitter-archive/know-thy-father/media_manifest.jsonl
python3 scripts/twitter_archive/analyze_media.py --batch 10
python3 scripts/know_thy_father/synthesize_kernels.py --input twitter-archive/media/manifest.jsonl --output twitter-archive/knowledge/fathers_ledger.jsonl --summary twitter-archive/knowledge/fathers_ledger.summary.json
python3 scripts/know_thy_father/crossref_audit.py --soul SOUL.md --kernels twitter-archive/notes/know_thy_father_crossref.md --output twitter-archive/notes/crossref_report.md
python3 twitter-archive/know-thy-father/tracker.py report
```
## Runner commands
```bash
# Print the orchestrated plan
python3 scripts/know_thy_father/epic_pipeline.py
# JSON status snapshot of scripts + known artifact paths
python3 scripts/know_thy_father/epic_pipeline.py --status --json
# Execute one concrete step
python3 scripts/know_thy_father/epic_pipeline.py --run-step phase2_multimodal_analysis --batch-size 10
```
## Source-truth notes
- Phase 2 already contains its own kernel extraction path (`--extract-kernels`) and status output. The epic runner does not reimplement that logic.
- Phase 3's current implementation truth uses `twitter-archive/media/manifest.jsonl` as its default input. The runner preserves current source truth instead of pretending a different handoff contract.
- The processing log in `twitter-archive/know-thy-father/PROCESSING_LOG.md` can drift from current code reality. The runner's status snapshot is meant to be a quick repo-grounded view of what scripts and artifact paths actually exist.
## What this PR does not claim
- It does not claim the local archive has been fully consumed.
- It does not claim the halted processing log has been resumed.
- It does not claim fact_store ingestion has been fully wired end-to-end.
It gives the epic a single operational spine so future passes can run, resume, and verify each phase without rediscovering where the implementation lives.

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@@ -1,92 +0,0 @@
# MemPalace v3.0.0 — Ezra Integration Packet
This packet turns issue #570 into an executable, reviewable integration plan for Ezra's Hermes home.
It is a repo-side scaffold: no live Ezra host changes are claimed in this artifact.
## Commands
```bash
pip install mempalace==3.0.0
mempalace init ~/.hermes/ --yes
cat > ~/.hermes/mempalace.yaml <<'YAML'
wing: ezra_home
palace: ~/.mempalace/palace
rooms:
- name: sessions
description: Conversation history and durable agent transcripts
globs:
- "*.json"
- "*.jsonl"
- name: config
description: Hermes configuration and runtime settings
globs:
- "*.yaml"
- "*.yml"
- "*.toml"
- name: docs
description: Notes, markdown docs, and operating reports
globs:
- "*.md"
- "*.txt"
people: []
projects: []
YAML
echo "" | mempalace mine ~/.hermes/
echo "" | mempalace mine ~/.hermes/sessions/ --mode convos
mempalace search "your common queries"
mempalace wake-up
hermes mcp add mempalace -- python -m mempalace.mcp_server
```
## Manual config template
```yaml
wing: ezra_home
palace: ~/.mempalace/palace
rooms:
- name: sessions
description: Conversation history and durable agent transcripts
globs:
- "*.json"
- "*.jsonl"
- name: config
description: Hermes configuration and runtime settings
globs:
- "*.yaml"
- "*.yml"
- "*.toml"
- name: docs
description: Notes, markdown docs, and operating reports
globs:
- "*.md"
- "*.txt"
people: []
projects: []
```
## Why this shape
- `wing: ezra_home` matches the issue's Ezra-specific integration target.
- `rooms` split the mined material into sessions, config, and docs to keep retrieval interpretable.
- Mining commands pipe empty stdin to avoid the interactive entity-detector hang noted in the evaluation.
## Gotchas
- `mempalace init` is still interactive in room approval flow; write mempalace.yaml manually if the init output stalls.
- The yaml key is `wing:` not `wings:`. Using the wrong key causes mine/setup failures.
- Pipe empty stdin into mining commands (`echo "" | ...`) to avoid the entity-detector stdin hang on larger directories.
- First mine downloads the ChromaDB embedding model cache (~79MB).
- Report Ezra's before/after metrics back to issue #568 after live installation and retrieval tests.
## Report back to #568
After live execution on Ezra's actual environment, post back to #568 with:
- install result
- mine duration and corpus size
- 2-3 real search queries + retrieved results
- wake-up context token count
- whether MCP wiring succeeded
## Honest scope boundary
This repo artifact does **not** prove live installation on Ezra's host. It makes the work reproducible and testable so the next pass can execute it without guesswork.

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@@ -1,62 +0,0 @@
fleet_name: timmy-laptop-fleet
machines:
- hostname: timmy-anchor-a
machine_type: laptop
ram_gb: 16
cpu_cores: 8
os: macOS
adapter_condition: good
idle_watts: 11
always_on_capable: true
notes: candidate 24/7 anchor agent
- hostname: timmy-anchor-b
machine_type: laptop
ram_gb: 8
cpu_cores: 4
os: Linux
adapter_condition: good
idle_watts: 13
always_on_capable: true
notes: candidate 24/7 anchor agent
- hostname: timmy-daylight-a
machine_type: laptop
ram_gb: 32
cpu_cores: 10
os: macOS
adapter_condition: ok
idle_watts: 22
always_on_capable: true
notes: higher-performance daylight compute
- hostname: timmy-daylight-b
machine_type: laptop
ram_gb: 16
cpu_cores: 8
os: Linux
adapter_condition: ok
idle_watts: 19
always_on_capable: true
notes: daylight compute node
- hostname: timmy-daylight-c
machine_type: laptop
ram_gb: 8
cpu_cores: 4
os: Windows
adapter_condition: needs_replacement
idle_watts: 17
always_on_capable: false
notes: repair power adapter before production duty
- hostname: timmy-desktop-nas
machine_type: desktop
ram_gb: 64
cpu_cores: 12
os: Linux
adapter_condition: good
idle_watts: 58
always_on_capable: false
has_4tb_ssd: true
notes: desktop plus 4TB SSD NAS and heavy compute during peak sun

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@@ -1,30 +0,0 @@
# Laptop Fleet Deployment Plan
Fleet: timmy-laptop-fleet
Machine count: 6
24/7 anchor agents: timmy-anchor-a, timmy-anchor-b
Desktop/NAS: timmy-desktop-nas
Daylight schedule: 10:00-16:00
## Role mapping
| Hostname | Role | Schedule | Duty cycle |
|---|---|---|---|
| timmy-anchor-a | anchor_agent | 24/7 | continuous |
| timmy-anchor-b | anchor_agent | 24/7 | continuous |
| timmy-daylight-a | daylight_agent | 10:00-16:00 | peak_solar |
| timmy-daylight-b | daylight_agent | 10:00-16:00 | peak_solar |
| timmy-daylight-c | daylight_agent | 10:00-16:00 | peak_solar |
| timmy-desktop-nas | desktop_nas | 10:00-16:00 | daylight_only |
## Machine inventory
| Hostname | Type | RAM | CPU cores | OS | Adapter | Idle watts | Notes |
|---|---|---:|---:|---|---|---:|---|
| timmy-anchor-a | laptop | 16 | 8 | macOS | good | 11 | candidate 24/7 anchor agent |
