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Author SHA1 Message Date
Alexander Whitestone
79b841727f docs: add timmy-dispatch genome artifact (#682) 2026-04-15 02:33:19 -04:00
3016e012cc Merge PR #739: feat: add laptop fleet planner scaffold (#530) 2026-04-15 06:17:19 +00:00
60b9b90f34 Merge PR #738: feat: add Know Thy Father epic orchestrator 2026-04-15 06:12:05 +00:00
Alexander Whitestone
c818a30522 feat: add laptop fleet planner scaffold (#530)
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2026-04-15 02:11:31 -04:00
Alexander Whitestone
89dfa1e5de feat: add Know Thy Father epic orchestrator (#582)
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2026-04-15 01:52:58 -04:00
Alexander Whitestone
d791c087cb feat: add Ezra mempalace integration packet (#570)
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2026-04-15 01:37:47 -04:00
15 changed files with 1243 additions and 254 deletions

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# 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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# 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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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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# 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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# GENOME.md — timmy-dispatch
Generated: 2026-04-15 02:29:00 EDT
Analyzed repo: Timmy_Foundation/timmy-dispatch
Analyzed commit: 730dde8
Host issue: timmy-home #682
## Project Overview
`timmy-dispatch` is a small, script-first orchestration repo for a cron-driven Hermes fleet. It does not try to be a general platform. It is an operator's toolbelt for one specific style of swarm work:
- select a Gitea issue
- build a self-contained prompt
- run one cheap-model implementation pass
- push a branch and PR back to Forge
- measure what the fleet did overnight
The repo is intentionally lightweight:
- 7 Python files
- 4 shell entry points
- a checked-in `GENOME.md` already present on the analyzed repo's `main`
- generated telemetry state committed in `telemetry/`
- no tests on `main` (`python3 -m pytest -q` -> `no tests ran in 0.01s`)
A crucial truth about this ticket: the analyzed repo already contains a genome on `main`, and it already has an open follow-up issue for test coverage:
- `timmy-dispatch#1` — genome file already present on main
- `timmy-dispatch#3` — critical-path tests still missing
So this host-repo artifact is not pretending to discover a blank slate. It is documenting the repo's real current state for the cross-repo genome lane in `timmy-home`.
## Architecture
```mermaid
graph TD
CRON[crontab] --> LAUNCHER[bin/sprint-launcher.sh]
CRON --> COLLECTOR[bin/telemetry-collector.py]
CRON --> MONITOR[bin/sprint-monitor.sh]
CRON --> WATCHDOG[bin/model-watchdog.py]
CRON --> ANALYZER[bin/telemetry-analyzer.py]
LAUNCHER --> RUNNER[bin/sprint-runner.py]
LAUNCHER --> GATEWAY[optional gateway on :8642]
LAUNCHER --> CLI[hermes chat fallback]
RUNNER --> GITEA[Gitea API]
RUNNER --> LLM[OpenAI SDK\nNous or Ollama]
RUNNER --> TOOLS[local tools\nrun_command/read_file/write_file/gitea_api]
RUNNER --> TMP[/tmp/sprint-* workspaces]
RUNNER --> RESULTS[~/.hermes/logs/sprint/results.csv]
AGENTDISPATCH[bin/agent-dispatch.sh] --> HUMAN[human/operator copy-paste into agent UI]
AGENTLOOP[bin/agent-loop.sh] --> TMUX[tmux worker panes]
WATCHDOG --> TMUX
SNAPSHOT[bin/tmux-snapshot.py] --> TELEMETRY[telemetry/*.jsonl]
COLLECTOR --> TELEMETRY
ANALYZER --> REPORT[overnight report text]
DISPATCHHEALTH[bin/dispatch-health.py] --> TELEMETRY
```
## Entry Points
### `bin/sprint-launcher.sh`
Primary cron-facing shell entry point.
