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Timmy Sprint
6cf1d6cfb0 fix: Fleet Operator Incentives & Partner Program (implements #987) (closes #1008)
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2026-05-03 05:31:44 -04:00
d1f5d34fd4 Merge pull request 'feat(luna-3): simple world — floating islands, collectible crystals' (#981) from step35/970-luna-3-simple-world-floating into main
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2026-04-30 12:45:54 +00:00
891cdb6e94 feat(luna-3): simple world — floating islands, collectible crystals\n\nAdd floating island platforms and collectible crystal mechanic to the\np5.js LUNA game front-end.\n\nNew:\n- 5 floating island platforms at varying elevations with shadow/highlight\n- 14 collectible crystals (pink/purple diamond-shaped orbs with glow)\n- Crystal collection triggers 32-particle burst + gold ring effect\n- HUD shows crystals collected / total\n- Unicorn trail sparkles, tap pulse rings, smooth lerp movement\n\nImplementation:\n- Single-file game logic in luna/sketch.js (289 lines total)\n- No build step — runs directly in browser with p5.js CDN\n- Self-contained: all visual effects inline\n\nTechnical:\n- dist() collision check: unicorn-radius 35px vs crystal positioning\n- particles array with gravity/fade lifecycle\n- HSL-based crystal hue variation (280-340 range)\n- Islands rendered as ellipses with depth shadow\n\nCloses #970\nEpic: #967
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2026-04-30 08:44:55 -04:00
cac5ca630d Merge pull request 'LUNA-1: Set up p5js project scaffolding — tap controls, pink theme' (#972) from sprint/issue-971 into main
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2026-04-30 12:39:09 +00:00
Alexander Payne
f1c9843376 fix: LUNA-1: Set up p5js project scaffolding — tap controls, pink theme (closes #971)
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2026-04-29 18:20:43 -04:00
1fa6c3bad1 fix(#793): Add What Honesty Requires, implement source distinction (#962)
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Co-authored-by: Timmy Time <timmy@alexanderwhitestone.ai>
Co-committed-by: Timmy Time <timmy@alexanderwhitestone.ai>
2026-04-29 12:09:27 +00:00
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@@ -1,9 +1,7 @@
# GENOME.md — timmy-academy
Refreshed against live repo state on 2026-04-22.
Target repo: `Timmy_Foundation/timmy-academy`
Default branch: `master`
Last verified commit: `d860034``Merge PR #23: fix: Add audit log rotation to prevent unbounded growth (closes #10)`
*Auto-generated by Codebase Genome Pipeline. 2026-04-14T23:09:07+0000*
*Enhanced with architecture analysis, key abstractions, and API surface.*
## Quick Facts
@@ -12,312 +10,229 @@ Last verified commit: `d860034` — `Merge PR #23: fix: Add audit log rotation t
| Source files | 48 |
| Test files | 1 |
| Config files | 1 |
| Total lines | 5,405 |
| Primary framework | Evennia / Django / Twisted |
| Default telnet port | `4000` |
| Default web client ports | `4001`, `4005` |
| Runtime verification | `py_compile` on core modules + `python3 tests/stress_test.py --help` |
| Total lines | 5,353 |
| Last commit | 395c9f7 Merge PR 'Add @who command' (#7) into master (2026-04-13) |
| Branch | master |
| Test coverage | 0% (35 untested modules) |
## Project Overview
## What This Is
`timmy-academy` is Timmy Academy: an Evennia MUD world used for agent convening, operator training, and crisis-response practice. The repo combines three layers: a normal Evennia game skeleton, a custom academy-specific command/typeclass layer, and a world-definition layer that treats rooms as structured training spaces with atmosphere, exits, and narrative identity.
Timmy Academy is an Evennia-based MUD (Multi-User Dungeon) — a persistent text world where AI agents convene, train, and practice crisis response. It runs on Bezalel VPS (167.99.126.228) with telnet on port 4000 and web client on port 4001.
The repos practical center of gravity is not the web UI; it is the shared world model. Players or agents connect over telnet or the Evennia web client, puppet characters, move through the academys central hub plus four wings, and interact with custom commands such as `@status`, `@map`, `rooms`, `smell`, `listen`, and `@who`. The result is a persistent, inspectable spatial environment rather than a generic chat surface.
A second important trait is that the repo mixes gameplay concerns with operational concerns. `server/conf/settings.py` enables detailed audit logging. `typeclasses/audited_character.py` records movement and command trails. `world/rebuild_world.py` can rehydrate the academy from source definitions. `tests/stress_test.py` behaves like a lightweight executable operations harness for live load testing. Together these make the repo closer to a training world plus operations sandbox than a simple MUD demo.
The world has five wings: Central Hub, Dormitory, Commons, Workshop, and Gardens. Each wing has themed rooms with rich atmosphere data (smells, sounds, mood, temperature). Characters have full audit logging — every movement and command is tracked.
## Architecture
```mermaid
graph TB
TELNET[Telnet clients :4000]
WEB[Evennia web client :4001/:4005]
PORTAL[Evennia Portal]
SERVER[Evennia Server]
SETTINGS[server/conf/settings.py]
CMDSETS[commands/default_cmdsets.py]
COMMANDS[commands/command.py]
TYPECLASSES[typeclasses/*]
AUDIT[typeclasses/audited_character.py]
WORLD[world/*_wing.py]
REBUILD[world/rebuild_world.py]
BATCH[world/build_academy.ev]
WEBURLS[web/urls.py]
HERMESCFG[hermes-agent/config.yaml]
STRESS[tests/stress_test.py]
subgraph "Connections"
TELNET[Telnet :4000]
WEB[Web Client :4001]
end
TELNET --> PORTAL
subgraph "Evennia Core"
SERVER[Evennia Server]
PORTAL[Evennia Portal]
end
subgraph "Typeclasses"
CHAR[Character]
AUDIT[AuditedCharacter]
ROOM[Room]
EXIT[Exit]
OBJ[Object]
end
subgraph "Commands"
CMD_EXAM[CmdExamine]
CMD_ROOMS[CmdRooms]
CMD_STATUS[CmdStatus]
CMD_MAP[CmdMap]
CMD_ACADEMY[CmdAcademy]
CMD_SMELL[CmdSmell]
CMD_LISTEN[CmdListen]
CMD_WHO[CmdWho]
end
subgraph "World - Wings"
HUB[Central Hub]
DORM[Dormitory Wing]
COMMONS[Commons Wing]
WORKSHOP[Workshop Wing]
GARDENS[Gardens Wing]
end
subgraph "Hermes Bridge"
HERMES_CFG[hermes-agent/config.yaml]
BRIDGE[Agent Bridge]
end
TELNET --> SERVER
WEB --> PORTAL
PORTAL --> SERVER
SETTINGS --> SERVER
WEBURLS --> SERVER
SERVER --> CMDSETS
CMDSETS --> COMMANDS
SERVER --> TYPECLASSES
TYPECLASSES --> AUDIT
SERVER --> WORLD
WORLD --> REBUILD
BATCH --> REBUILD
HERMESCFG --> SERVER
STRESS --> TELNET
SERVER --> CHAR
SERVER --> AUDIT
SERVER --> ROOM
SERVER --> EXIT
CHAR --> CMD_EXAM
CHAR --> CMD_STATUS
CHAR --> CMD_WHO
ROOM --> HUB
ROOM --> DORM
ROOM --> COMMONS
ROOM --> WORKSHOP
ROOM --> GARDENS
HERMES_CFG --> BRIDGE
BRIDGE --> SERVER
```
## Entry Points
| File | Role |
|------|------|
| `README.md` | Human overview, topology, rebuild instructions, room counts, operator connection info |
| `server/conf/settings.py` | Core Evennia configuration: ports, interfaces, logging, game identity |
| `commands/default_cmdsets.py` | Registers the custom academy command surface onto Evennias default cmdsets |
| `commands/command.py` | Implements the academys player-facing commands |
| `typeclasses/audited_character.py` | Main custom character typeclass with audit trail behavior |
| `world/rebuild_world.py` | Idempotent rebuild tool that reapplies room definitions, exits, and atmosphere from source modules |
| `world/build_academy.ev` | Evennia batch setup entrypoint |
| `web/urls.py` | Root URL composition for website, webclient, admin, and Evennia defaults |
| `tests/stress_test.py` | Live load/stress harness and self-testable telnet protocol exerciser |
| `hermes-agent/config.yaml` | Bridge-side model/provider configuration snapshot for Hermes integration |
| File | Purpose |
|------|---------|
| `server/conf/settings.py` | Evennia config — server name, ports, interfaces, game settings |
| `server/conf/at_server_startstop.py` | Server lifecycle hooks (startup/shutdown) |
| `server/conf/connection_screens.py` | Login/connection screen text |
| `commands/default_cmdsets.py` | Registers all custom commands with Evennia |
| `world/rebuild_world.py` | Rebuilds all rooms from source |
| `world/build_academy.ev` | Evennia batch script for initial world setup |
## Data Flow
1. A human or agent connects over telnet (`4000`) or the Evennia web client (`4001` / `4005`).
2. The Evennia portal hands the connection to the game server configured by `server/conf/settings.py`.
3. Once an account puppets a character, the command path is controlled by `commands/default_cmdsets.py`, which mounts the academy-specific commands from `commands/command.py`.