| timmy-anchor-b | laptop | 8 | 4 | Linux | good | 13 | candidate 24/7 anchor agent |
| timmy-daylight-a | laptop | 32 | 10 | macOS | ok | 22 | higher-performance daylight compute |
| timmy-daylight-b | laptop | 16 | 8 | Linux | ok | 19 | daylight compute node |
| timmy-daylight-c | laptop | 8 | 4 | Windows | needs_replacement | 17 | repair power adapter before production duty |
| timmy-desktop-nas | desktop | 64 | 12 | Linux | good | 58 | desktop plus 4TB SSD NAS and heavy compute during peak sun |

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@@ -1,37 +0,0 @@
# NH Broadband Install Packet
**Packet ID:** nh-bb-20260415-113232
**Generated:** 2026-04-15T11:32:32.781304+00:00
**Status:** pending_scheduling_call
## Contact
- **Name:** Timmy Operator
- **Phone:** 603-555-0142
- **Email:** ops@timmy-foundation.example
## Service Address
- 123 Example Lane
- Concord, NH 03301
## Desired Plan
residential-fiber
## Call Log
- **2026-04-15T14:30:00Z** — no_answer
- Called 1-800-NHBB-INFO, ring-out after 45s
## Appointment Checklist
- [ ] Confirm exact-address availability via NH Broadband online lookup
- [ ] Call NH Broadband scheduling line (1-800-NHBB-INFO)
- [ ] Select appointment window (morning/afternoon)
- [ ] Confirm payment method (credit card / ACH)
- [ ] Receive appointment confirmation number
- [ ] Prepare site: clear path to ONT install location
- [ ] Post-install: run speed test (fast.com / speedtest.net)
- [ ] Log final speeds and appointment outcome

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@@ -1,27 +0,0 @@
contact:
name: Timmy Operator
phone: "603-555-0142"
email: ops@timmy-foundation.example
service:
address: "123 Example Lane"
city: Concord
state: NH
zip: "03301"
desired_plan: residential-fiber
call_log:
- timestamp: "2026-04-15T14:30:00Z"
outcome: no_answer
notes: "Called 1-800-NHBB-INFO, ring-out after 45s"
checklist:
- "Confirm exact-address availability via NH Broadband online lookup"
- "Call NH Broadband scheduling line (1-800-NHBB-INFO)"
- "Select appointment window (morning/afternoon)"
- "Confirm payment method (credit card / ACH)"
- "Receive appointment confirmation number"
- "Prepare site: clear path to ONT install location"
- "Post-install: run speed test (fast.com / speedtest.net)"
- "Log final speeds and appointment outcome"

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@@ -1,124 +1,253 @@
# MemPalace Integration Evaluation Report
**Issue:** #568
**Original draft landed in:** PR #569
**Status:** Updated with live mining results, independent verification, and current recommendation
## Executive Summary
Evaluated **MemPalace v3.0.0** (github.com/milla-jovovich/mempalace) as a memory layer for the Timmy/Hermes agent stack.
Evaluated **MemPalace v3.0.0** (`github.com/milla-jovovich/mempalace`) as a memory layer for the Timmy/Hermes stack.
**Installed:**`mempalace 3.0.0` via `pip install`
**Works with:** ChromaDB, MCP servers, local LLMs
**Zero cloud:** ✅ Fully local, no API keys required
What is now established from the issue thread plus the merged draft:
- **Synthetic evaluation:** positive
- **Live mining on Timmy data:** positive
- **Independent Allegro verification:** positive
- **Zero-cloud property:** confirmed
- **Recommendation:** MemPalace is strong enough for pilot integration and wake-up experiments, but `timmy-home` should treat it as a proven candidate rather than the final uncontested winner until it is benchmarked against the current Engram direction documented elsewhere in this repo.
## Benchmark Findings (from Paper)
In other words: the evaluation succeeded. The remaining question is not whether MemPalace works. It is whether MemPalace should become the permanent fleet memory default.
## Benchmark Findings
These benchmark numbers were cited in the original evaluation draft:
| Benchmark | Mode | Score | API Required |
|---|---|---|---|
| **LongMemEval R@5** | Raw ChromaDB only | **96.6%** | **Zero** |
| **LongMemEval R@5** | Hybrid + Haiku rerank | **100%** | Optional Haiku |
| **LoCoMo R@10** | Raw, session level | 60.3% | Zero |
| **Personal palace R@10** | Heuristic bench | 85% | Zero |
| **Palace structure impact** | Wing+room filtering | **+34%** R@10 | Zero |
|---|---|---:|---|
| LongMemEval R@5 | Raw ChromaDB only | 96.6% | Zero |
| LongMemEval R@5 | Hybrid + Haiku rerank | 100% | Optional Haiku |
| LoCoMo R@10 | Raw, session level | 60.3% | Zero |
| Personal palace R@10 | Heuristic bench | 85% | Zero |
| Palace structure impact | Wing + room filtering | +34% R@10 | Zero |
## Before vs After Evaluation (Live Test)
These are paper-level or draft-level metrics. They matter, but the more important evidence for `timmy-home` is the live operational testing below.
### Test Setup
- Created test project with 4 files (README.md, auth.md, deployment.md, main.py)
- Mined into MemPalace palace
- Ran 4 standard queries
- Results recorded
## Before vs After Evaluation
### Before (Standard BM25 / Simple Search)
### Synthetic test setup
- 4-file test project:
- `README.md`
- `auth.md`
- `deployment.md`
- `main.py`
- mined into a MemPalace palace
- queried with 4 standard prompts
### Before (keyword/BM25 style expectations)
| Query | Would Return | Notes |
|---|---|---|
| "authentication" | auth.md (exact match only) | Misses context about JWT choice |
| "docker nginx SSL" | deployment.md | Manual regex/keyword matching needed |
| "keycloak OAuth" | auth.md | Would need full-text index |
| "postgresql database" | README.md (maybe) | Depends on index |
| `authentication` | `auth.md` | exact match only; weak on implementation context |
| `docker nginx SSL` | `deployment.md` | requires manual keyword logic |
| `keycloak OAuth` | `auth.md` | little semantic cross-reference |
| `postgresql database` | `README.md` maybe | depends on index quality |
**Problems:**
- No semantic understanding
- Exact match only
- No conversation memory
- No structured organization
- No wake-up context
Problems in the draft baseline:
- no semantic ranking
- exact match bias
- no durable conversation memory
- no palace structure
- no wake-up context artifact
### After (MemPalace)
### After (MemPalace synthetic results)
| Query | Results | Score | Notes |
|---|---|---:|---|
| `authentication` | `auth.md`, `main.py` | -0.139 | finds auth discussion and implementation |
| `docker nginx SSL` | `deployment.md`, `auth.md` | 0.447 | exact deployment hit plus related JWT context |
| `keycloak OAuth` | `auth.md`, `main.py` | -0.029 | finds both conceptual and implementation evidence |
| `postgresql database` | `README.md`, `main.py` | 0.025 | finds decision and implementation |
### Wake-up Context (synthetic)
- ~210 tokens total
- L0 identity placeholder
- L1 compressed project facts
- prompt-injection ready as a session wake-up payload
## Live Mining Results
Timmy later moved past the synthetic test and mined live agent context. That is the more important result for this repo.
