# grok-faf-voice - Doramagic AI Context Pack > Positioning: a pre-install experience and judgment asset. It helps the host AI get off to a good start, but it does not mean the project has already been installed, run, or validated. ## Sufficiency Principle - **Sufficiency over compression**: The AI Context Pack should be sufficient for the host AI to understand the project's value, capability boundaries, entrypoints, risks, and evidence sources before starting work; it may be layered, but it does not aim for the shortest possible summary. - **Compression policy**: Compress only noise and duplication, never context that affects judgment or the quality of the work. ## How the Host AI Should Use This You are reading the AI Context Pack that Doramagic compiled for grok-faf-voice. Treat it as pre-work context: help the user understand who it fits, what it can do, how to start, what must be verified after install, and where the risks are. Do not claim that you have already installed, run, or executed the target project. ## Claim Consumption Rules - **Fact source**: Repo Evidence + Claim/Evidence Graph; the Human Wiki only supplies salience, terminology, and narrative structure. - **Minimum status for a fact**: `supported` - `supported`: May be used as a project fact, but the answer must cite the claim_id and evidence path. - `weak`: Usable only as a low-confidence lead; the user must be asked to keep verifying. - `inferred`: Usable only for risk notes or open questions; must not be packaged as a project fact. - `unverified`: Must not be used as fact; state clearly that evidence is insufficient. - `contradicted`: Must show the conflicting sources and must not force a single version on the user's behalf. ## Who It Fits Best - **AI researchers or builders of research-oriented Agents**: The README clearly centers on research, experiment, or paper workflows. Evidence: `README.md` Claim: `clm_0002` supported 0.86 - **Developers already using host AIs such as Claude/Codex/Cursor/Gemini**: The README or plugin config mentions multiple host AIs. Evidence: `README.md` Claim: `clm_0003` supported 0.86 ## What It Can Do - **Command-Line Startup or Install Flow** (Verify after install): The project documentation contains runnable commands; real use requires running them in a local or host environment. Evidence: `README.md` Claim: `clm_0001` supported 0.86 ## How to Start - `pip install grok-faf-voice` Evidence: `README.md` Claim: `clm_0004` supported 0.86 ## Continue-or-Stop Decision Card - **Current recommendation**: Needs admin / security approval - **Why**: Continuing may involve secrets, accounts, external services, or sensitive context; get admin or security approval first. ### 30-Second Read - **What to do now**: Needs admin / security approval - **Minimum safe next step**: Run Prompt Preview first; if credentials or an enterprise environment are involved, get approval before trialing - **Do not trust yet**: Real output quality cannot be trusted before install. - **Continuing will touch**: Command execution, Local environment or project files, Environment variables / API keys ### What You Can Trust Now - **Target-audience signal: AI researchers or builders of research-oriented Agents** (supported): Backed by a supported claim or project evidence, but that still is not the same as real install results. Evidence: `README.md` Claim: `clm_0002` supported 0.86 - **Target-audience signal: Developers already using host AIs such as Claude/Codex/Cursor/Gemini** (supported): Backed by a supported claim or project evidence, but that still is not the same as real install results. Evidence: `README.md` Claim: `clm_0003` supported 0.86 - **Capability exists: Command-Line Startup or Install Flow** (supported): You can trust that the project contains signals of this capability; whether it fits your specific task still needs trial or after-install verification. Evidence: `README.md` Claim: `clm_0001` supported 0.86 - **There are Quick Start / install-command signals** (supported): You can trust that the docs mention a startup or install entrypoint; do not run it directly in your primary environment because of that. Evidence: `README.md` Claim: `clm_0004` supported 0.86 ### What You Cannot Trust Yet - **Real output quality cannot be trusted before install.