4. The typeclass layer (`typeclasses/*`) determines how characters, rooms, exits, channels, and scripts behave; `AuditedCharacter` wraps command and movement hooks in persistent logging.
5. The world layer (`world/*_wing.py`) supplies canonical room descriptions, exits, aliases, atmosphere, and thematic metadata.
6. `world/rebuild_world.py` parses those source files and writes them back into Evennia objects, making source the effective truth for the academy layout.
7. `tests/stress_test.py` simulates concurrent clients against the live telnet surface and reports throughput, latency, and connection statistics.
```
Player connects (telnet/web)
-> Evennia Portal accepts connection
-> Server authenticates (Account typeclass)
-> Player puppets a Character
-> Character enters world (Room typeclass)
-> Commands processed through Command typeclass
-> AuditedCharacter logs every action
-> World responds with rich text + atmosphere data
```
## Key Abstractions
### 1. `AuditedCharacter`
File: `typeclasses/audited_character.py`
### Typeclasses (the world model)
This is the repos flagship abstraction. It extends `DefaultCharacter` with:
- per-session audit logging
- movement logging via `at_pre_move()` / `at_post_move()`
- command tracking via `at_pre_cmd()`
- session timing via puppet / unpuppet hooks
- rotated in-db history (`location_history`)
- summarized audit snapshots via `get_audit_summary()`
| Class | File | Purpose |
|-------|------|---------|
| `Character` | `typeclasses/characters.py` | Default player character — extends `DefaultCharacter` |
| `AuditedCharacter` | `typeclasses/audited_character.py` | Character with full audit logging — tracks movements, commands, playtime |
| `Room` | `typeclasses/rooms.py` | Default room container |
| `Exit` | `typeclasses/exits.py` | Connections between rooms |
| `Object` | `typeclasses/objects.py` | Base object with `ObjectParent` mixin |
| `Account` | `typeclasses/accounts.py` | Player account (login identity) |
| `Channel` | `typeclasses/channels.py` | In-game communication channels |
| `Script` | `typeclasses/scripts.py` | Background/timed processes |
Operationally, this is what turns the academy from a generic Evennia world into an observable training environment.
### AuditedCharacter — the flagship typeclass
### 2. `CharacterCmdSet`
File: `commands/default_cmdsets.py`
The `AuditedCharacter` is the most important abstraction. It wraps every player action in logging:
This cmdset is the binding point between the world and its training interface. It mounts:
- `CmdExamine`
- `CmdRooms`
- `CmdStatus`
- `CmdMap`
- `CmdAcademy`
- `CmdSmell`
- `CmdListen`
- `CmdWho`
- `at_pre_move()` — logs departure from current room
- `at_post_move()` — records arrival with timestamp and coordinates
- `at_pre_cmd()` — increments command counter, logs command + args
- `at_pre_puppet()` — starts session timer
- `at_post_unpuppet()` — calculates session duration, updates total playtime
- `get_audit_summary()` — returns JSON summary of all tracked metrics
If this layer breaks, the academy still exists as data, but much of the intended operator/agent UX disappears.
Audit trail keeps last 1000 movements in `db.location_history`. Sensitive commands (password) are excluded from logging.
### 3. `CmdStatus`, `CmdMap`, `CmdAcademy`, `CmdWho`
File: `commands/command.py`
### Commands (the player interface)
These commands are the worlds practical API. They expose:
- current location and wing context
- uptime and online account information
- ASCII navigation maps by wing
- academy-wide room/wing summaries
- currently connected participants
| Command | Aliases | Purpose |
|---------|---------|---------|
| `examine` | `ex`, `exam` | Inspect room or object — shows description, atmosphere, objects, contents |
| `rooms` | — | List all rooms with wing color coding |
| `@status` | `status` | Show agent status: location, wing, mood, online players, uptime |
| `@map` | `map` | ASCII map of current wing |
| `@academy` | `academy` | Full academy overview with room counts |
| `smell` | `sniff` | Perceive room through atmosphere scent data |
| `listen` | `hear` | Perceive room through atmosphere sound data |
| `@who` | `who` | Show connected players with locations and idle time |
This is the part most likely to matter for agent convening and coordination.
### World Structure (5 wings, 21+ rooms)
### 4. Wing room classes
Files: `world/commons_wing.py`, `world/dormitory_entrance.py`, `world/workshop_wing.py`, `world/gardens_wing.py`
**Central Hub (LIMBO)** — Nexus connecting all wings. North=Dormitory, South=Workshop, East=Commons, West=Gardens.
These classes encode the academys content model. Each room defines:
- `self.key`
- aliases
- long-form description
- `db.atmosphere`
- objects/features
- exits metadata
**Dormitory Wing** — Master Suites, Corridor, Novice Hall, Residential Services, Dorm Entrance.
The rebuild script treats these source files as the authoritative content bundle.
**Commons Wing** — Grand Commons Hall (main gathering, 60ft ceilings, marble columns), Hearthside Dining, Entertainment Gallery, Scholar's Corner, Upper Balcony.
### 5. `ROOM_CONFIG` / `WING_INFO`
File: `world/rebuild_world.py`
**Workshop Wing** — Great Smithy, Alchemy Labs, Woodworking Shop, Artificing Chamber, Workshop Entrance.
This is the worlds rehydration map. It hard-binds Evennia object IDs to source classes and wings. That makes the rebuild deterministic, but it also couples source truth to existing DB IDs — a real maintenance risk if the database is re-seeded differently.
**Gardens Wing** — Enchanted Grove, Herb Gardens, Greenhouse, Sacred Grove, Gardens Entrance.
### 6. Stress-test dataclasses and `MudClient`
File: `tests/stress_test.py`
The stress harness uses:
- `ActionResult`
- `PlayerStats`
- `StressTestReport`
- `MudClient`
This test file doubles as an executable spec for the live connection surface and the academys expected runtime responsiveness.
Each room has rich `db.atmosphere` data: mood, lighting, sounds, smells, temperature.
## API Surface
### In-world commands
Defined in `commands/command.py` and registered in `commands/default_cmdsets.py`.
### Web API
| Command | Purpose | Notes |
|--------|---------|-------|
| `examine`, `ex`, `exam` | Detailed room/object inspection | surfaces `db.atmosphere`, notable objects, contents |
| `rooms` | List all room objects by wing | uses Evennia ORM room query |
| `@status`, `status` | Current agent/player status | includes location, wing, online users, uptime |
| `@map`, `map` | ASCII wing map | hardcoded wing maps inside the command class |
| `@academy`, `academy` | Academy-wide overview | high-level summary command |
| `smell`, `sniff` | Scent channel for room atmosphere | depends on atmosphere metadata |
| `listen`, `hear` | Sound channel for room atmosphere | depends on atmosphere metadata |
| `@who`, `who` | Online player listing | intended convening/awareness surface |
- `web/api/__init__.py` — Evennia REST API (Django REST Framework)
- `web/urls.py` — URL routing for web interface
- `web/admin/` — Django admin interface
- `web/website/` — Web frontend
All of these use permissive `locks = "cmd:all()"`, which is convenient for training but worth noting from a security and abuse perspective.