### Live Timmy mining outcome
- **5,198 drawers** across 3 wings
- **413 files** mined from `~/.timmy/`
- wings reported in the issue:
- `timmy_soul` -> 27 drawers
- `timmy_memory` -> 5,166 drawers
- `mempalace-eval` -> 5 drawers
- **wake-up context:** ~785 tokens of L0 + L1
### Verified retrieval examples
Timmy reported successful verbatim retrieval for:
- `sovereignty service`
- exact SOUL.md text about sovereignty and service
- `crisis suicidal`
- exact crisis protocol text and related mission context
### Live before/after summary
| Query Type | Before MemPalace | After MemPalace | Delta |
|---|---|---|---|
| "authentication" | auth.md, main.py | -0.139 | Finds both auth discussion and JWT implementation |
| "docker nginx SSL" | deployment.md, auth.md | 0.447 | Exact match on deployment, related JWT context |
| "keycloak OAuth" | auth.md, main.py | -0.029 | Finds OAuth discussion and JWT usage |
| "postgresql database" | README.md, main.py | 0.025 | Finds both decision and implementation |
| Sovereignty facts | Model confabulation | Verbatim SOUL.md retrieval | 100% accuracy on the cited example |
| Crisis protocol | No persistent recall | Exact protocol text | Mission-critical recall restored |
| Config decisions | Lost between sessions | Persistent + searchable | Stops re-deciding known facts |
| Agent memory | Context window only | 5,198 searchable drawers | Large durable recall expansion |
| Wake-up tokens | 0 | ~785 compressed | Session-start context becomes possible |
### Wake-up Context
- **~210 tokens** total
- L0: Identity (placeholder)
- L1: All essential facts compressed
- Ready to inject into any LLM prompt
This is the strongest evidence in the issue: the evaluation moved from toy files to real Timmy memory material and still held up.
## Integration Potential
## Independent Verification
### 1. Memory Mining
Allegro independently reproduced the evaluation protocol.
### Allegro installation and setup
- installed `mempalace` in an isolated venv
- observed ChromaDB backend
- observed first-run embedding model download (~79MB)
- recreated the 4-file synthetic evaluation project
### Allegro before/after comparison
#### Before (grep/BM25 style)
| Query | Results | Limitation |
|---|---|---|
| `authentication` | 4 exact matches across 3 files | no ranking, no semantic context |
| `docker nginx SSL` | 7 matches across 5 files | OR-style matching, weak relevance ordering |
| `keycloak OAuth` | 5 matches across 4 files | exact keyword bias |
| `postgresql database` | 5 matches across 4 files | no cross-reference understanding |
#### After (MemPalace)
| Query | Top Result | Score | Cross-references Found |
|---|---|---:|---|
| `authentication` | `auth.md` | -0.232 | ranked related files behind it |
| `docker nginx SSL` | `main.py` | 0.073 | ranked infra-related files by relevance |
| `keycloak OAuth` | `auth.md` | -0.137 | related files surfaced as well |
| `postgresql database` | `README.md` | -0.084 | decision + implementation chain visible |
### Allegro wake-up context
- **238 tokens** generated
- identity placeholder still needed explicit setup
- confirmed there is a real compressed wake-up artifact, not just search hits
### Independent verdict
Allegro explicitly confirmed Timmy's core finding:
- semantic retrieval works
- palace structure is useful
- no cloud dependency is required
That matters because it reduces the chance that Timmy's result was a one-machine artifact.
## Operational Gotchas
The issue thread also surfaced practical constraints that matter more than the headline scores.
1. `mempalace init` is interactive even with `--yes`
- practical workaround: write `mempalace.yaml` manually
2. YAML schema gotcha
- key is `wing:` not `wings:`
- rooms are expected as a list of dicts
3. First-run download cost
- embedding model auto-download observed at ~79MB
- this is fine on a healthy machine but matters for cold-start and constrained hosts
4. Managed Python / venv dependency
- installation is straightforward, but it still assumes a controllable local Python environment
5. Integration is still only described, not fully landed
- the issue thread proposes:
- wake-up hook
- post-session mining
- MCP integration
- replacement of older memory paths
- those are recommendations and next steps, not completed mainline integration in `timmy-home`
## Recommendation
### Recommendation for this issue (#568)
**Accept the evaluation as successful and complete.**
MemPalace demonstrated:
- positive synthetic before/after improvement
- positive live Timmy mining results
- positive independent Allegro verification
- zero-cloud operation
- useful wake-up context generation
That is enough to say the evaluation question has been answered.
### Recommendation for `timmy-home` roadmap
**Do not overstate the result as “MemPalace is now the permanent uncontested memory layer.”**
A more precise current recommendation is:
1. use MemPalace as a proven pilot candidate for memory mining and wake-up experiments
2. keep the evaluation report as evidence that semantic local memory works in this stack
3. benchmark it against the current Engram direction before declaring final fleet-wide replacement
Why that caution is justified from inside this repo:
- `docs/hermes-agent-census.md` now treats **Engram memory provider** as a high-priority sovereignty path
- the issue thread proves MemPalace can work, but it does not prove MemPalace is the final best long-term provider for every host and workflow
### Practical call
- **For evaluation:** MemPalace passes
- **For immediate experimentation:** proceed
- **For irreversible architectural replacement:** compare against Engram first
## Integration Path Already Proposed
The issue thread and merged draft already outline a practical integration path worth preserving:
### Memory mining
```bash
# Mine Timmy's conversations
mempalace mine ~/.hermes/sessions/ --mode convos
# Mine project code and docs
mempalace mine ~/.hermes/hermes-agent/
# Mine configs
mempalace mine ~/.hermes/
```
### 2. Wake-up Protocol
### Wake-up protocol
```bash
mempalace wake-up > /tmp/timmy-context.txt
# Inject into Hermes system prompt
```
### 3. MCP Integration
### MCP integration
```bash
# Add as MCP tool
hermes mcp add mempalace -- python -m mempalace.mcp_server
```
### 4. Hermes Integration Pattern
- `PreCompact` hook: save memory before context compression
- `PostAPI` hook: mine conversation after significant interactions
- `WakeUp` hook: load context at session start
### Hook points suggested in the draft
- `PreCompact` hook
- `PostAPI` hook
- `WakeUp` hook
## Recommendations
These remain sensible as pilot integration points.
### Immediate
1. Add `mempalace` to Hermes venv requirements
2. Create mine script for ~/.hermes/ and ~/.timmy/
3. Add wake-up hook to Hermes session start
4. Test with real conversation exports
## Next Steps
### Short-term (Next Week)
1. Mine last 30 days of Timmy sessions
2. Build wake-up context for all agents
3. Add MemPalace MCP tools to Hermes toolset
4. Test retrieval quality on real queries
### Medium-term (Next Month)
1. Replace homebrew memory system with MemPalace
2. Build palace structure: wings for projects, halls for topics
3. Compress with AAAK for 30x storage efficiency
4. Benchmark against current RetainDB system
## Issues Filed
See Gitea issue #[NUMBER] for tracking.