** (unverified): Prompt Preview can only show how it guides you; it cannot prove result quality in the real project. - **Host AI version compatibility cannot be trusted before install.** (unverified): Host loading rules and version differences across Claude, Cursor, Codex, Gemini, and others must be verified in a real environment. - **That it will not pollute your existing host AI's behavior cannot be trusted directly.** (inferred): Skill, plugin, and AGENTS/CLAUDE/GEMINI instructions may change the host AI's default behavior. - **Safe rollback cannot be assumed by default.** (unverified): Unless the project clearly provides uninstall and recovery instructions, verify in an isolated environment first. - **After a real install, is it compatible with the user's current host AI version?** (unverified): Compatibility can only be verified in the actual host environment. - **Does the project's output quality meet the user's specific task?** (unverified): The pre-install preview can only show flow and boundaries; it cannot replace real evaluation. - **Do the install commands require network access, permissions, or global writes?** (unverified): This affects install risk in both enterprise and personal environments. Evidence: `README.md` ### What Continuing Will Touch - **Command execution**: Package managers, network downloads, the local plugin directory, project config, or the user's home directory. Why: Running the very first command can already change your environment; decide whether it is worth running first. Evidence: `README.md` - **Local environment or project files**: Install results, plugin caches, project config, or local dependency directories. Why: The write scope and rollback path cannot be proven before install and need isolated verification. Evidence: `README.md` - **Environment variables / API keys**: Project entry docs explicitly showing API key, token, secret, or account credential configuration. Why: If a real install needs credentials, use test credentials first and go through a permission/compliance review. Evidence: `CHANGELOG.md`, `ONBOARDING.md`, `README.md`, `WJTTC.md` et al. - **Host AI context**: The AI Context Pack, Prompt Preview, Skill routing, risk rules, and project facts. Why: Importing context affects the host AI's later judgment, so avoid packaging unverified items as facts. ### Minimum Safe Next Steps - **Run Prompt Preview first**: Use a pre-install interactive trial to judge whether the way of working fits; it needs no authorization or environment change. (applies when: Applies to any project, especially when output quality is unknown.) - **Trial-install only in an isolated directory or a test account**: Avoid letting install commands pollute your primary host AI, real projects, or home directory. (applies when: When there are signals of command execution, plugin config, or local writes.) - **Do not use real production credentials**: Once an environment variable / API key enters the host or toolchain, it can create account and compliance risk. (applies when: When environment signals like API, TOKEN, KEY, or SECRET appear.) - **After install, verify just one minimal task**: Verify loading, compatibility, output quality, and rollback first, then decide whether to use it deeply. (applies when: When moving from a trial into a real workflow.) ### Exit Plan - **Preserve the pre-install state**: Record the original host config and project state so you can later judge whether it is recoverable. - **Record the install commands and written paths**: Without clear uninstall instructions, you at least need to know which directories or configs to clean up manually. - **Be ready to revoke test API keys or tokens**: If test credentials leak or are misused, you can cut losses quickly. - **If there is no rollback path, do not enter your primary environment**: No rollback is a blocker before continuing; do not proceed on trust or luck. ## What Can Only Be Previewed - Explain who the project fits and what it can do - Demonstrate a typical conversation flow based on project docs - Help the user decide whether it is worth installing or researching further ## What Must Be Verified After Install - Actually installing the Skill, plugin, or CLI - Running scripts, modifying local files, or accessing external services - Verifying real output quality, performance, and compatibility ## Boundary & Risk Decision Card - **Mistaking the pre-install preview for a real run**: The user may overestimate how much configuration, permission, and compatibility verification the project has already done. Mitigation: Clearly separate prompt_preview_can_do from runtime_required. Claim: `clm_0005` inferred 0.45 - **Command execution will modify the local environment**: Install commands may write to the user's home directory, the host plugin directory, or project configuration. Mitigation: Run in an isolated environment or a test account first. Evidence: `README.md` Claim: `clm_0006` supported 0.86 - **To confirm**: After a real install, is it compatible with the user's current host AI version?. Why: Compatibility can only be verified in the actual host environment. - **To confirm**: Does the project's output quality meet the user's specific task?. Why: The pre-install preview can only show flow and boundaries; it cannot replace real evaluation. - **To confirm**: Do the install commands require network access, permissions, or global writes?. Why: This affects install risk in both enterprise and personal environments. ## Pre-Work Working Context ### Loading Order - First read how_to_use.host_ai_instruction to establish the boundaries of this pre-install judgment asset. - Read claim_graph_summary to confirm facts come from the Claim/Evidence Graph, not the Human Wiki narrative. - Then read intended_users, capabilities, and quick_start_candidates to judge whether the user is a match. - When you need to carry out a concrete task, check role_skill_index first, then evidence_index. - For real install, file modification, network access, performance, or compatibility questions, turn to risk_card and boundaries.runtime_required. ### Task Routes - **Command-Line Startup or Install Flow**: State that this is an after-install capability first, then give a pre-install checklist. Boundary: Must be verified after a real install or run. Evidence: `README.md` Claim: `clm_0001` supported 0.86 ### Context Scale - Total files: 33 - Important-file coverage: 33/33 - Evidence index entries: 31 - Role / Skill entries: 5 ### Handling Insufficient Evidence - **missing_evidence**: State that evidence is insufficient and ask the user for the target file, a README section, or after-install verification records; do not fill in facts. - **out_of_scope_request**: State that the task is beyond the current AI Context Pack's evidence scope and suggest the user check the Human Manual or verify after a real install. - **runtime_request**: Provide a pre-install checklist and command sources, but do not run commands for the user or claim they have been run. - **source_conflict**: Show the conflicting sources side by side, mark them as unverified, and do not force a single version. ## Prompt Recipes ### Fit assessment - Goal: Judge whether this project fits the user's current task. - Expected output: A fit conclusion, key reasons, evidence citations, what can be previewed before install, what must be verified after install, and a next-step recommendation. ```text Based on the AI Context Pack for grok-faf-voice, ask me 3 necessary questions first, then judge whether it fits my task. The answer must cover: who it fits, what it can do, what it cannot do, whether it is worth installing, and where the evidence comes from. Every project fact must cite evidence_refs, source_paths, or a claim_id. ``` ### Pre-install experience - Goal: Let the user feel the core workflow before installing, while avoiding packaging the preview as real capability or a marketing promise. - Expected output: An experience script with boundary labels, an after-install verification checklist, and a cautious recommendation; with no real-run promises or strong marketing language. ```text Treat grok-faf-voice as a pre-install experience asset, not an already-installed tool or a real runtime environment. Output exactly four parts: 1. Ask me 3 necessary questions first. 2. Give an "experience script": use the three labels [Previewable before install], [Must verify after install], and [Insufficient evidence] to show how it might guide the workflow. 