Responsibilities:
- allocate a unique `/tmp/sprint-*` workspace
- fetch open issues from Gitea
- choose the first non-epic, non-study issue
- write a fully self-contained prompt file
- try the local Hermes gateway first
- fall back to `hermes chat` CLI if the gateway is down
- record result rows in `~/.hermes/logs/sprint/results.csv`
- prune old workspaces and old logs
### `bin/sprint-runner.py`
Primary Python implementation engine.
Responsibilities:
- read active provider settings from `~/.hermes/config.yaml`
- read auth from `~/.hermes/auth.json`
- route through OpenAI SDK to the currently active provider
- implement a tiny local tool-calling loop with 4 tools:
- `run_command`
- `read_file`
- `write_file`
- `gitea_api`
- clone repo, branch, implement, commit, push, PR, comment
This is the cognitive core of the repo.
### `bin/agent-loop.sh`
Persistent tmux worker loop.
This is important because it soft-conflicts with the README claim that the system “does NOT run persistent agent loops.” It clearly does support them as an alternate lane.
### `bin/agent-dispatch.sh`
Manual one-shot prompt generator.
It packages all of the context, token, repo, issue, and Git/Gitea commands into a copy-pasteable prompt for another agent.
### Telemetry/ops entry points
- `bin/telemetry-collector.py`
- `bin/telemetry-analyzer.py`
- `bin/sprint-monitor.sh`
- `bin/dispatch-health.py`
- `bin/tmux-snapshot.py`
- `bin/model-watchdog.py`
- `bin/nous-auth-refresh.py`
These form the observability layer around dispatch.
## Data Flow
### Autonomous sprint path
1. cron starts `bin/sprint-launcher.sh`
2. launcher fetches open issues from Gitea
3. launcher filters out epic/study work
4. launcher writes a self-contained prompt to a temp workspace
5. launcher tries gateway API on `localhost:8642`
6. if gateway is unavailable, launcher falls back to `hermes chat`
7. or, in the separate Python lane, `bin/sprint-runner.py` directly calls an LLM provider via the OpenAI SDK
8. model requests local tool calls
9. local tool functions execute subprocess/Gitea/file actions
10. runner logs results and writes success/failure to `results.csv`
### Telemetry path
1. `bin/telemetry-collector.py` samples tmux, cron, Gitea, sprint activity, and process liveness
2. it appends snapshots to `telemetry/metrics.jsonl`
3. it emits state changes to `telemetry/events.jsonl`
4. it stores a reduced comparison state in `telemetry/last_state.json`
5. `bin/telemetry-analyzer.py` summarizes those snapshots into a morning report
6. `bin/dispatch-health.py` separately checks whether the system is actually doing work, not merely running processes
## Key Abstractions
### Stateless sprint model
The repo's main philosophical abstraction is that each sprint run is disposable.
State lives in:
- Gitea
- tmux session topology
- log files
- telemetry JSONL streams
Not in a long-running queue or orchestration daemon.
### Self-contained prompt contract
`bin/agent-dispatch.sh` and `bin/sprint-launcher.sh` both assume that the work unit can be described as a prompt containing:
- issue context
- API URLs
- token path or token value
- branching instructions
- PR creation instructions
That is a very opinionated orchestration primitive.
### Local tool-calling shim
`bin/sprint-runner.py` reimplements a tiny tool layer locally instead of using the Hermes gateway tool registry. That makes it simple and portable, but also means duplicated tool logic and duplicated security risk.
### Telemetry-as-paper-artifact
The repo carries a `paper/` directory with a research framing around “hierarchical self-orchestration.” The telemetry directory is part of that design — not just ops exhaust, but raw material for claims.
## API Surface
### Gitea APIs consumed
- repo issue listing
- issue detail fetch
- PR creation
- issue comment creation
- repo metadata queries
- commit/PR count sampling in telemetry
### LLM APIs consumed
Observed paths in code/docs:
- Nous inference API
- local Ollama-compatible endpoint
- gateway `/v1/chat/completions` when available
### File/state APIs produced
- `~/.hermes/logs/sprint/*.log`
- `~/.hermes/logs/sprint/results.csv`
- `telemetry/metrics.jsonl`
- `telemetry/events.jsonl`
- `telemetry/last_state.json`
- telemetry snapshots under `telemetry/snapshots/`
## Test Coverage Gaps
### Current state
On the analyzed repo's `main`:
- `python3 -m pytest -q` -> `no tests ran in 0.01s`
- `python3 -m py_compile bin/*.py` -> passes
- `bash -n bin/*.sh` -> passes
So the repo is parse-clean but untested.