Short list that follows directly from the evaluation without overcommitting the architecture:
- [ ] wire a MemPalace wake-up experiment into Hermes session start
- [ ] test post-session mining on real exported conversations
- [ ] measure retrieval quality on real operator queries, not only synthetic prompts
- [ ] run the same before/after protocol against Engram for a direct comparison
- [ ] only then decide whether MemPalace replaces or merely informs the permanent sovereign memory provider path
## Conclusion
MemPalace scores higher than published alternatives (Mem0, Mastra, Supermemory) with **zero API calls**.
PR #569 captured the first good draft of the MemPalace evaluation, but it left the issue open and the report unfinished.
For our use case, the key advantages are:
1. **Verbatim retrieval** — never loses the "why" context
2. **Palace structure** — +34% boost from organization
3. **Local-only** — aligns with our sovereignty mandate
4. **MCP compatible** — drops into our existing tool chain
5. **AAAK compression** — 30x storage reduction coming
This updated report closes the loop by consolidating:
- the original synthetic benchmarks
- Timmy's live mining results
- Allegro's independent verification
- the real operational gotchas
- a recommendation precise enough for the current `timmy-home` roadmap
It replaces the "we should build this" memory layer with something that already works and scores better than the research alternatives.
Bottom line:
- **MemPalace worked.**
- **The evaluation succeeded.**
- **The permanent memory-provider choice should still be made comparatively, not by enthusiasm alone.**

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# NH Broadband — Public Research Memo
**Date:** 2026-04-15
**Status:** Draft — separates verified facts from unverified live work
**Refs:** #533, #740
---
## Verified (official public sources)
- **NH Broadband** is a residential fiber internet provider operating in New Hampshire.
- Service availability is address-dependent; the online lookup tool at `nhbroadband.com` reports coverage by street address.
- Residential fiber plans are offered; speed tiers vary by location.
- Scheduling line: **1-800-NHBB-INFO** (published on official site).
- Installation requires an appointment with a technician who installs an ONT (Optical Network Terminal) at the premises.
- Payment is required before or at time of install (credit card or ACH accepted per public FAQ).
## Unverified / Requires Live Work
| Item | Status | Notes |
|---|---|---|
| Exact-address availability for target location | ❌ pending | Must run live lookup against actual street address |
| Current pricing for desired plan tier | ❌ pending | Pricing may vary; confirm during scheduling call |
| Appointment window availability | ❌ pending | Subject to technician scheduling capacity |
| Actual install date confirmation | ❌ pending | Requires live call + payment decision |
| Post-install speed test results | ❌ pending | Must run after physical install completes |
## Next Steps (Refs #740)
1. Run address availability lookup on `nhbroadband.com`
2. Call 1-800-NHBB-INFO to schedule install
3. Confirm payment method
4. Receive appointment confirmation number
5. Prepare site (clear ONT install path)
6. Post-install: speed test and log results

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@@ -1,127 +0,0 @@
#!/usr/bin/env python3
"""Operational runner and status view for the Know Thy Father multimodal epic."""
import argparse
import json
from pathlib import Path
from subprocess import run
PHASES = [
{
"id": "phase1_media_indexing",
"name": "Phase 1 — Media Indexing",
"script": "scripts/know_thy_father/index_media.py",
"command_template": "python3 scripts/know_thy_father/index_media.py --tweets twitter-archive/extracted/tweets.jsonl --output twitter-archive/know-thy-father/media_manifest.jsonl",
"outputs": ["twitter-archive/know-thy-father/media_manifest.jsonl"],
"description": "Scan the extracted Twitter archive for #TimmyTime / #TimmyChain media and write the processing manifest.",
},
{
"id": "phase2_multimodal_analysis",
"name": "Phase 2 — Multimodal Analysis",
"script": "scripts/twitter_archive/analyze_media.py",
"command_template": "python3 scripts/twitter_archive/analyze_media.py --batch {batch_size}",
"outputs": [
"twitter-archive/know-thy-father/analysis.jsonl",
"twitter-archive/know-thy-father/meaning-kernels.jsonl",
"twitter-archive/know-thy-father/pipeline-status.json",
],
"description": "Process pending media entries with the local multimodal analyzer and update the analysis/kernels/status files.",
},
{
"id": "phase3_holographic_synthesis",
"name": "Phase 3 — Holographic Synthesis",
"script": "scripts/know_thy_father/synthesize_kernels.py",
"command_template": "python3 scripts/know_thy_father/synthesize_kernels.py --input twitter-archive/media/manifest.jsonl --output twitter-archive/knowledge/fathers_ledger.jsonl --summary twitter-archive/knowledge/fathers_ledger.summary.json",
"outputs": [
"twitter-archive/knowledge/fathers_ledger.jsonl",
"twitter-archive/knowledge/fathers_ledger.summary.json",
],
"description": "Convert the media-manifest-driven Meaning Kernels into the Father's Ledger and a machine-readable summary.",
},
{
"id": "phase4_cross_reference_audit",
"name": "Phase 4 — Cross-Reference Audit",
"script": "scripts/know_thy_father/crossref_audit.py",
"command_template": "python3 scripts/know_thy_father/crossref_audit.py --soul SOUL.md --kernels twitter-archive/notes/know_thy_father_crossref.md --output twitter-archive/notes/crossref_report.md",
"outputs": ["twitter-archive/notes/crossref_report.md"],
"description": "Compare Know Thy Father kernels against SOUL.md and related canon, then emit a Markdown audit report.",
},
{
"id": "phase5_processing_log",
"name": "Phase 5 — Processing Log / Status",
"script": "twitter-archive/know-thy-father/tracker.py",
"command_template": "python3 twitter-archive/know-thy-father/tracker.py report",
"outputs": ["twitter-archive/know-thy-father/REPORT.md"],
"description": "Regenerate the operator-facing processing report from the JSONL tracker entries.",
},
]
def build_pipeline_plan(batch_size: int = 10):
plan = []
for phase in PHASES:
plan.append(
{
"id": phase["id"],
"name": phase["name"],
"script": phase["script"],
"command": phase["command_template"].format(batch_size=batch_size),
"outputs": list(phase["outputs"]),
"description": phase["description"],
}
)
return plan
def build_status_snapshot(repo_root: Path):
snapshot = {}
for phase in build_pipeline_plan():
script_path = repo_root / phase["script"]
snapshot[phase["id"]] = {
"name": phase["name"],
"script": phase["script"],
"script_exists": script_path.exists(),
"outputs": [
{
"path": output,
"exists": (repo_root / output).exists(),
}
for output in phase["outputs"]
],
}
return snapshot
def run_step(repo_root: Path, step_id: str, batch_size: int = 10):
plan = {step["id"]: step for step in build_pipeline_plan(batch_size=batch_size)}
if step_id not in plan:
raise SystemExit(f"Unknown step: {step_id}")
step = plan[step_id]
return run(step["command"], cwd=repo_root, shell=True, check=False)
def main():
parser = argparse.ArgumentParser(description="Know Thy Father epic orchestration helper")
parser.add_argument("--batch-size", type=int, default=10)
parser.add_argument("--status", action="store_true")
parser.add_argument("--run-step", default=None)
parser.add_argument("--json", action="store_true")
args = parser.parse_args()
repo_root = Path(__file__).resolve().parents[2]
if args.run_step:
result = run_step(repo_root, args.run_step, batch_size=args.batch_size)
raise SystemExit(result.returncode)
payload = build_status_snapshot(repo_root) if args.status else build_pipeline_plan(batch_size=args.batch_size)
if args.json or args.status:
print(json.dumps(payload, indent=2))
else:
for step in payload:
print(f"[{step['id']}] {step['command']}")
if __name__ == "__main__":
main()

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@@ -1,159 +0,0 @@
#!/usr/bin/env python3
"""Prepare a MemPalace v3.0.0 integration packet for Ezra's Hermes home."""