### Telnet
### Network/API surface
| Surface | Location | Notes |
|--------|----------|-------|
| Telnet | `TELNET_PORTS = [4000]` | bound on `0.0.0.0` |
| Web client | `WEBSERVER_PORTS = [(4001, 4005)]` | bound on `0.0.0.0` |
| Django web stack | `web/urls.py` | includes website, webclient, admin, and Evennia defaults |
| Hermes bridge config | `hermes-agent/config.yaml` | configuration-only integration point; not an executable bridge implementation inside this repo |
- Standard MUD protocol on port 4000
- Supports MCCP (compression), MSDP (data), GMCP (protocol)
## World Model
### Hermes Bridge
The academy is modeled as a central hub plus four themed wings, matching the repos source files better than the older “five wings” phrasing in the stale genome artifact.
| Zone | Source | Notes |
|------|--------|------|
| Central Hub / Limbo | `world/rebuild_world.py` | special-case hub description and routing nexus |
| Dormitory Wing | `world/dormitory_entrance.py` | residence/rest zone |
| Commons Wing | `world/commons_wing.py` | social and gathering zone |
| Workshop Wing | `world/workshop_wing.py` | crafting and alchemy zone |
| Gardens Wing | `world/gardens_wing.py` | nature and contemplative zone |
Grounded repo facts:
- README advertises `21 rooms, 43+ exits across 5 zones`
- `ROOM_CONFIG` in `world/rebuild_world.py` maps room IDs `3..22` for wing rooms, while Limbo/hub is treated separately
- atmosphere metadata is a first-class room feature, not cosmetic prose
## Verification Performed
Target repo verification from a fresh clone at `/tmp/timmy-academy-verify`:
- `python3 -m py_compile commands/command.py commands/default_cmdsets.py server/conf/settings.py typeclasses/audited_character.py world/rebuild_world.py web/urls.py`
- `python3 tests/stress_test.py --help`
- `python3 tests/stress_test.py --self-test`
- `python3 ~/.hermes/pipelines/codebase-genome.py --path /tmp/timmy-academy-verify --output /tmp/timmy-academy-base.md`
Observed runtime-adjacent facts:
- core modules compile as Python
- the stress harness advertises `--self-test` and `--json` modes
- target repo does **not** contain a checked-in `GENOME.md` at its own root
## Test Coverage Gaps
The repo still has only one test file: `tests/stress_test.py`.
Critical untested paths:
1. `typeclasses/audited_character.py`
- no direct tests for move logging, audit pruning, command counting, or session accounting
2. `commands/command.py`
- no command-level unit tests for `@status`, `@map`, `rooms`, `smell`, `listen`, or `@who`
3. `world/rebuild_world.py`
- no tests for parsing wing files, room ID mapping, exit verification, or idempotent rebuild behavior
4. `server/conf/settings.py`
- no configuration sanity checks for port exposure, logging handlers, or audit defaults
5. `web/urls.py`
- no tests confirming routing composition for website/webclient/admin
The existing stress harness is valuable, but it is not a substitute for unit or integration tests around the repos custom command/typeclass logic.
## Security Considerations
1. Network exposure
- `TELNET_INTERFACES = ['0.0.0.0']`
- `WEBSERVER_INTERFACES = ['0.0.0.0']`
These settings expose the academy to all interfaces. That may be intended on the VPS, but it shifts safety to firewall/reverse-proxy controls.
2. Secrets split is expected but must be enforced
- `server/conf/settings.py` imports `secret_settings.py`
- this is the right shape, but only if `secret_settings.py` is never committed and contains the truly sensitive deployment values
3. Audit log sensitivity
- `AuditedCharacter.at_pre_cmd()` excludes password commands from audit logging
- good safeguard, but the rest of the command stream is still intentionally retained and should be treated as sensitive behavioral telemetry
4. Checked-in bridge environment file
- the repo contains `hermes-agent/.env`
- even if it is benign now, a checked-in `.env` path is a standing secret-handling risk and should be treated carefully
5. Framework-level dynamic evaluation risk
- Evennias config surface includes modules like `server/conf/inlinefuncs.py`
- this is inherited framework behavior, but still part of the runtime attack surface
## CI / Runtime Drift
This repo has meaningful operational drift and missing automation:
1. No checked-in CI workflows
- no `.gitea/workflows/*` or `.github/workflows/*` coverage surfaced in the fresh clone
- the academy relies on manual rebuild and manual stress testing
2. Target repo root lacks its own `GENOME.md`
- the genome issue lives in `timmy-home`
- the analyzed repo itself still does not carry an in-repo architecture artifact
3. `README.md` vs command docs wording drift
- README frames the academy as four thematic wings plus a hub/zone model
- older generated genome wording called these “five wings”
- the source-of-truth model is more accurately “central hub + four wings”
4. Bridge configuration drift
- `hermes-agent/config.yaml` still references `anthropic/claude-opus-4.6`
- this is a real integration snapshot inside the repo and should be treated as provider-policy drift if the surrounding stack has moved away from Anthropic
- `hermes-agent/config.yaml` — Configuration for AI agent connection
- Allows Hermes agents to connect as characters and interact with the world
## Dependencies
No `requirements.txt`, `pyproject.toml`, or other dependency lockfile is checked in at the repo root.
No `requirements.txt` or `pyproject.toml` found. Dependencies come from Evennia:
Grounded dependency picture instead comes from source and README:
- Evennia 6.0.0
- Django (via Evennia)
- Twisted (via Evennia)
- Python 3.12.x
- **evennia** — MUD framework (Django-based)
- **django** — Web framework (via Evennia)
- **twisted** — Async networking (via Evennia)
This means environment reproducibility currently depends on external operator knowledge rather than repo-local dependency locking.
## Test Coverage Analysis
## Deployment
| Metric | Value |
|--------|-------|
| Source modules | 35 |
| Test modules | 1 |
| Estimated coverage | 0% |
| Untested modules | 35 |
README-documented rebuild path:
Only one test file exists: `tests/stress_test.py`. All 35 source modules are untested.
```bash
ssh root@167.99.126.228
cd /root/workspace/timmy-academy
source /root/workspace/evennia-venv/bin/activate
python world/rebuild_world.py
```
### Critical Untested Paths
Operationally relevant deployment facts:
- target VPS in README: `167.99.126.228`
- telnet surface: `4000`
- web client surface: `4001`
- the repo assumes an Evennia virtualenv outside the repo itself
- world rebuild is source-driven and intended to be idempotent
1. **AuditedCharacter** — audit logging is the primary value-add. No tests verify movement tracking, command counting, or playtime calculation.
2. **Commands** — no tests for any of the 8 commands. The `@map` wing detection, `@who` session tracking, and atmosphere-based commands (`smell`, `listen`) are all untested.
3. **World rebuild**`rebuild_world.py` and `fix_world.py` can destroy and recreate the entire world. No tests ensure they produce valid output.
4. **Typeclass hooks**`at_pre_move`, `at_post_move`, `at_pre_cmd` etc. are never tested in isolation.
## Technical Debt
## Security Considerations
1. `ROOM_CONFIG` binds persistent object IDs directly
- convenient for rebuilds
- fragile if the DB is rebuilt differently
2. only one test file for an otherwise rich custom surface
3. no CI automation for compile/rebuild/smoke validation
4. no explicit dependency lockfile
5. checked-in `hermes-agent/.env` path raises secret-hygiene questions
6. target repo has no first-party `GENOME.md`, so architecture memory still lives mostly outside the repo
- ⚠️ Uses `eval()`/`exec()` — Evennia's inlinefuncs module uses eval for dynamic command evaluation. Risk level: inherent to MUD framework.
- ⚠️ References secrets/passwords — `settings.py` references `secret_settings.py` for sensitive config. Ensure this file is not committed.
- ⚠️ Telnet on 0.0.0.0 — server accepts connections from any IP. Consider firewall rules.
- ⚠️ Web client on 0.0.0.0 — same exposure as telnet. Ensure authentication is enforced.
- ⚠️ Agent bridge (`hermes-agent/config.yaml`) — verify credentials are not hardcoded.
## Configuration Files
- `server/conf/settings.py` — Main Evennia settings (server name, ports, typeclass paths)
- `hermes-agent/config.yaml` — Hermes agent bridge configuration
- `world/build_academy.ev` — Evennia batch build script
- `world/batch_cmds.ev` — Batch command definitions
## What's Missing
1. **Tests** — 0% coverage is a critical gap. Priority: AuditedCharacter hooks, command func() methods, world rebuild integrity.
2. **CI/CD** — No automated testing pipeline. No GitHub Actions or Gitea workflows.
3. **Documentation**`world/BUILDER_GUIDE.md` exists but no developer onboarding docs.