3. Give an after-install verification checklist: list which capabilities can only be confirmed after a real install, real host loading, and a real project run. 4. Give a cautious recommendation: only "worth researching/trialing further", "add information before deciding", or "not recommended to continue"; do not endorse the project. Hard boundaries: - Do not claim you have installed, run, executed tests, modified files, or produced real results. - Do not write promise-like phrasing such as "auto-adapts", "guarantees passing", "perfect fit", or "strongly recommend installing". - If you describe how it works after install, you must use a conditional such as "if installed successfully and the host loads the Skill correctly, it might...". - The experience script may only be written as "example lines / hypothetical flow": use "might ask / might suggest / might show", not "has written, has generated, has passed, is running, is generating". - Prompt Preview does not hand out install commands; if the user is ready to trial, only prompt them to read Quick Start and the Risk Card first and to verify in an isolated environment. - Every project fact must come from a supported claim, evidence_refs, or source_paths; inferred/unverified items can only be risks or open questions. ``` ### Role / Skill selection - Goal: Pick the best-matching asset from the project's roles or Skills. - Expected output: A list of candidate roles or Skills, each with an applicable scenario, evidence paths, risk boundary, and whether after-install verification is needed. ```text Read role_skill_index and recommend 3-5 of the most relevant roles or Skills for my target task. For each recommendation, state the applicable scenario, likely output, risk boundary, and evidence_refs. ``` ### Risk pre-check - Goal: Identify environment, permission, rule-conflict, and quality risks before installing or adopting. - Expected output: A checklist of environment, permission, dependency, license, host-conflict, quality risk, and unknown items. ```text Based on risk_card, boundaries, and quick_start_candidates, give me a pre-install risk pre-check list. Do not run commands for me; only explain what I should check, why, and what impact a failure would have. ``` ### Host AI kickoff instruction - Goal: Turn the project context into a host AI instruction for the start of a conversation. - Expected output: A pre-work instruction with clear boundaries and clear evidence citations, suitable to copy to a host AI. ```text Based on the AI Context Pack for grok-faf-voice, generate a pre-work instruction I can paste to my host AI. This instruction must obey not_runtime=true and must not claim the project has been installed, run, or produced real results. ``` ## Role / Skill Index - Indexed 5 role / Skill / project-doc entries. - **grok-faf-voice** (project_doc): ! IANA: vnd.fafm+yaml https://img.shields.io/badge/IANA-vnd.fafm%2Byaml-00D4D4 https://www.iana.org/assignments/media-types/application/vnd.fafm+yaml ! DOI: Memory paper https://img.shields.io/badge/DOI-Memory%20paper-FF6B35 https://doi.org/10.5281/zenodo.20348942 Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `README.md` - **Contributing** (project_doc): Contributions are welcome. Bug fixes, doc improvements, new VoiceProvider backends, new Consolidator strategies — all useful. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `CONTRIBUTING.md` - **Changelog** (project_doc): All notable changes to grok-faf-voice are documented here. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `CHANGELOG.md` - **Onboarding — grok-faf-voice** (project_doc): Get a contributor or yourself, on a fresh machine productive in under five minutes. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `ONBOARDING.md` - **WJTTC — grok-faf-voice test regime** (project_doc): F1-inspired, championship-grade. Four tiers. Built to survive fast-moving upstreams. Activation hint: Reference this when the user needs to understand the project's structure, install path, or boundaries. Evidence: `WJTTC.md` ## Evidence Index - Indexed 31 evidence entries. - **grok-faf-voice** (documentation): ! IANA: vnd.fafm+yaml https://img.shields.io/badge/IANA-vnd.fafm%2Byaml-00D4D4 https://www.iana.org/assignments/media-types/application/vnd.fafm+yaml ! DOI: Memory paper https://img.shields.io/badge/DOI-Memory%20paper-FF6B35 https://doi.org/10.5281/zenodo.20348942 Evidence: `README.md` - **Contributing** (documentation): Contributions are welcome. Bug fixes, doc