### Important nuance
This is already known upstream:
- `timmy-dispatch#3` explicitly tracks critical-path tests for the repo (issue #3 in the analyzed repo)
That means the honest genome should say:
- test coverage is missing on `main`
- but the gap is already recognized in the analyzed repo itself
### Most important missing lanes
1. `sprint-runner.py`
- provider selection
- fallback behavior
- tool-dispatch semantics
- result logging
2. `telemetry-collector.py`
- state diff correctness
- event emission correctness
- deterministic cron drift detection
3. `model-watchdog.py`
- profile/model expectation map
- drift detection and fix behavior
4. `agent-loop.sh`
- work selection and skip-list handling
- lock discipline
5. `sprint-launcher.sh`
- issue selection and gateway/CLI fallback path
## Security Considerations
### 1. Token handling is shell-centric and leaky
The repo frequently assumes tokens are read from files and injected into:
- shell variables
- curl headers
- clone URLs
- copy-paste prompts
This is operationally convenient but expands exposure through:
- process list leakage
- logs
- copied prompt artifacts
- shell history if mishandled
### 2. Arbitrary shell execution is a core feature
`run_command` in `sprint-runner.py` is intentionally broad. That is fine for a trusted operator loop, but it means this repo is a dispatch engine, not a sandbox.
### 3. `/tmp` workspace exposure
The default sprint workspace location is `/tmp/sprint-*`. On a shared multi-user machine, that is weaker isolation than a private worktree root.
### 4. Generated telemetry is committed
`telemetry/events.jsonl` and `telemetry/last_state.json` are on `main`. That can be useful for paper artifacts, but it also means runtime state mixes with source history.
## Dependencies
### Runtime dependencies
- Python 3
- shell utilities (`bash`, `curl`, `tmux`, `git`)
- OpenAI-compatible SDK/runtime
- Gitea server access
- local Hermes config/auth files
### Optional/ambient dependencies
- local Hermes gateway on port `8642`
- local Ollama endpoint
- Nous portal auth state
### Documentation/research dependencies
- LaTeX toolchain for `paper/`
## Deployment
This repo is not a service deployment repo in the classic sense. It is an operator repo.
Typical live environment assumptions:
- cron invokes shell/Python entry points
- tmux sessions hold worker panes
- Hermes is already installed elsewhere
- Gitea and auth are already provisioned
Minimal validation I ran:
- `python3 -m py_compile /tmp/timmy-dispatch-genome/bin/*.py`
- `bash -n /tmp/timmy-dispatch-genome/bin/*.sh`
- `python3 -m pytest -q` -> no tests present
## Technical Debt
### 1. README contradiction about persistent loops
README says:
- “The system does NOT run persistent agent loops.”
But the repo clearly ships `bin/agent-loop.sh`, described as a persistent tmux-based worker loop.
That is the most important docs drift in the repo.
### 2. Two orchestration philosophies coexist
- cron-fired disposable runs
- persistent tmux workers
Both may be intentional, but the docs do not clearly state which is canonical versus fallback/legacy.
### 3. Target repo already has a genome, but the host issue still exists
This timmy-home genome issue is happening after `timmy-dispatch` already gained:
- `GENOME.md` on `main`
- open issue `#3` for missing tests
That is not bad, but it means the cross-repo genome process and the target repo's own documentation lane are out of sync.
### 4. Generated/runtime artifacts mixed into source tree
Telemetry and research assets are part of the repo history. That may be intentional for paper-writing, but it makes source metrics noisier and can blur runtime-vs-source boundaries.