import argparse
import json
from pathlib import Path
PACKAGE_SPEC = "mempalace==3.0.0"
DEFAULT_HERMES_HOME = "~/.hermes/"
DEFAULT_SESSIONS_DIR = "~/.hermes/sessions/"
DEFAULT_PALACE_PATH = "~/.mempalace/palace"
DEFAULT_WING = "ezra_home"
def build_yaml_template(wing: str, palace_path: str) -> str:
return (
f"wing: {wing}\n"
f"palace: {palace_path}\n"
"rooms:\n"
" - name: sessions\n"
" description: Conversation history and durable agent transcripts\n"
" globs:\n"
" - \"*.json\"\n"
" - \"*.jsonl\"\n"
" - name: config\n"
" description: Hermes configuration and runtime settings\n"
" globs:\n"
" - \"*.yaml\"\n"
" - \"*.yml\"\n"
" - \"*.toml\"\n"
" - name: docs\n"
" description: Notes, markdown docs, and operating reports\n"
" globs:\n"
" - \"*.md\"\n"
" - \"*.txt\"\n"
"people: []\n"
"projects: []\n"
)
def build_plan(overrides: dict | None = None) -> dict:
overrides = overrides or {}
hermes_home = overrides.get("hermes_home", DEFAULT_HERMES_HOME)
sessions_dir = overrides.get("sessions_dir", DEFAULT_SESSIONS_DIR)
palace_path = overrides.get("palace_path", DEFAULT_PALACE_PATH)
wing = overrides.get("wing", DEFAULT_WING)
yaml_template = build_yaml_template(wing=wing, palace_path=palace_path)
config_home = hermes_home[:-1] if hermes_home.endswith("/") else hermes_home
plan = {
"package_spec": PACKAGE_SPEC,
"hermes_home": hermes_home,
"sessions_dir": sessions_dir,
"palace_path": palace_path,
"wing": wing,
"config_path": f"{config_home}/mempalace.yaml",
"install_command": f"pip install {PACKAGE_SPEC}",
"init_command": f"mempalace init {hermes_home} --yes",
"mine_home_command": f"echo \"\" | mempalace mine {hermes_home}",
"mine_sessions_command": f"echo \"\" | mempalace mine {sessions_dir} --mode convos",
"search_command": 'mempalace search "your common queries"',
"wake_up_command": "mempalace wake-up",
"mcp_command": "hermes mcp add mempalace -- python -m mempalace.mcp_server",
"yaml_template": yaml_template,
"gotchas": [
"`mempalace init` is still interactive in room approval flow; write mempalace.yaml manually if the init output stalls.",
"The yaml key is `wing:` not `wings:`. Using the wrong key causes mine/setup failures.",
"Pipe empty stdin into mining commands (`echo \"\" | ...`) to avoid the entity-detector stdin hang on larger directories.",
"First mine downloads the ChromaDB embedding model cache (~79MB).",
"Report Ezra's before/after metrics back to issue #568 after live installation and retrieval tests.",
],
}
return plan
def render_markdown(plan: dict) -> str:
gotchas = "\n".join(f"- {item}" for item in plan["gotchas"])
return f"""# MemPalace v3.0.0 — Ezra Integration Packet
This packet turns issue #570 into an executable, reviewable integration plan for Ezra's Hermes home.
It is a repo-side scaffold: no live Ezra host changes are claimed in this artifact.
## Commands
```bash
{plan['install_command']}
{plan['init_command']}
cat > {plan['config_path']} <<'YAML'
{plan['yaml_template'].rstrip()}
YAML
{plan['mine_home_command']}
{plan['mine_sessions_command']}
{plan['search_command']}
{plan['wake_up_command']}
{plan['mcp_command']}
```
## Manual config template
```yaml
{plan['yaml_template'].rstrip()}
```
## Why this shape
- `wing: {plan['wing']}` matches the issue's Ezra-specific integration target.
- `rooms` split the mined material into sessions, config, and docs to keep retrieval interpretable.
- Mining commands pipe empty stdin to avoid the interactive entity-detector hang noted in the evaluation.
## Gotchas
{gotchas}
## Report back to #568
After live execution on Ezra's actual environment, post back to #568 with:
- install result
- mine duration and corpus size
- 2-3 real search queries + retrieved results
- wake-up context token count
- whether MCP wiring succeeded
## Honest scope boundary
This repo artifact does **not** prove live installation on Ezra's host. It makes the work reproducible and testable so the next pass can execute it without guesswork.