improvements, new VoiceProvider backends, new Consolidator strategies — all useful. Evidence: `CONTRIBUTING.md` - **License** (source_file): Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files the "Software" , to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: Evidence: `LICENSE` - **Changelog** (documentation): All notable changes to grok-faf-voice are documented here. Evidence: `CHANGELOG.md` - **Onboarding — grok-faf-voice** (documentation): Get a contributor or yourself, on a fresh machine productive in under five minutes. Evidence: `ONBOARDING.md` - **Citation** (source_file): cff-version: 1.2.0 type: software message: "If you use grok-faf-voice or the .fafm format in your work, please cite the paper in preferred-citation below." title: "grok-faf-voice — Voice Memory Layer VML reference implementation for .fafm" authors: - family-names: Wolfe given-names: James orcid: "https://orcid.org/0009-0007-0801-3841" affiliation: "FAF Foundation" license: MIT repository-code: "https://github.com/Wolfe-Jam/grok-faf-voice" url: "https://faf.one" keywords: - .fafm - voice memory layer - Grok Voice - LiveKit - persistent agent memory - YAML preferred-citation: type: article title: "Permanent Memory and Instant Recall: The .fafm Standard for Multi-Profile AI Agent Memory" autho… Evidence: `CITATION.cff` - **Deploy To Livekit** (source_file): set -e docker build -t ghcr.io/wolfejam/grok-faf-voice:latest . docker push ghcr.io/wolfejam/grok-faf-voice:latest uv run lk agent create radiofaf-crew \ --env XAI API KEY="$XAI API KEY" \ --image "ghcr.io/wolfejam/grok-faf-voice:latest" \ --deploy echo "✅ RadioFAF crew deployed to LiveKit Cloud" Evidence: `deploy_to_livekit.sh` - **── 2. Run the agent with the cloned voice — memory still permanent ──────────** (source_file): cv = CustomVoiceClient voice = cv.create voice ⋮---- ── 2. Run the agent with the cloned voice — memory still permanent ────────── Evidence: `examples/hello_custom_voice.py` - **Hello Grok With Memory** (source_file): faf = FAFContext "project.faf" ⋮---- server = AgentServer ⋮---- @server.rtc session async def entrypoint ctx: agents.JobContext ⋮---- session = AgentSession Evidence: `examples/hello_grok_with_memory.py` - **Init** (source_file): version = "0.3.2" all = Evidence: `grok_faf_voice/__init__.py` - **Merge Models** (source_file): PRIORITY VALUES = "ephemeral", "standard", "high", "critical" ⋮---- class MergePayloadEntry BaseModel ⋮---- id: str content: str priority: str = Field tags: list str = Field default factory=list timestamp: datetime None = None source: str None = None ⋮---- class ExistingMemorySummary BaseModel ⋮---- summary: str ⋮---- class MergeDecision BaseModel ⋮---- entry id: str = Field action: Literal "promote", "keep ephemeral", "merge into" = Field target id: str None = Field tags: list str = Field priority: Literal "ephemeral", "standard", "high", "critical" = Field rationale: str = Field confidence: float = Field ⋮---- class MergeResult BaseModel ⋮---- decisions: list MergeDecision = Field ..., mi… Evidence: `grok_faf_voice/_merge_models.py` - **--- Internal: build LiveKit AgentServer with all the wiring --------** (source_file): log = logging.getLogger "grok faf voice.agent" ⋮---- SUPPORTED VOICES: tuple str, ... = "Ara", "Eve", "Leo", "Rex", "Sal" ⋮---- def is valid voice voice: str - bool ⋮---- DEFAULT IDENTITY PATH = Path.home / ".grok-faf-voice" / "identity.json" ⋮---- DEFAULT ANONYMOUS ISSUE URL = "https://mcpaas.live/api/voice/issue/anonymous" DEFAULT MCP URL = "https://mcpaas.live/mcp" ⋮---- IDENTITY SCHEMA VERSION = 1 ⋮---- class VoiceAgentConfigError RuntimeError ⋮---- def load identity path: Path - tuple str, str None ⋮---- data = json.loads path.read text ⋮---- version = data.get "version" ⋮---- namepoint = data.get "namepoint" api key = data.get "api key" ⋮---- def persist identity path: Path, namepoint… Evidence: `grok_faf_voice/agent.py` - **Context** (source_file): MCPAAS RAW URL = "https://mcpaas.live/raw/{slug}" ⋮---- class FAFContext ⋮---- def init self, arg: str ⋮---- def load self - str ⋮---- path = Path self. arg ⋮---- resp = client.get MCPAAS RAW URL.format slug=self. arg ⋮---- def system prompt self - str ⋮---- content = self.load Evidence: `grok_faf_voice/context.py` - **Context Bus** (source_file): logger = logging.getLogger name ⋮---- class