## Existing Work Already on Main
The analyzed repo already has two important genome-lane artifacts:
- `GENOME.md` on `main`
- open issue `timmy-dispatch#3` tracking critical-path tests
So the most honest statement for `timmy-home#682` is:
- the genome itself is already present in the target repo
- the remaining missing piece on the target repo is test coverage
- this host-repo artifact exists to make the cross-repo analysis lane explicit and traceable
## Bottom Line
`timmy-dispatch` is a small but very revealing repo. It embodies the Timmy Foundation's dispatch style in concentrated form:
- script-first
- cron-first
- tmux-aware
- Gitea-centered
- cheap-model friendly
- operator-visible
Its biggest weakness is not code volume. It is architectural ambiguity in the docs and a complete lack of tests on `main` despite being a coordination-critical repo.

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# Phase 4 Sovereignty Audit
Generated: 2026-04-15 00:45:01 EDT
Issue: #551
Scope: repo-grounded audit of whether `timmy-home` currently proves **[PHASE-4] Sovereignty - Zero Cloud Dependencies**
## Phase Definition
Issue #551 defines Phase 4 as:
- no API call leaves your infrastructure
- no rate limits
- no censorship
- no shutdown dependency
- trigger condition: all Phase-3 buildings operational and all models running locally
The milestone sentence is explicit:
> “A model ran locally for the first time. No cloud. No rate limits. No one can turn it off.”
This audit asks a narrower, truthful question:
**Does the current `timmy-home` repo prove that the Timmy harness is already in Phase 4?**
## Current Repo Evidence
### 1. The repo already contains a local-only cutover diagnosis — and it says the harness is not there yet
Primary source:
- `specs/2026-03-29-local-only-harness-cutover-plan.md`
That plan records a live-state audit from 2026-03-29 and names concrete blockers:
- active cloud default in `~/.hermes/config.yaml`
- cloud fallback entries
- enabled cron inheritance risk
- legacy remote ops scripts still on the active path
- optional Groq offload still present in the Nexus path
Direct repo-grounded examples from that file:
- `model.default: gpt-5.4`
- `model.provider: openai-codex`
- `model.base_url: https://chatgpt.com/backend-api/codex`
- custom provider: Google Gemini
- fallback path still pointing to Gemini
- active cloud escape path via `groq_worker.py`
The same cutover plan defines “done” in stricter terms than the issue body and plainly says those conditions were not yet met.
### 2. The baseline report says sovereignty is still overwhelmingly cloud-backed
Primary source:
- `reports/production/2026-03-29-local-timmy-baseline.md`
That report gives the clearest quantitative evidence in this repo:
- sovereignty score: `0.7%` local
- sessions: `403 total | 3 local | 400 cloud`
- estimated cloud cost: `$125.83`
That is incompatible with any honest claim that Phase 4 has already been reached.
The same baseline also says:
- local mind: alive
- local session partner: usable
- local Hermes agent: not ready
So the repo's own truthful baseline says local capability exists, but zero-cloud operational sovereignty does not.
### 3. The model tracker is built to measure local-vs-cloud reality because the transition is not finished
Primary source:
- `metrics/model_tracker.py`
This file tracks:
- `local_sessions`
- `cloud_sessions`
- `local_pct`
- `est_cloud_cost`
- `est_saved`
That means the repo is architected to monitor a sovereignty transition, not to assume it is already complete.
### 4. There is already a proof harness — and its existence implies proof is still needed
Primary source:
- `scripts/local_timmy_proof_test.py`
This script explicitly searches for cloud/remote markers including:
- `chatgpt.com/backend-api/codex`
- `generativelanguage.googleapis.com`
- `api.groq.com`
- `143.198.27.163`
It also frames the output question as:
- is the active harness already local-only?
- why or why not?
A repo does not add a proof script like this if the zero-cloud cutover is already a settled fact.
### 5. The local subtree is stronger than the harness, but it is still only the target architecture
Primary sources:
- `LOCAL_Timmy_REPORT.md`
- `timmy-local/README.md`
`LOCAL_Timmy_REPORT.md` documents real local-first building blocks:
- local caching
- local Evennia world shell
- local ingestion pipeline
- prompt warming
Those are important Phase-4-aligned components.