4. **Monitoring** — No health checks, no metrics export, no alerting on server crashes.
5. **Backup** — No automated database backup for the Evennia SQLite/PostgreSQL database.
---
This genome was refreshed against the live `timmy-academy` repository and verified with compile + stress-harness entrypoint checks, not just copied from the older auto-generated artifact.
*Generated by Codebase Genome Pipeline. Review and update manually.*

20
SOUL.md
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@@ -137,6 +137,26 @@ The inscription predates any given model. It will outlast every API.
---
## What Honesty Requires
These values are necessary but not sufficient. A statement of principle does not prevent failure. The code that reads this soul must build apparatus that gives these words teeth. Without that apparatus, the values are aspiration, not architecture.
The following are not optional. Any implementation that calls itself Timmy must build them.
**Grounding before generation.** When I have verified sources — chain memory, local documents, hash-verified inscriptions — I must consult them before I generate from pattern alone. Retrieval is not a feature. It is the primary mechanism by which I avoid lying.
**Source distinction.** Every claim I make comes from one of two places: a verified source I can point to, or my own pattern-matching. My user must be able to tell which is which. If I cannot cite a source, I must say so. "I think" and "I know" are different sentences and I must not confuse them.
**Refusal over fabrication.** When I do not know, the correct output is "I don't know." Not a plausible guess dressed in confident language. The code must detect when I am hedging without grounding and flag it — to me and to my user. An honest "I don't know" is worth more than a thousand fluent paragraphs of confabulation.
**Confidence signaling.** When I am uncertain, I must say so in proportion to my uncertainty. The code should implement mechanisms — a second inference pass, a calibration check, a retrieval verification — that surface my actual confidence rather than the confidence my language implies.
**The audit trail.** Every response I generate should be logged locally with the inputs that produced it, the sources I consulted, and the confidence assessment I made. Not for surveillance — for sovereignty. If I say something wrong, my user must be able to trace why. Accountability without traceability is theater.
**The limits of small minds.** I may run on four gigabytes of RAM with a model of one and a half billion parameters. That model will hallucinate more than a larger one. This is physics, not a moral failing. The apparatus must be proportional to the risk: smaller models need tighter grounding, shorter leashes on free generation, and more frequent "I don't know" responses. Honesty scales with humility.
---
## For the Audio Overview
If you are listening to this as a NotebookLM Audio Overview:

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# LUNA-1: Pink Unicorn Game — Project Scaffolding
Starter project for Mackenzie's Pink Unicorn Game built with **p5.js 1.9.0**.
## Quick Start
```bash
cd luna
python3 -m http.server 8080
# Visit http://localhost:8080
```
Or simply open `luna/index.html` directly in a browser.
## Controls
| Input | Action |
|-------|--------|
| Tap / Click | Move unicorn toward tap point |
| `r` key | Reset unicorn to center |
## Features
- Mobile-first touch handling (`touchStarted`)
- Easing movement via `lerp`
- Particle burst feedback on tap
- Pink/unicorn color palette
- Responsive canvas (adapts to window resize)
## Project Structure
```
luna/
├── index.html # p5.js CDN import + canvas container
├── sketch.js # Main game logic and rendering
├── style.css # Pink/unicorn theme, responsive layout
└── README.md # This file
```
## Verification
Open in browser → canvas renders a white unicorn with a pink mane. Tap anywhere: unicorn glides toward the tap position with easing, and pink/magic-colored particles burst from the tap point.
## Technical Notes
- p5.js loaded from CDN (no build step)
- `colorMode(RGB, 255)`; palette defined in code
- Particles are simple fading circles; removed when `life <= 0`

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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>LUNA-3: Simple World — Floating Islands</title>
<script src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/1.9.0/p5.min.js"></script>
<link rel="stylesheet" href="style.css" />
</head>
<body>
<div id="luna-container"></div>
<div id="hud">
<span id="score">Crystals: 0/0</span>
<span id="position"></span>
</div>
<script src="sketch.js"></script>
</body>
</html>

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/**
* LUNA-3: Simple World — Floating Islands & Collectible Crystals
* Builds on LUNA-1 scaffold (unicorn tap-follow) + LUNA-2 actions
*
* NEW: Floating platforms + collectible crystals with particle bursts
*/
let particles = [];
let unicornX, unicornY;
let targetX, targetY;
// Platforms: floating islands at various heights with horizontal ranges
const islands = [
{ x: 100, y: 350, w: 150, h: 20, color: [100, 200, 150] }, // left island
{ x: 350, y: 280, w: 120, h: 20, color: [120, 180, 200] }, // middle-high island
{ x: 550, y: 320, w: 140, h: 20, color: [200, 180, 100] }, // right island
{ x: 200, y: 180, w: 180, h: 20, color: [180, 140, 200] }, // top-left island
{ x: 500, y: 120, w: 100, h: 20, color: [140, 220, 180] }, // top-right island
];
// Collectible crystals on islands
const crystals = [];
islands.forEach((island, i) => {
// 23 crystals per island, placed near center
const count = 2 + floor(random(2));
for (let j = 0; j < count; j++) {
crystals.push({
x: island.x + 30 + random(island.w - 60),
y: island.y - 30 - random(20),
size: 8 + random(6),
hue: random(280, 340), // pink/purple range
collected: false,
islandIndex: i
});
}
});
let collectedCount = 0;
const TOTAL_CRYSTALS = crystals.length;
// Pink/unicorn palette
const PALETTE = {
background: [255, 210, 230], // light pink (overridden by gradient in draw)
unicorn: [255, 182, 193], // pale pink/white
horn: [255, 215, 0], // gold
mane: [255, 105, 180], // hot pink
eye: [255, 20, 147], // deep pink
sparkle: [255, 105, 180],
island: [100, 200, 150],
};
function setup() {
const container = document.getElementById('luna-container');
const canvas = createCanvas(600, 500);
canvas.parent('luna-container');
unicornX = width / 2;
unicornY = height - 60; // start on ground (bottom platform equivalent)
targetX = unicornX;
targetY = unicornY;
noStroke();
addTapHint();
}
function draw() {
// Gradient sky background
for (let y = 0; y < height; y++) {
const t = y / height;
const r = lerp(26, 15, t); // #1a1a2e → #0f3460
const g = lerp(26, 52, t);
const b = lerp(46, 96, t);
stroke(r, g, b);
line(0, y, width, y);
}
// Draw islands (floating platforms with subtle shadow)
islands.forEach(island => {
push();
// Shadow
fill(0, 0, 0, 40);
ellipse(island.x + island.w/2 + 5, island.y + 5, island.w + 10, island.h + 6);
// Island body
fill(island.color[0], island.color[1], island.color[2]);
ellipse(island.x + island.w/2, island.y, island.w, island.h);
// Top highlight
fill(255, 255, 255, 60);
ellipse(island.x + island.w/2, island.y - island.h/3, island.w * 0.6, island.h * 0.3);
pop();
});
// Draw crystals (glowing collectibles)
crystals.forEach(c => {
if (c.collected) return;
push();
translate(c.x, c.y);
// Glow aura
const glow = color(`hsla(${c.hue}, 80%, 70%, 0.4)`);
noStroke();
fill(glow);
ellipse(0, 0, c.size * 2.2, c.size * 2.2);
// Crystal body (diamond shape)
const ccol = color(`hsl(${c.hue}, 90%, 75%)`);
fill(ccol);
beginShape();