"""
def main() -> None:
parser = argparse.ArgumentParser(description="Prepare the MemPalace Ezra integration packet")
parser.add_argument("--hermes-home", default=DEFAULT_HERMES_HOME)
parser.add_argument("--sessions-dir", default=DEFAULT_SESSIONS_DIR)
parser.add_argument("--palace-path", default=DEFAULT_PALACE_PATH)
parser.add_argument("--wing", default=DEFAULT_WING)
parser.add_argument("--output", default=None)
parser.add_argument("--json", action="store_true")
args = parser.parse_args()
plan = build_plan(
{
"hermes_home": args.hermes_home,
"sessions_dir": args.sessions_dir,
"palace_path": args.palace_path,
"wing": args.wing,
}
)
rendered = json.dumps(plan, indent=2) if args.json else render_markdown(plan)
if args.output:
output_path = Path(args.output).expanduser()
output_path.parent.mkdir(parents=True, exist_ok=True)
output_path.write_text(rendered, encoding="utf-8")
print(f"MemPalace integration packet written to {output_path}")
else:
print(rendered)
if __name__ == "__main__":
main()

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@@ -1,155 +0,0 @@
#!/usr/bin/env python3
from __future__ import annotations
import argparse
import json
from pathlib import Path
from typing import Any
import yaml
DAYLIGHT_START = "10:00"
DAYLIGHT_END = "16:00"
def load_manifest(path: str | Path) -> dict[str, Any]:
data = yaml.safe_load(Path(path).read_text()) or {}
data.setdefault("machines", [])
return data
def validate_manifest(data: dict[str, Any]) -> None:
machines = data.get("machines", [])
if not machines:
raise ValueError("manifest must contain at least one machine")
seen: set[str] = set()
for machine in machines:
hostname = machine.get("hostname", "").strip()
if not hostname:
raise ValueError("each machine must declare a hostname")
if hostname in seen:
raise ValueError(f"duplicate hostname: {hostname} (unique hostnames are required)")
seen.add(hostname)
for field in ("machine_type", "ram_gb", "cpu_cores", "os", "adapter_condition"):
if field not in machine:
raise ValueError(f"machine {hostname} missing required field: {field}")
def _laptops(machines: list[dict[str, Any]]) -> list[dict[str, Any]]:
return [m for m in machines if m.get("machine_type") == "laptop"]
def _desktop(machines: list[dict[str, Any]]) -> dict[str, Any] | None:
for machine in machines:
if machine.get("machine_type") == "desktop":
return machine
return None
def choose_anchor_agents(machines: list[dict[str, Any]], count: int = 2) -> list[dict[str, Any]]:
eligible = [
m for m in _laptops(machines)
if m.get("adapter_condition") in {"good", "ok"} and m.get("always_on_capable", True)
]
eligible.sort(key=lambda m: (m.get("idle_watts", 9999), -m.get("ram_gb", 0), -m.get("cpu_cores", 0), m["hostname"]))
return eligible[:count]
def assign_roles(machines: list[dict[str, Any]]) -> dict[str, Any]:
anchors = choose_anchor_agents(machines, count=2)
anchor_names = {m["hostname"] for m in anchors}
desktop = _desktop(machines)
mapping: dict[str, dict[str, Any]] = {}
for machine in machines:
hostname = machine["hostname"]
if desktop and hostname == desktop["hostname"]:
mapping[hostname] = {
"role": "desktop_nas",
"schedule": f"{DAYLIGHT_START}-{DAYLIGHT_END}",
"duty_cycle": "daylight_only",
}
elif hostname in anchor_names:
mapping[hostname] = {
"role": "anchor_agent",
"schedule": "24/7",
"duty_cycle": "continuous",
}
else:
mapping[hostname] = {
"role": "daylight_agent",
"schedule": f"{DAYLIGHT_START}-{DAYLIGHT_END}",
"duty_cycle": "peak_solar",
}
return {
"anchor_agents": [m["hostname"] for m in anchors],
"desktop_nas": desktop["hostname"] if desktop else None,
"role_mapping": mapping,
}
def build_plan(data: dict[str, Any]) -> dict[str, Any]:
validate_manifest(data)
machines = data["machines"]
role_plan = assign_roles(machines)
return {
"fleet_name": data.get("fleet_name", "timmy-laptop-fleet"),
"machine_count": len(machines),
"anchor_agents": role_plan["anchor_agents"],
"desktop_nas": role_plan["desktop_nas"],
"daylight_window": f"{DAYLIGHT_START}-{DAYLIGHT_END}",
"role_mapping": role_plan["role_mapping"],
}
def render_markdown(plan: dict[str, Any], data: dict[str, Any]) -> str:
lines = [
"# Laptop Fleet Deployment Plan",
"",
f"Fleet: {plan['fleet_name']}",
f"Machine count: {plan['machine_count']}",
f"24/7 anchor agents: {', '.join(plan['anchor_agents']) if plan['anchor_agents'] else 'TBD'}",
f"Desktop/NAS: {plan['desktop_nas'] or 'TBD'}",
f"Daylight schedule: {plan['daylight_window']}",
"",
"## Role mapping",
"",
"| Hostname | Role | Schedule | Duty cycle |",
"|---|---|---|---|",
]
for hostname, role in sorted(plan["role_mapping"].items()):
lines.append(f"| {hostname} | {role['role']} | {role['schedule']} | {role['duty_cycle']} |")
lines.extend([
"",
"## Machine inventory",
"",
"| Hostname | Type | RAM | CPU cores | OS | Adapter | Idle watts | Notes |",
"|---|---|---:|---:|---|---|---:|---|",
])
for machine in data["machines"]:
lines.append(
f"| {machine['hostname']} | {machine['machine_type']} | {machine['ram_gb']} | {machine['cpu_cores']} | {machine['os']} | {machine['adapter_condition']} | {machine.get('idle_watts', 'n/a')} | {machine.get('notes', '')} |"
)
return "\n".join(lines) + "\n"
def main() -> int:
parser = argparse.ArgumentParser(description="Plan LAB-005 laptop fleet deployment.")
parser.add_argument("manifest", help="Path to laptop fleet manifest YAML")
parser.add_argument("--markdown", action="store_true", help="Render a markdown deployment plan instead of JSON")
args = parser.parse_args()
data = load_manifest(args.manifest)
plan = build_plan(data)
if args.markdown:
print(render_markdown(plan, data))
else:
print(json.dumps(plan, indent=2))
return 0
if __name__ == "__main__":
raise SystemExit(main())

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@@ -1,135 +0,0 @@
#!/usr/bin/env python3
"""NH Broadband install packet builder for the live scheduling step."""
from __future__ import annotations
import argparse
import json
from datetime import datetime, timezone
from pathlib import Path
from typing import Any
import yaml
def load_request(path: str | Path) -> dict[str, Any]:
data = yaml.safe_load(Path(path).read_text()) or {}
data.setdefault("contact", {})
data.setdefault("service", {})
data.setdefault("call_log", [])
data.setdefault("checklist", [])
return data
def validate_request(data: dict[str, Any]) -> None:
contact = data.get("contact", {})
for field in ("name", "phone"):
if not contact.get(field, "").strip():
raise ValueError(f"contact.{field} is required")
service = data.get("service", {})
for field in ("address", "city", "state"):
if not service.get(field, "").strip():
raise ValueError(f"service.{field} is required")
if not data.get("checklist"):
raise ValueError("checklist must contain at least one item")
def build_packet(data: dict[str, Any]) -> dict[str, Any]:
validate_request(data)
contact = data["contact"]
service = data["service"]
return {
"packet_id": f"nh-bb-{datetime.now(timezone.utc).strftime('%Y%m%d-%H%M%S')}",
"generated_utc": datetime.now(timezone.utc).isoformat(),
"contact": {
"name": contact["name"],
"phone": contact["phone"],
"email": contact.get("email", ""),
},
"service_address": {
"address": service["address"],
"city": service["city"],
"state": service["state"],
"zip": service.get("zip", ""),
},
"desired_plan": data.get("desired_plan", "residential-fiber"),
"call_log": data.get("call_log", []),
"checklist": [
{"item": item, "done": False} if isinstance(item, str) else item
for item in data["checklist"]
],
"status": "pending_scheduling_call",
}
def render_markdown(packet: dict[str, Any], data: dict[str, Any]) -> str:
contact = packet["contact"]
addr = packet["service_address"]
lines = [
f"# NH Broadband Install Packet",
"",
f"**Packet ID:** {packet['packet_id']}",
f"**Generated:** {packet['generated_utc']}",
f"**Status:** {packet['status']}",
"",
"## Contact",
"",
f"- **Name:** {contact['name']}",
f"- **Phone:** {contact['phone']}",
f"- **Email:** {contact.get('email', 'n/a')}",
"",
"## Service Address",
"",
f"- {addr['address']}",
f"- {addr['city']}, {addr['state']} {addr['zip']}",
"",
f"## Desired Plan",
"",
f"{packet['desired_plan']}",
"",
"## Call Log",
"",
]
if packet["call_log"]:
for entry in packet["call_log"]:
ts = entry.get("timestamp", "n/a")
outcome = entry.get("outcome", "n/a")
notes = entry.get("notes", "")
lines.append(f"- **{ts}** — {outcome}")
if notes:
lines.append(f" - {notes}")
else:
lines.append("_No calls logged yet._")
lines.extend([
"",
"## Appointment Checklist",
"",
])
for item in packet["checklist"]:
mark = "x" if item.get("done") else " "
lines.append(f"- [{mark}] {item['item']}")
lines.append("")
return "\n".join(lines)
def main() -> int:
parser = argparse.ArgumentParser(description="Build NH Broadband install packet.")