But the broader repo still includes evidence of non-sovereign dependencies or remote references, such as:
- `scripts/evennia/bootstrap_local_evennia.py` defaulting operator email to `alexpaynex@gmail.com`
- `timmy-local/evennia/commands/tools.py` hardcoding `http://143.198.27.163:3000/...`
- `uni-wizard/tools/network_tools.py` hardcoding `GITEA_URL = "http://143.198.27.163:3000"`
- `uni-wizard/v2/task_router_daemon.py` defaulting `--gitea-url` to that same remote endpoint
These are not necessarily cloud inference dependencies, but they are still external dependency anchors inconsistent with the spirit of “No cloud. No rate limits. No one can turn it off.”
## Contradictions and Drift
### Contradiction A — local architecture exists, but repo evidence says cutover is incomplete
- `LOCAL_Timmy_REPORT.md` celebrates local infrastructure delivery.
- `reports/production/2026-03-29-local-timmy-baseline.md` still records `400 cloud` sessions and `0.7%` local.
These are not actually contradictory if read honestly:
- the local stack was delivered
- the fleet had not yet switched over to it
### Contradiction B — the local README was overstating current reality
Before this PR, `timmy-local/README.md` said the stack:
- “Runs entirely on your hardware with no cloud dependencies for core functionality.”
That sentence was too strong given the rest of the repo evidence:
- cloud defaults were still documented in the cutover plan
- cloud session volume was still quantified in the baseline report
- remote service references still existed across multiple scripts
This PR fixes that wording so the README describes `timmy-local` as the destination shape, not proof that the whole harness is already sovereign.
### Contradiction C — Phase 4 wants zero cloud dependencies, but the repo still documents explicit cloud-era markers
The repo itself still names or scans for:
- `openai-codex`
- `chatgpt.com/backend-api/codex`
- `generativelanguage.googleapis.com`
- `api.groq.com`
- `GROQ_API_KEY`
That does not mean the system can never become sovereign. It does mean the repo currently documents an unfinished migration boundary.
## Verdict
**Phase 4 is not yet reached.**
Why:
1. the repo's own baseline report still shows `403 total | 3 local | 400 cloud`
2. the repo's cutover plan still lists active cloud defaults and fallback paths as unresolved work
3. proof/guard scripts exist specifically to detect unresolved cloud and remote dependency markers
4. multiple runtime/ops files still point at external services such as `143.198.27.163`, `alexpaynex@gmail.com`, and Groq/OpenAI/Gemini-era paths
The truthful repo-grounded statement is:
- **local-first infrastructure exists**
- **zero-cloud sovereignty is the target**
- **the migration was not yet complete at the time this repo evidence was written**
## Highest-Leverage Next Actions
1. **Eliminate cloud defaults and hidden fallbacks first**
- follow `specs/2026-03-29-local-only-harness-cutover-plan.md`
- remove `openai-codex`, Gemini fallback, and any active cloud default path
2. **Kill cron inheritance bugs**
- no enabled cron should run with null model/provider if cloud defaults still exist anywhere
3. **Quarantine remote-ops scripts and hardcoded remote endpoints**
- `143.198.27.163` still appears in active repo scripts and command surfaces
- move legacy remote ops into quarantine or replace with local truth surfaces
4. **Run and preserve proof artifacts, not just intentions**
- the repo already has `scripts/local_timmy_proof_test.py`
- use it as the phase-gate proof generator
5. **Use the sovereignty scoreboard as a real gate**
- Phase 4 should not be declared complete while reports still show materially nonzero cloud sessions as the operating norm
## Definition of Done
Issue #551 should only be considered truly complete when the repo can point to evidence that all of the following are true:
1. no active model default points to a remote inference API
2. no fallback path silently escapes to cloud inference
3. no enabled cron can inherit a remote model/provider
4. active runtime paths no longer depend on Groq/OpenAI/Gemini-era inference markers
5. operator-critical services do not depend on external platforms like Gmail
6. remote hardcoded ops endpoints such as `143.198.27.163` are removed from the active Timmy path or clearly quarantined
7. the local proof script passes end-to-end
8. the sovereignty scoreboard shows cloud usage reduced to the point that “Zero Cloud Dependencies” is a truthful operational statement, not just an architectural aspiration
## Recommendation for This PR
This PR should **advance** Phase 4 by making the repo's public local-first docs honest and by recording a clear audit of why the milestone remains open.