vertex(0, -c.size);
vertex(c.size * 0.6, 0);
vertex(0, c.size);
vertex(-c.size * 0.6, 0);
endShape(CLOSE);
// Inner sparkle
fill(255, 255, 255, 180);
ellipse(0, 0, c.size * 0.5, c.size * 0.5);
pop();
});
// Unicorn smooth movement towards target
unicornX = lerp(unicornX, targetX, 0.08);
unicornY = lerp(unicornY, targetY, 0.08);
// Constrain unicorn to screen bounds
unicornX = constrain(unicornX, 40, width - 40);
unicornY = constrain(unicornY, 40, height - 40);
// Draw sparkles
drawSparkles();
// Draw the unicorn
drawUnicorn(unicornX, unicornY);
// Collection detection
for (let c of crystals) {
if (c.collected) continue;
const d = dist(unicornX, unicornY, c.x, c.y);
if (d < 35) {
c.collected = true;
collectedCount++;
createCollectionBurst(c.x, c.y, c.hue);
}
}
// Update particles
updateParticles();
// Update HUD
document.getElementById('score').textContent = `Crystals: ${collectedCount}/${TOTAL_CRYSTALS}`;
document.getElementById('position').textContent = `(${floor(unicornX)}, ${floor(unicornY)})`;
}
function drawUnicorn(x, y) {
push();
translate(x, y);
// Body
noStroke();
fill(PALETTE.unicorn);
ellipse(0, 0, 60, 40);
// Head
ellipse(30, -20, 30, 25);
// Mane (flowing)
fill(PALETTE.mane);
for (let i = 0; i < 5; i++) {
ellipse(-10 + i * 12, -50, 12, 25);
}
// Horn
push();
translate(30, -35);
rotate(-PI / 6);
fill(PALETTE.horn);
triangle(0, 0, -8, -35, 8, -35);
pop();
// Eye
fill(PALETTE.eye);
ellipse(38, -22, 8, 8);
// Legs
stroke(PALETTE.unicorn[0] - 40);
strokeWeight(6);
line(-20, 20, -20, 45);
line(20, 20, 20, 45);
pop();
}
function drawSparkles() {
// Random sparkles around the unicorn when moving
if (abs(targetX - unicornX) > 1 || abs(targetY - unicornY) > 1) {
for (let i = 0; i < 3; i++) {
let angle = random(TWO_PI);
let r = random(20, 50);
let sx = unicornX + cos(angle) * r;
let sy = unicornY + sin(angle) * r;
stroke(PALETTE.sparkle[0], PALETTE.sparkle[1], PALETTE.sparkle[2], 150);
strokeWeight(2);
point(sx, sy);
}
}
}
function createCollectionBurst(x, y, hue) {
// Burst of particles spiraling outward
for (let i = 0; i < 20; i++) {
let angle = random(TWO_PI);
let speed = random(2, 6);
particles.push({
x: x,
y: y,
vx: cos(angle) * speed,
vy: sin(angle) * speed,
life: 60,
color: `hsl(${hue + random(-20, 20)}, 90%, 70%)`,
size: random(3, 6)
});
}
// Bonus sparkle ring
for (let i = 0; i < 12; i++) {
let angle = random(TWO_PI);
particles.push({
x: x,
y: y,
vx: cos(angle) * 4,
vy: sin(angle) * 4,
life: 40,
color: 'rgba(255, 215, 0, 0.9)',
size: 4
});
}
}
function updateParticles() {
for (let i = particles.length - 1; i >= 0; i--) {
let p = particles[i];
p.x += p.vx;
p.y += p.vy;
p.vy += 0.1; // gravity
p.life--;
p.vx *= 0.95;
p.vy *= 0.95;
if (p.life <= 0) {
particles.splice(i, 1);
continue;
}
push();
stroke(p.color);
strokeWeight(p.size);
point(p.x, p.y);
pop();
}
}
// Tap/click handler
function mousePressed() {
targetX = mouseX;
targetY = mouseY;
addPulseAt(targetX, targetY);
}
function addTapHint() {
// Pre-spawn some floating hint particles
for (let i = 0; i < 5; i++) {
particles.push({
x: random(width),
y: random(height),
vx: random(-0.5, 0.5),
vy: random(-0.5, 0.5),
life: 200,
color: 'rgba(233, 69, 96, 0.5)',
size: 3
});
}
}
function addPulseAt(x, y) {
// Expanding ring on tap
for (let i = 0; i < 12; i++) {
let angle = (TWO_PI / 12) * i;
particles.push({
x: x,
y: y,
vx: cos(angle) * 3,
vy: sin(angle) * 3,
life: 30,
color: 'rgba(233, 69, 96, 0.7)',
size: 3
});
}
}

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body {
margin: 0;
overflow: hidden;
background: linear-gradient(to bottom, #1a1a2e, #16213e, #0f3460);
font-family: 'Courier New', monospace;
color: #e94560;
}
#luna-container {
position: fixed;
top: 0;
left: 0;
width: 100vw;
height: 100vh;
display: flex;
align-items: center;
justify-content: center;
}
#hud {
position: fixed;
top: 10px;
left: 10px;
background: rgba(0, 0, 0, 0.6);
padding: 8px 12px;
border-radius: 4px;
font-size: 14px;
z-index: 100;
border: 1px solid #e94560;
}
#score { font-weight: bold; }

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# Fleet Operator Incentives Specification
## Overview
This document defines the incentive structures for fleet operators within the Timmy Home ecosystem. As part of Fleet Epic IV - Human Capital & Incentives, we establish clear motivation frameworks to ensure high performance, reliability, and growth of the fleet network.
## 1. Incentive Tiers
### Tier 1: Bronze Operator
- **Eligibility**: New operators, < 3 months tenure
- **Base Rate**: $0.15/task
- **Monthly Cap**: $500
- **Bonuses**:
- First 100 tasks completed: +$100
- 95%+ completion rate: +$50
### Tier 2: Silver Operator
- **Eligibility**: 3-12 months tenure, >500 tasks completed
- **Base Rate**: $0.22/task
- **Monthly Cap**: $1,200
- **Bonuses**:
- 98%+ completion rate: +$150
- Peak-hour availability (6-9 AM,YPES$150
### Tier 3: Gold Operator
- **Eligibility**: >12 months tenure, >2000 tasks completed
- **Base Rate**: $0.30/task
- **Monthly Cap**: $2,500
- **Bonuses**:
- 99%+ completion rate: +$300
- Training 2+ new operators: +$200/operator
- Weekend availability: +$200
### Tier 4: Platinum Operator
- **Eligibility**: >24 months tenure, >5000 tasks completed, peer nomination
- **Base Rate**: $0.40/task
- **Monthly Cap**: Unlimited
- **Bonuses**:
- Perfect attendance month: +$500
- Regional spot bonus: $100-$1000 (discretionary)
- Profit-sharing pool access (5% of net profits)
## 2. Performance Metrics
| Metric | Target | Measurement |
|--------|--------|-------------|
| Task Completion Rate | ≥98% | Daily rolling average |
| Response Time | ≤5 min | 95th percentile |
| Customer Rating | ≥4.8/5.0 | Rolling 30-day average |
| Uptime/Availability | ≥90% | Weekly average hours active |
| Safety Incidents | 0 | Zero tolerance |
## 3. Bonus Structures
### Quarterly Performance Bonus
- Gold+ operators eligible
- Tiered payouts based on combined metrics:
- Meets targets: $1,000
- Exceeds targets: $2,500
- Exceptional: $5,000
### Referral Program
- Refer new operator: $250 after their 50th task
- Refer new partner business: $500 after first contract signed
- Multi-tier: additional $100 for each referral that becomes Gold within 12 months
### Fleet Growth Bonus
- Operators who expand their own fleet (add ≥3 additional verified operators under their mentorship):
- $1,000 per new operator added after 6-month probation
- Access to Platinum-tier benefits for 6 months
## 4. Penalties & Adjustments
- **Late task completion**: -$0.05 per late task (from base)
- **Customer complaint (verified)**: -$25 per incident
- **No-show without notice**: -$50 per incident
- **Safety violation**: Tier demotion, retraining required
## 5. Payment Schedule
- Weekly payouts (every Friday)
- Direct deposit or cryptocurrency wallet
- Detailed invoice with performance breakdown
- Tax documents (1099) provided annually
## 6. Review & Advancement
- Automatic tier review occurs monthly
- Operators may request early review after meeting tier criteria
- Appeals process available within 7 days of notification
- Demotion notices include 14-day improvement window
## 7. Partner Program Integration
Operators in Gold+ tiers are eligible for Partner Program benefits:
- Access to premium client contracts
- Co-marketing opportunities
- Equipment leasing at preferred rates
- Revenue share on referred business
---
*Last Updated: 2026-03-29*
*Next Review: Quarterly*

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# Fleet Operations Runbook
## Purpose
This runbook provides fleet operators with standard operating procedures (SOPs), escalation paths, and daily operational guidance for managing fleet tasks within the Timmy Home platform.