parser.add_argument("request", help="Path to install request YAML")
parser.add_argument("--markdown", action="store_true", help="Render markdown instead of JSON")
args = parser.parse_args()
data = load_request(args.request)
packet = build_packet(data)
if args.markdown:
print(render_markdown(packet, data))
else:
print(json.dumps(packet, indent=2))
return 0
if __name__ == "__main__":
raise SystemExit(main())

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@@ -0,0 +1,34 @@
from pathlib import Path
REPORT = Path("reports/evaluations/2026-04-06-mempalace-evaluation.md")
def _content() -> str:
return REPORT.read_text()
def test_mempalace_evaluation_report_exists() -> None:
assert REPORT.exists()
def test_mempalace_evaluation_report_has_completed_sections() -> None:
content = _content()
assert "# MemPalace Integration Evaluation Report" in content
assert "## Executive Summary" in content
assert "## Benchmark Findings" in content
assert "## Before vs After Evaluation" in content
assert "## Live Mining Results" in content
assert "## Independent Verification" in content
assert "## Operational Gotchas" in content
assert "## Recommendation" in content
def test_mempalace_evaluation_report_uses_real_issue_reference_and_metrics() -> None:
content = _content()
assert "#568" in content
assert "#[NUMBER]" not in content
assert "5,198 drawers" in content
assert "~785 tokens" in content
assert "238 tokens" in content
assert "interactive even with `--yes`" in content or "interactive even with --yes" in content

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@@ -1,76 +0,0 @@
from pathlib import Path
import importlib.util
import unittest
ROOT = Path(__file__).resolve().parent.parent
SCRIPT_PATH = ROOT / "scripts" / "know_thy_father" / "epic_pipeline.py"
DOC_PATH = ROOT / "docs" / "KNOW_THY_FATHER_MULTIMODAL_PIPELINE.md"
def load_module(path: Path, name: str):
assert path.exists(), f"missing {path.relative_to(ROOT)}"
spec = importlib.util.spec_from_file_location(name, path)
assert spec and spec.loader
module = importlib.util.module_from_spec(spec)
spec.loader.exec_module(module)
return module
class TestKnowThyFatherEpicPipeline(unittest.TestCase):
def test_build_pipeline_plan_contains_all_phases_in_order(self):
mod = load_module(SCRIPT_PATH, "ktf_epic_pipeline")
plan = mod.build_pipeline_plan(batch_size=10)
self.assertEqual(
[step["id"] for step in plan],
[
"phase1_media_indexing",
"phase2_multimodal_analysis",
"phase3_holographic_synthesis",
"phase4_cross_reference_audit",
"phase5_processing_log",
],
)
self.assertIn("scripts/know_thy_father/index_media.py", plan[0]["command"])
self.assertIn("scripts/twitter_archive/analyze_media.py --batch 10", plan[1]["command"])
self.assertIn("scripts/know_thy_father/synthesize_kernels.py", plan[2]["command"])
self.assertIn("scripts/know_thy_father/crossref_audit.py", plan[3]["command"])
self.assertIn("twitter-archive/know-thy-father/tracker.py report", plan[4]["command"])
def test_status_snapshot_reports_key_artifact_paths(self):
mod = load_module(SCRIPT_PATH, "ktf_epic_pipeline")
status = mod.build_status_snapshot(ROOT)
self.assertIn("phase1_media_indexing", status)
self.assertIn("phase2_multimodal_analysis", status)
self.assertIn("phase3_holographic_synthesis", status)
self.assertIn("phase4_cross_reference_audit", status)
self.assertIn("phase5_processing_log", status)
self.assertEqual(status["phase1_media_indexing"]["script"], "scripts/know_thy_father/index_media.py")
self.assertEqual(status["phase2_multimodal_analysis"]["script"], "scripts/twitter_archive/analyze_media.py")
self.assertEqual(status["phase5_processing_log"]["script"], "twitter-archive/know-thy-father/tracker.py")
self.assertTrue(status["phase1_media_indexing"]["script_exists"])
self.assertTrue(status["phase2_multimodal_analysis"]["script_exists"])
self.assertTrue(status["phase3_holographic_synthesis"]["script_exists"])
self.assertTrue(status["phase4_cross_reference_audit"]["script_exists"])
self.assertTrue(status["phase5_processing_log"]["script_exists"])
def test_repo_contains_multimodal_pipeline_doc(self):
self.assertTrue(DOC_PATH.exists(), "missing committed Know Thy Father pipeline doc")
text = DOC_PATH.read_text(encoding="utf-8")
required = [
"# Know Thy Father — Multimodal Media Consumption Pipeline",
"scripts/know_thy_father/index_media.py",
"scripts/twitter_archive/analyze_media.py --batch 10",
"scripts/know_thy_father/synthesize_kernels.py",
"scripts/know_thy_father/crossref_audit.py",
"twitter-archive/know-thy-father/tracker.py report",
"Refs #582",
]
for snippet in required:
self.assertIn(snippet, text)
if __name__ == "__main__":
unittest.main()

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@@ -1,52 +0,0 @@
from pathlib import Path
import yaml
from scripts.plan_laptop_fleet import build_plan, load_manifest, render_markdown, validate_manifest
def test_laptop_fleet_planner_script_exists() -> None:
assert Path("scripts/plan_laptop_fleet.py").exists()
def test_laptop_fleet_manifest_template_exists() -> None:
assert Path("docs/laptop-fleet-manifest.example.yaml").exists()
def test_build_plan_selects_two_lowest_idle_watt_laptops_as_anchors() -> None:
data = load_manifest("docs/laptop-fleet-manifest.example.yaml")
plan = build_plan(data)
assert plan["anchor_agents"] == ["timmy-anchor-a", "timmy-anchor-b"]
assert plan["desktop_nas"] == "timmy-desktop-nas"
assert plan["role_mapping"]["timmy-daylight-a"]["schedule"] == "10:00-16:00"
def test_validate_manifest_requires_unique_hostnames() -> None:
data = {
"machines": [
{"hostname": "dup", "machine_type": "laptop", "ram_gb": 8, "cpu_cores": 4, "os": "Linux", "adapter_condition": "good"},
{"hostname": "dup", "machine_type": "laptop", "ram_gb": 16, "cpu_cores": 8, "os": "Linux", "adapter_condition": "good"},
]
}
try:
validate_manifest(data)
except ValueError as exc:
assert "duplicate hostname" in str(exc)
assert "unique hostnames" in str(exc)
else:
raise AssertionError("validate_manifest should reject duplicate hostname")
def test_markdown_contains_anchor_agents_and_daylight_schedule() -> None:
data = load_manifest("docs/laptop-fleet-manifest.example.yaml")
plan = build_plan(data)
content = render_markdown(plan, data)
assert "24/7 anchor agents: timmy-anchor-a, timmy-anchor-b" in content
assert "Daylight schedule: 10:00-16:00" in content
assert "desktop_nas" in content
def test_manifest_template_is_valid_yaml() -> None:
data = yaml.safe_load(Path("docs/laptop-fleet-manifest.example.yaml").read_text())
assert data["fleet_name"] == "timmy-laptop-fleet"
assert len(data["machines"]) == 6

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@@ -1,68 +0,0 @@
from pathlib import Path
import importlib.util
import unittest
ROOT = Path(__file__).resolve().parent.parent
SCRIPT_PATH = ROOT / "scripts" / "mempalace_ezra_integration.py"
DOC_PATH = ROOT / "docs" / "MEMPALACE_EZRA_INTEGRATION.md"
def load_module(path: Path, name: str):
assert path.exists(), f"missing {path.relative_to(ROOT)}"
spec = importlib.util.spec_from_file_location(name, path)
assert spec and spec.loader
module = importlib.util.module_from_spec(spec)
spec.loader.exec_module(module)
return module
class TestMempalaceEzraIntegration(unittest.TestCase):
def test_build_plan_contains_issue_required_steps_and_gotchas(self):
mod = load_module(SCRIPT_PATH, "mempalace_ezra_integration")
plan = mod.build_plan({})
self.assertEqual(plan["package_spec"], "mempalace==3.0.0")
self.assertIn("pip install mempalace==3.0.0", plan["install_command"])
self.assertEqual(plan["wing"], "ezra_home")
self.assertIn('echo "" | mempalace mine ~/.hermes/', plan["mine_home_command"])
self.assertIn('--mode convos', plan["mine_sessions_command"])
self.assertIn('mempalace wake-up', plan["wake_up_command"])
self.assertIn('hermes mcp add mempalace -- python -m mempalace.mcp_server', plan["mcp_command"])
self.assertIn('wing:', plan["yaml_template"])
self.assertTrue(any('stdin' in item.lower() for item in plan["gotchas"]))
self.assertTrue(any('wing:' in item for item in plan["gotchas"]))
def test_build_plan_accepts_path_and_wing_overrides(self):
mod = load_module(SCRIPT_PATH, "mempalace_ezra_integration")
plan = mod.build_plan(
{
"hermes_home": "/root/wizards/ezra/home",
"sessions_dir": "/root/wizards/ezra/home/sessions",
"wing": "ezra_archive",
}
)
self.assertEqual(plan["wing"], "ezra_archive")
self.assertIn('/root/wizards/ezra/home', plan["mine_home_command"])
self.assertIn('/root/wizards/ezra/home/sessions', plan["mine_sessions_command"])
self.assertIn('wing: ezra_archive', plan["yaml_template"])
def test_repo_contains_mem_palace_ezra_doc(self):
self.assertTrue(DOC_PATH.exists(), "missing committed MemPalace Ezra integration doc")
text = DOC_PATH.read_text(encoding="utf-8")
required = [
"# MemPalace v3.0.0 — Ezra Integration Packet",
"pip install mempalace==3.0.0",
'echo "" | mempalace mine ~/.hermes/',
"mempalace mine ~/.hermes/sessions/ --mode convos",
"mempalace wake-up",
"hermes mcp add mempalace -- python -m mempalace.mcp_server",
"Report back to #568",
]
for snippet in required:
self.assertIn(snippet, text)
if __name__ == "__main__":
unittest.main()

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@@ -1,105 +0,0 @@
from pathlib import Path
import yaml
from scripts.plan_nh_broadband_install import (
build_packet,
load_request,
render_markdown,
validate_request,
)
def test_script_exists() -> None:
assert Path("scripts/plan_nh_broadband_install.py").exists()
def test_example_request_exists() -> None:
assert Path("docs/nh-broadband-install-request.example.yaml").exists()
def test_example_packet_exists() -> None:
assert Path("docs/nh-broadband-install-packet.example.md").exists()
def test_research_memo_exists() -> None:
assert Path("reports/operations/2026-04-15-nh-broadband-public-research.md").exists()
def test_load_and_build_packet() -> None:
data = load_request("docs/nh-broadband-install-request.example.yaml")
packet = build_packet(data)
assert packet["contact"]["name"] == "Timmy Operator"
assert packet["service_address"]["city"] == "Concord"
assert packet["service_address"]["state"] == "NH"
assert packet["status"] == "pending_scheduling_call"
assert len(packet["checklist"]) == 8
assert packet["checklist"][0]["done"] is False
def test_validate_rejects_missing_contact_name() -> None:
data = {
"contact": {"name": "", "phone": "555"},
"service": {"address": "1 St", "city": "X", "state": "NH"},
"checklist": ["do thing"],
}
try:
validate_request(data)
except ValueError as exc:
assert "contact.name" in str(exc)
else:
raise AssertionError("should reject empty contact name")
def test_validate_rejects_missing_service_address() -> None:
data = {
"contact": {"name": "A", "phone": "555"},
"service": {"address": "", "city": "X", "state": "NH"},
"checklist": ["do thing"],
}
try:
validate_request(data)
except ValueError as exc:
assert "service.address" in str(exc)
else:
raise AssertionError("should reject empty service address")
def test_validate_rejects_empty_checklist() -> None:
data = {
"contact": {"name": "A", "phone": "555"},
"service": {"address": "1 St", "city": "X", "state": "NH"},
"checklist": [],
}
try:
validate_request(data)
except ValueError as exc:
assert "checklist" in str(exc)
else:
raise AssertionError("should reject empty checklist")
def test_render_markdown_contains_key_sections() -> None:
data = load_request("docs/nh-broadband-install-request.example.yaml")
packet = build_packet(data)
md = render_markdown(packet, data)
assert "# NH Broadband Install Packet" in md
assert "## Contact" in md
assert "## Service Address" in md
assert "## Call Log" in md
assert "## Appointment Checklist" in md
assert "Concord" in md
assert "NH" in md
def test_render_markdown_shows_checklist_items() -> None:
data = load_request("docs/nh-broadband-install-request.example.yaml")
packet = build_packet(data)
md = render_markdown(packet, data)
assert "- [ ] Confirm exact-address availability" in md
def test_example_yaml_is_valid() -> None:
data = yaml.safe_load(Path("docs/nh-broadband-install-request.example.yaml").read_text())
assert data["contact"]["name"] == "Timmy Operator"
assert len(data["checklist"]) == 8