That means the right PR reference style is:
- `Refs #551`
not:
- `Closes #551`
because the evidence in this repo shows the milestone is still in progress.
*Sovereignty and service always.*

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#!/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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#!/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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#!/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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@@ -1,46 +0,0 @@
from pathlib import Path
REPORT = Path("reports/evaluations/2026-04-15-phase-4-sovereignty-audit.md")
README = Path("timmy-local/README.md")
def _report() -> str:
return REPORT.read_text()
def _readme() -> str:
return README.read_text()
def test_phase4_audit_report_exists() -> None:
assert REPORT.exists()
def test_phase4_audit_report_has_required_sections() -> None:
content = _report()
assert "# Phase 4 Sovereignty Audit" in content
assert "## Phase Definition" in content
assert "## Current Repo Evidence" in content
assert "## Contradictions and Drift" in content
assert "## Verdict" in content
assert "## Highest-Leverage Next Actions" in content
assert "## Definition of Done" in content
def test_phase4_audit_captures_key_repo_findings() -> None:
content = _report()
assert "#551" in content
assert "0.7%" in content
assert "400 cloud" in content
assert "openai-codex" in content
assert "GROQ_API_KEY" in content
assert "143.198.27.163" in content
assert "not yet reached" in content.lower()
def test_timmy_local_readme_is_honest_about_phase4_status() -> None:
content = _readme()
assert "Phase 4" in content
assert "zero-cloud sovereignty is not yet complete" in content
assert "no cloud dependencies for core functionality" not in content

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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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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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@@ -0,0 +1,68 @@
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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@@ -0,0 +1,39 @@
from pathlib import Path
GENOME = Path("genomes/timmy-dispatch-GENOME.md")
def _content() -> str:
return GENOME.read_text()
def test_timmy_dispatch_genome_exists() -> None:
assert GENOME.exists()
def test_timmy_dispatch_genome_has_required_sections() -> None:
content = _content()
assert "# GENOME.md — timmy-dispatch" in content
assert "## Project Overview" in content
assert "## Architecture" in content
assert "```mermaid" in content
assert "## Entry Points" in content
assert "## Data Flow" in content
assert "## Key Abstractions" in content
assert "## API Surface" in content
assert "## Test Coverage Gaps" in content
assert "## Security Considerations" in content
assert "## Dependencies" in content
assert "## Deployment" in content
assert "## Technical Debt" in content
def test_timmy_dispatch_genome_captures_repo_specific_findings() -> None:
content = _content()
assert "bin/sprint-runner.py" in content
assert "bin/telemetry-collector.py" in content
assert "bin/model-watchdog.py" in content
assert "tmux" in content
assert "results.csv" in content
assert "issue #3" in content.lower() or "issue #3" in content

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@@ -1,6 +1,6 @@
# Timmy Local — Sovereign AI Infrastructure
Local infrastructure for Timmy's sovereign AI operation. This subtree is the local-first target architecture, but **Phase 4 zero-cloud sovereignty is not yet complete** across the wider Timmy harness.
Local infrastructure for Timmy's sovereign AI operation. Runs entirely on your hardware with no cloud dependencies for core functionality.
## Quick Start
@@ -176,7 +176,7 @@ gitea:
└────────┘ └────────┘ └────────┘
```
Local Timmy is the sovereign target architecture for the fleet. The wider harness still contains cloud-era defaults, remote service references, and cutover work tracked under Phase 4, so this repo should be read as the destination shape rather than proof that zero-cloud sovereignty is already complete.
Local Timmy operates sovereignly. Cloud backends provide additional capacity but Timmy survives without them.
## Performance Targets