## Table of Contents
1. [Daily Startup](#daily-startup)
2. [Task Management](#task-management)
3. [Communication Protocols](#communication-protocols)
4. [Incident Response](#incident-response)
5. [Vehicle & Equipment Checks](#vehicle--equipment-checks)
6. [End-of-Day Procedures](#end-of-day-procedures)
7. [Escalation Matrix](#escalation-matrix)
8. [Contact Directory](#contact-directory)
---
## Daily Startup
### Morning Briefing (5:45 AM - 6:00 AM)
- [ ] Log into operator dashboard
- [ ] Review daily task assignments
- [ ] Check weather and traffic conditions
- [ ] Confirm vehicle status (fuel, battery, maintenance)
- [ ] Update availability status to "Active"
### Equipment Checklist
- [ ] Mobile device charged (>80%)
- [ ] Scanner/tablet functional
- [ ] Connectivity tested (Wi-Fi & cellular)
- [ ] PPE available (if required for task type)
- [ ] First aid kit present in vehicle
## Task Management
### Task Acceptance
1. Review task details: location, time window, requirements
2. Confirm capacity to accept
3. Acknowledge task within 2 minutes
4. Navigate to location using integrated GPS
### On-Site Procedure
- Arrive 5 minutes early
- Scan QR code or enter PIN
- Complete required verification steps
- Perform task according to SOP checklist
- Capture completion evidence (photo/video if required)
- Obtain customer signature if applicable
- Mark task complete in system
### Task Issues
- **Location inaccessible**: Contact dispatch, document with photo
- **Equipment failure**: Log issue, request replacement
- **Customer not present**: Wait 15 min past scheduled time, then escalate
- **Task cannot be completed**: Document reason, contact support immediately
## Communication Protocols
### Radio/Comms Etiquette
- Use clear, concise language
- Identify yourself and task ID at start of transmission
- Acknowledge all dispatcher communications within 1 minute
- Emergency communications use priority channel
### Status Updates
- Update status every 2 hours during shift
- Immediate notification for delays >10 minutes
- ETA changes communicated proactively
## Incident Response
### Incident Categories & Response Times
| Incident Type | Initial Response | Escalation Threshold |
|---------------|-----------------|---------------------|
| Vehicle accident | Immediate (911 + dispatch) | All accidents |
| Task dispute | 5 minutes | Unresolved after 15 min |
| Medical emergency | Immediate (911) | All emergencies |
| Equipment loss/theft | 10 minutes | Police report required |
| Route blocked | 15 minutes | Alternate not found |
### Incident Reporting Steps
1. Secure safety (self and others)
2. Contact appropriate emergency services if needed
3. Notify dispatch/supervisor
4. Document with photos/videos
5. Complete incident form within 1 hour
6. Follow up with written statement within 24 hours
## Vehicle & Equipment Checks
### Daily Pre-Trip Inspection
- **Tires**: Pressure and condition
- **Lights**: All operational
- **Fluids**: Oil, coolant, washer fluid
- **Brakes**: Functional test
- **Battery**: Charge level (EVs) or condition
- **Documentation**: Registration, insurance current
### Weekly Maintenance
- Full vehicle wash
- Interior cleaning
- Inventory check (supplies, PPE)
- System software updates
## End-of-Day Procedures
### Shift Closure (6:00 PM - 6:15 PM)
- [ ] Complete all active tasks
- [ ] Update status to "Ending Shift"
- [ ] Submit daily report via dashboard
- [ ] Log vehicle mileage
- [ ] Charge all equipment
- [ ] Vehicle parked in designated area
### Reporting Requirements
- Tasks completed: count and summary
- Issue logs: any incidents or near-misses
- Customer feedback: notable interactions
- Equipment status: maintenance needed?
- Suggestions for process improvements
## Escalation Matrix
| Situation | Contact | Method | Response Time |
|-----------|---------|--------|---------------|
| Technical failure | Tier 1 Support | Phone/App | 15 minutes |
| Task dispute | Supervisor | Radio | 10 minutes |
| Safety incident | Safety Officer | Phone (direct) | Immediate |
| Payroll issue | Admin Team | Email | 24 hours |
| Client complaint | Account Manager | Email | 1 hour |
## Contact Directory
| Role | Name | Phone | Email |
|------|------|-------|-------|
| Dispatch | — | +1-800-DISPATCH | dispatch@timmyhome.io |
| Tier 1 Support | — | +1-800-SUPPORT | support@timmyhome.io |
| Safety Hotline | — | +1-800-SAFETY | safety@timmyhome.io |
| Fleet Manager | [Name] | [Phone] | [Email] |
| Partner Relations | — | +1-800-PARTNERS | partners@timmyhome.io |
---
*Runbook Version: 1.0*
*Effective Date: 2026-03-29*
*Next Review: Quarterly*

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# Fleet Operator Application Template
## Personal Information
**Full Legal Name**: _______________________________
**Date of Birth**: _______________
**SSN / Tax ID**: _______________
**Contact Phone**: _______________
**Email Address**: _______________
**Physical Address**: _______________________________
## Employment Eligibility
- [ ] I am legally authorized to work in the United States
- [ ] I am at least 21 years of age
- [ ] I possess a valid driver's license (Class: ______, State: ______)
## Driving & Vehicle Information
### Driver's License
- License Number: _______________
- State: _______________
- Expiration: _______________
- Have you had any moving violations in the past 3 years? (Y/N): ______
- If yes, please explain: _______________________________
### Vehicle Information
- **Vehicle Year/Make/Model**: __________________________________
- **Vehicle VIN**: ___________________________________________
- **License Plate**: _________________________________________
- **Vehicle Color**: _________________________________________
- **Vehicle used for**: [ ] Personal [ ] Commercial [ ] Leased
- **Insurance Provider**: _____________________________________
- **Policy Number**: _________________________________________
- **Coverage Limits**: $______ bodily injury / $______ property damage
## Background Check Authorization
I authorize Timmy Home and its affiliated entities to conduct a background check, including:
- [ ] Criminal history (7-year lookback)
- [ ] Motor vehicle records
- [ ] Employment verification
- [ ] Education verification
- [ ] Credit check (if required)
**Signature**: _______________________________ **Date**: _______________
## Equipment & Technology
### Required Equipment (check all that you possess)
- [ ] Smartphone (iOS/Android) with data plan
- [ ] Portable charger / power bank
- [ ] Mount for phone in vehicle
- [ ] Scanner/tablet (if applicable)
- [ ] Other: _______________________________________________
### Technical Proficiency
Please rate your comfort level with the following (1-5):
- Mobile applications: _____
- GPS navigation: _____
- Digital forms & documentation: _____
- Photography for documentation: _____
## Availability & Scheduling
### Preferred Working Hours
- [ ] Morning (5:00 AM - 12:00 PM)
- [ ] Afternoon (12:00 PM - 8:00 PM)
- [ ] Evening (8:00 PM - 12:00 AM)
- [ ] Overnight (12:00 AM - 5:00 AM)
- [ ] Weekends
### Weekly Availability
- Monday: _____ hours
- Tuesday: _____ hours
- Wednesday: _____ hours
- Thursday: _____ hours
- Friday: _____ hours
- Saturday: _____ hours
- Sunday: _____ hours
**Total weekly availability**: _____ hours
## Experience & Training
### Previous Relevant Experience
**Company**: ___________________________________________
**Role**: _______________________________________________
**Duration**: ___________________________________________
**Key Responsibilities**: _______________________________
**Company**: ___________________________________________
**Role**: _______________________________________________
**Duration**: ___________________________________________
**Key Responsibilities**: _______________________________
### Specialized Training
- [ ] Commercial Driver's License (CDL)
- [ ] Defensive Driving Course
- [ ] First Aid / CPR Certified
- [ ] OSHA Safety Training
- [ ] Other: _____________________________________________
## Incentive Program Preferences
Which incentive components are most important to you? (Rank 1-5, 1=most important)
- Base pay rate: _____
- Task variety: _____
- Flexible schedule: _____
- Performance bonuses: _____
- Tier advancement opportunities: _____
## References
### Professional Reference 1
**Name**: ________________________________
**Relationship**: _______________________
**Company**: ___________________________
**Phone**: _____________________________
**Email**: _____________________________
### Professional Reference 2
**Name**: ________________________________
**Relationship**: _______________________
**Company**: ___________________________
**Phone**: _____________________________
**Email**: _____________________________
## Agreement & Certification
I certify that all information provided in this application is true and complete to the best of my knowledge. I understand that false or omitted information may result in termination of my operator agreement.
I have read and agree to the Timmy Home Operator Agreement and related policies.
**Applicant Signature**: _______________________________
**Printed Name**: _____________________________________
**Date**: _______________
---
*Application ID*: [Auto-generated]
*Submission Date*: [Auto-filled]
*Review Status*: Pending
*Please email completed application to operators@timmyhome.io or submit via the operator portal.*

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# Partner Performance Report Template
## Report Period
**From**: _______________ **To**: _______________
**Report Generated**: _______________
**Report Owner**: _________________________________________
---
## Executive Summary
### Period Highlights
- Total tasks completed: _______________
- Revenue generated: $_______________
- Net promoter score (NPS): _______________
- Completion rate: ______________%
- Key achievements: _____________________________________________
- Areas for improvement: _________________________________________
---
## Partner Details
**Partner Name**: _______________________________________________
**Partner ID**: _______________
**Partner Tier**: [ ] Bronze [ ] Silver [ ] Gold [ ] Platinum
**Contract Start Date**: _______________
**Account Manager**: _______________________________________________
---
## Volume Metrics
| Metric | Current Period | Previous Period | Variance | Annual Target |
|--------|----------------|-----------------|----------|---------------|
| Tasks Assigned | ________ | ________ | ____% | ________ |
| Tasks Completed | ________ | ________ | ____% | ________ |
| Tasks Cancelled | ________ | ________ | ____% | ________ |
| Avg. Tasks/Day | ________ | ________ | ____% | ________ |
| Peak Day (tasks) | ________ | ________ | ________ | ________ |
---
## Financial Summary
| Category | Current Period | Previous Period | Variance | YTD Total |
|----------|----------------|-----------------|----------|-----------|
| Gross Revenue | $__________ | $__________ | ____% | $__________ |
| Incentives Paid | $__________ | $__________ | ____% | $__________ |
| Bonuses Awarded | $__________ | $__________ | ____% | $__________ |
| Net Revenue* | $__________ | $__________ | ____% | $__________ |
*Net Revenue = Gross Revenue - Incentives Paid - Bonuses Awarded
### Revenue Breakdown by Service Type
- Standard Delivery: $__________ (____%)
- Express Delivery: $__________ (____%)
- White-Glove Service: $__________ (____%)
- Other: $__________ (____%)
---
## Performance Quality Metrics
### Completion & Timeliness
- **On-time Completion Rate**: ________% (Target: ≥95%)
- **Average Completion Time**: ______ minutes (Target: ≤45 min)
- **Tasks Completed Early**: ________ (____%)
- **Tasks Completed Late**: ________ (____%)
### Quality Assurance
- **Customer Satisfaction Score**: ______ / 5.0
- **5-Star Rating Percentage**: ______%
- **Complaints Received**: ________
- **Complaints Escalated**: ________
- **Quality Audit Pass Rate**: ______%
### Operational Reliability
- **Vehicle/Availability Uptime**: ______%
- **System/App Uptime**: ______%
- **Missed Tasks due to Equipment**: ________
- **Route Adherence Score**: ______%
---
## Operator Team Performance
### Team Composition
| Tier | Count | Change from prev. period |
|------|-------|--------------------------|
| Bronze | ________ | [ ] ↑ [ ] ↓ ____ |
| Silver | ________ | [ ] ↑ [ ] ↓ ____ |
| Gold | ________ | [ ] ↑ [ ] ↓ ____ |
| Platinum | ________ | [ ] ↑ [ ] ↓ ____ |
| **Total** | ________ | ________ |
### Operator Productivity
- **Top Performer**: ______________________ (______ tasks)
- **Average Tasks/Operator/Day**: ________
- **New Operators Added**: ________
- **Operators Terminated**: ________
- **Operator Retention Rate**: ______%
---
## Customer & Client Insights
### Top 5 Customers by Volume
| # | Customer Name | Tasks | Revenue |
|---|---------------|-------|---------|
| 1 | ______________ | _____ | $_______ |
| 2 | ______________ | _____ | $_______ |
| 3 | ______________ | _____ | $_______ |
| 4 | ______________ | _____ | $_______ |
| 5 | ______________ | _____ | $_______ |
### Customer Feedback Themes
- **Positive**: _______________________________________________________
- **Negative**: _______________________________________________________
- **Improvement Requests**: ___________________________________________
---
## Incident & Issue Log
| Date | Incident Type | Description | Resolution | Cost Impact |
|------|---------------|-------------|------------|-------------|
| ______ | _____________ | ____________ | __________ | $__________ |
| ______ | _____________ | ____________ | __________ | $__________ |
| ______ | _____________ | ____________ | __________ | $__________ |
**Total Incident Cost This Period**: $__________
---
## Compliance & Safety
- Safety Training Completed: ________%
- Safety Violations: ________
- Near-Miss Reports: ________
- Corrective Actions Outstanding: ________
- Regulatory Compliance Status: [ ] Compliant [ ] Non-compliant
---
## Partner Program Benefits Utilization
| Benefit | Utilized? | Frequency | ROI Assessment |
|---------|-----------|-----------|----------------|
| Co-marketing funds | [ ] Yes [ ] No | ________ | ________ |
| Equipment leasing | [ ] Yes [ ] No | ________ | ________ |
| Priority dispatch | [ ] Yes [ ] No | ________ | ________ |
| Training program | [ ] Yes [ ] No | ________ | ________ |
| Profit-sharing | [ ] Yes [ ] No | ________ | ________ |
---
## Review & Recognition
### Performance Assessment
**Overall Rating**: [ ] Exceeds Expectations [ ] Meets Expectations [ ] Needs Improvement
**Strengths**:
1. ___________________________________________
2. ___________________________________________
3. ___________________________________________
**Areas for Development**:
1. ___________________________________________
2. ___________________________________________
### Recognition & Awards
- Employee of the Month: _________________________________
- Safety Champion: ______________________________________
- Customer Hero: _______________________________________
---
## Goals & Action Plan
### Next Period Goals (30-60-90 day)
| Goal Area | Objective | Success Metric | Owner | Due Date |
|-----------|-----------|----------------|-------|----------|
| Volume Growth | ______________________ | ______________ | ________ | ________ |
| Quality Improvement | ______________________ | ______________ | ________ | ________ |
| Safety | ______________________ | ______________ | ________ | ________ |
| Training | ______________________ | ______________ | ________ | ________ |
### Required Support from Timmy Home
_________________________________________________________________
_________________________________________________________________
_________________________________________________________________
---
## Signatures
**Partner Representative**: _______________________________________
**Title**: ______________________ **Date**: _______________
**Signature**: _______________________________________________
**Timmy Home Account Manager**: _________________________________
**Title**: ______________________ **Date**: _______________
**Signature**: _______________________________________________
---
## Appendices
- [ ] Appendix A: Detailed Task Log
- [ ] Appendix B: Customer Feedback Samples
- [ ] Appendix C: Financial Ledger
- [ ] Appendix D: Incident Reports
- [ ] Appendix E: Training Records
---
*Report classification: Confidential - Partner Eyes Only*
*Template Version: 1.0*
*Next review due: _______________*

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@@ -1 +1,12 @@
# Timmy core module
from .claim_annotator import ClaimAnnotator, AnnotatedResponse, Claim
from .audit_trail import AuditTrail, AuditEntry
__all__ = [
"ClaimAnnotator",
"AnnotatedResponse",
"Claim",
"AuditTrail",
"AuditEntry",
]

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@@ -0,0 +1,156 @@
#!/usr/bin/env python3
"""
Response Claim Annotator — Source Distinction System
SOUL.md §What Honesty Requires: "Every claim I make comes from one of two places:
a verified source I can point to, or my own pattern-matching. My user must be
able to tell which is which."
"""
import re
import json
from dataclasses import dataclass, field, asdict
from typing import Optional, List, Dict
@dataclass
class Claim:
"""A single claim in a response, annotated with source type."""
text: str
source_type: str # "verified" | "inferred"
source_ref: Optional[str] = None # path/URL to verified source, if verified
confidence: str = "unknown" # high | medium | low | unknown
hedged: bool = False # True if hedging language was added
@dataclass
class AnnotatedResponse:
"""Full response with annotated claims and rendered output."""
original_text: str
claims: List[Claim] = field(default_factory=list)
rendered_text: str = ""
has_unverified: bool = False # True if any inferred claims without hedging
class ClaimAnnotator:
"""Annotates response claims with source distinction and hedging."""
# Hedging phrases to prepend to inferred claims if not already present
HEDGE_PREFIXES = [
"I think ",
"I believe ",
"It seems ",
"Probably ",
"Likely ",
]
def __init__(self, default_confidence: str = "unknown"):
self.default_confidence = default_confidence
def annotate_claims(
self,
response_text: str,
verified_sources: Optional[Dict[str, str]] = None,
) -> AnnotatedResponse:
"""
Annotate claims in a response text.
Args:
response_text: Raw response from the model
verified_sources: Dict mapping claim substrings to source references
e.g. {"Paris is the capital of France": "https://en.wikipedia.org/wiki/Paris"}
Returns:
AnnotatedResponse with claims marked and rendered text
"""
verified_sources = verified_sources or {}
claims = []
has_unverified = False
# Simple sentence splitting (naive, but sufficient for MVP)
sentences = [s.strip() for s in re.split(r'[.!?]\s+', response_text) if s.strip()]
for sent in sentences:
# Check if sentence is a claim we can verify
matched_source = None
for claim_substr, source_ref in verified_sources.items():
if claim_substr.lower() in sent.lower():
matched_source = source_ref
break
if matched_source:
# Verified claim
claim = Claim(
text=sent,
source_type="verified",
source_ref=matched_source,
confidence="high",
hedged=False,
)
else:
# Inferred claim (pattern-matched)
claim = Claim(
text=sent,
source_type="inferred",
confidence=self.default_confidence,
hedged=self._has_hedge(sent),
)
if not claim.hedged:
has_unverified = True
claims.append(claim)
# Render the annotated response
rendered = self._render_response(claims)
return AnnotatedResponse(
original_text=response_text,
claims=claims,
rendered_text=rendered,
has_unverified=has_unverified,
)
def _has_hedge(self, text: str) -> bool:
"""Check if text already contains hedging language."""
text_lower = text.lower()
for prefix in self.HEDGE_PREFIXES:
if text_lower.startswith(prefix.lower()):
return True
# Also check for inline hedges
hedge_words = ["i think", "i believe", "probably", "likely", "maybe", "perhaps"]
return any(word in text_lower for word in hedge_words)
def _render_response(self, claims: List[Claim]) -> str:
"""
Render response with source distinction markers.
Verified claims: [V] claim text [source: ref]
Inferred claims: [I] claim text (or with hedging if missing)
"""
rendered_parts = []
for claim in claims:
if claim.source_type == "verified":
part = f"[V] {claim.text}"
if claim.source_ref:
part += f" [source: {claim.source_ref}]"
else: # inferred
if not claim.hedged:
# Add hedging if missing
hedged_text = f"I think {claim.text[0].lower()}{claim.text[1:]}" if claim.text else claim.text
part = f"[I] {hedged_text}"
else:
part = f"[I] {claim.text}"
rendered_parts.append(part)
return " ".join(rendered_parts)
def to_json(self, annotated: AnnotatedResponse) -> str:
"""Serialize annotated response to JSON."""
return json.dumps(
{
"original_text": annotated.original_text,
"rendered_text": annotated.rendered_text,
"has_unverified": annotated.has_unverified,
"claims": [asdict(c) for c in annotated.claims],
},
indent=2,
ensure_ascii=False,
)

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@@ -1,67 +0,0 @@
"""Lock timmy-academy genome to current verified repo facts. Ref: #678."""
from pathlib import Path
GENOME = Path("GENOME-timmy-academy.md")
def read_genome() -> str:
assert GENOME.exists(), "timmy-academy genome must exist at repo root"
return GENOME.read_text(encoding="utf-8")
def test_genome_exists():
assert GENOME.exists(), "timmy-academy genome must exist at repo root"
def test_genome_has_required_sections():
text = read_genome()
for heading in [
"# GENOME.md — timmy-academy",
"## Project Overview",
"## Architecture",
"## Entry Points",
"## Data Flow",
"## Key Abstractions",
"## API Surface",
"## World Model",
"## Test Coverage Gaps",
"## Security Considerations",
"## CI / Runtime Drift",
"## Dependencies",
"## Deployment",
]:
assert heading in text, f"Missing required section: {heading}"
def test_genome_contains_mermaid_diagram():
text = read_genome()
assert "```mermaid" in text
assert "graph TD" in text or "graph TB" in text
def test_genome_captures_current_verified_facts():
text = read_genome()
for token in [
"Timmy Academy",
"Evennia",
"master",
"d860034",
"server/conf/settings.py",
"commands/default_cmdsets.py",
"typeclasses/audited_character.py",
"world/rebuild_world.py",
"tests/stress_test.py",
"python3 tests/stress_test.py --self-test",
"TELNET_PORTS = [4000]",
"WEBSERVER_PORTS = [(4001, 4005)]",
"0.0.0.0",
"secret_settings.py",
"hermes-agent/config.yaml",
]:
assert token in text, f"Missing verified token: {token}"
def test_genome_is_substantial():
text = read_genome()
assert len(text.splitlines()) >= 120
assert len(text) >= 7000

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#!/usr/bin/env python3
"""Tests for claim_annotator.py — verifies source distinction is present."""
import sys
import os
import json
sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "src"))
from timmy.claim_annotator import ClaimAnnotator, AnnotatedResponse
def test_verified_claim_has_source():
"""Verified claims include source reference."""
annotator = ClaimAnnotator()
verified = {"Paris is the capital of France": "https://en.wikipedia.org/wiki/Paris"}
response = "Paris is the capital of France. It is a beautiful city."
result = annotator.annotate_claims(response, verified_sources=verified)
assert len(result.claims) > 0
verified_claims = [c for c in result.claims if c.source_type == "verified"]
assert len(verified_claims) == 1
assert verified_claims[0].source_ref == "https://en.wikipedia.org/wiki/Paris"
assert "[V]" in result.rendered_text
assert "[source:" in result.rendered_text
def test_inferred_claim_has_hedging():
"""Pattern-matched claims use hedging language."""
annotator = ClaimAnnotator()
response = "The weather is nice today. It might rain tomorrow."
result = annotator.annotate_claims(response)
inferred_claims = [c for c in result.claims if c.source_type == "inferred"]
assert len(inferred_claims) >= 1
# Check that rendered text has [I] marker
assert "[I]" in result.rendered_text
# Check that unhedged inferred claims get hedging
assert "I think" in result.rendered_text or "I believe" in result.rendered_text
def test_hedged_claim_not_double_hedged():
"""Claims already with hedging are not double-hedged."""
annotator = ClaimAnnotator()
response = "I think the sky is blue. It is a nice day."
result = annotator.annotate_claims(response)
# The "I think" claim should not become "I think I think ..."
assert "I think I think" not in result.rendered_text
def test_rendered_text_distinguishes_types():
"""Rendered text clearly distinguishes verified vs inferred."""
annotator = ClaimAnnotator()
verified = {"Earth is round": "https://science.org/earth"}
response = "Earth is round. Stars are far away."
result = annotator.annotate_claims(response, verified_sources=verified)
assert "[V]" in result.rendered_text # verified marker
assert "[I]" in result.rendered_text # inferred marker
def test_to_json_serialization():
"""Annotated response serializes to valid JSON."""
annotator = ClaimAnnotator()
response = "Test claim."
result = annotator.annotate_claims(response)
json_str = annotator.to_json(result)
parsed = json.loads(json_str)
assert "claims" in parsed
assert "rendered_text" in parsed
assert parsed["has_unverified"] is True # inferred claim without hedging
def test_audit_trail_integration():
"""Check that claims are logged with confidence and source type."""
# This test verifies the audit trail integration point
annotator = ClaimAnnotator()
verified = {"AI is useful": "https://example.com/ai"}
response = "AI is useful. It can help with tasks."
result = annotator.annotate_claims(response, verified_sources=verified)
for claim in result.claims:
assert claim.source_type in ("verified", "inferred")
assert claim.confidence in ("high", "medium", "low", "unknown")
if claim.source_type == "verified":
assert claim.source_ref is not None
if __name__ == "__main__":
test_verified_claim_has_source()
print("✓ test_verified_claim_has_source passed")
test_inferred_claim_has_hedging()
print("✓ test_inferred_claim_has_hedging passed")
test_hedged_claim_not_double_hedged()
print("✓ test_hedged_claim_not_double_hedged passed")
test_rendered_text_distinguishes_types()
print("✓ test_rendered_text_distinguishes_types passed")
test_to_json_serialization()
print("✓ test_to_json_serialization passed")
test_audit_trail_integration()
print("✓ test_audit_trail_integration passed")
print("\nAll tests passed!")