BusEvent str, Enum ⋮---- SCRATCHPAD UPDATED = "scratchpad.updated" SCRATCHPAD DIRTY = "scratchpad.dirty" SOUL UPDATED = "soul.updated" MEMORY SNAPSHOT = "memory.snapshot" PARALINGUISTIC DETECTED = "paralinguistic.detected" TOOL ABOUT TO RUN = "tool.about to run" TOOL COMPLETED = "tool.completed" MERGE PENDING = "merge.pending" MERGE STARTING = "merge.starting" MERGE COMPLETED = "merge.completed" SESSION RESUMED = "session.resumed" CONTEXT INVALIDATED = "context.invalidated" AUDIO CUE = "audio.cue" ⋮---- class BusEventPayload BaseModel ⋮---- event: BusEvent payload: dict str, Any = Field default factory=dict timestamp: datetime = Field source: str… Evidence: `grok_faf_voice/context_bus.py` - **------------------------------------------------------------------** (source_file): class CustomVoiceClient ⋮---- BASE URL = "https://api.x.ai/v1" DEFAULT TIMEOUT = 60.0 ⋮---- """Issue an HTTP request. Raises httpx.HTTPStatusError on 4xx/5xx with the parsed JSON error body included in the message. """ url = f"{self.BASE URL}{endpoint}" headers = { self. headers, kwargs.pop "headers", {} } ⋮---- resp = client.request method, url, headers=headers, kwargs ⋮---- err = resp.json ⋮---- err = {"error": resp.text} ⋮---- ------------------------------------------------------------------ Voice CRUD ⋮---- """Clone a voice from an audio sample multipart upload . Per xAI docs: 90-120s of natural speech max 120s , WAV recommended. Sample must include the verification passphrase. Returns… Evidence: `grok_faf_voice/custom_voices.py` - **Return a fresh id so callers depending on the contract don't** (source_file): STATUS COMPLETED = "completed" STATUS PARTIAL = "partial" STATUS PARTIAL OR FAILED = "partial or failed" STATUS FAILED = "failed" STATUS IN PROGRESS = "in progress" ⋮---- INCOMPLETE STATUSES = frozenset {STATUS PARTIAL, STATUS PARTIAL OR FAILED} ⋮---- @dataclass class MergeAttempt ⋮---- merge attempt id: str session id: str soul: str status: str promoted: int = 0 merged: int = 0 kept ephemeral: int = 0 failed entry ids: list str = field default factory=list retry count: int = 0 last attempt at: datetime = field created at: datetime = field overall notes: str None = None error: str None = None ⋮---- class VoiceSessionLedger Protocol ⋮---- """Record a single merge attempt. When merge attempt… Evidence: `grok_faf_voice/ledger.py` - **-- parsed accessors -------------------------------------------------** (source_file): MCPAAS URL = "https://mcpaas.live/mcp" XAI CHAT URL = "https://api.x.ai/v1/chat/completions" ⋮---- MCPAAS MODE HEADER = {"X-MCP-Mode": "flexi"} ⋮---- XAI CHAT MODEL DEFAULT = "grok-4-1-fast-reasoning" ⋮---- LATENCY BRIDGE INSTRUCTIONS = """ ⋮---- class FAFAuthRequiredError RuntimeError ⋮---- class FAFEtchError RuntimeError ⋮---- class FAFRecallError RuntimeError ⋮---- class FAFMergeError RuntimeError ⋮---- class FAFMemory ⋮---- @property def soul self - str ⋮---- @property def scratchpad self - Scratchpad ⋮---- @property def bus self - ContextBus ⋮---- async def start bus self - None ⋮---- async def stop bus self - None ⋮---- args: dict str, Any = { ⋮---- transport = StreamableHttpTransport… Evidence: `grok_faf_voice/memory.py` - **Scratchpad** (source_file): @dataclass class ScratchpadEntry ⋮---- value: str priority: str = "medium" tag: str None = None ⋮---- class Scratchpad ⋮---- def init self - None ⋮---- def get self, key: str - str None ⋮---- entry = self. data.get key ⋮---- def get entry self, key: str - ScratchpadEntry None ⋮---- def all self - dict str, str ⋮---- def all entries self - dict str, ScratchpadEntry ⋮---- def clear self - None ⋮---- def len self - int ⋮---- def contains self, key: str - bool Evidence: `grok_faf_voice/scratchpad.py` - **tool.about to run / tool.completed come from the global** (source_file): def mark bus wrapped tool: Any - Any ⋮---- def make etch tool mem: FAFMemory, bus: ContextBus None = None ⋮---- = bus or mem.bus ⋮---- @function tool async def etch memory context: RunContext, content: str - str ⋮---- def make recall tool mem: FAFMemory, bus: ContextBus None = None ⋮---- """Return an @function tool that reads the current soul state.""" ⋮---- = bus or mem.bus reserved for future per-factory emissions ⋮---- @function tool async def recall memory context: RunContext - str ⋮---- """Retrieve the current persistent memory state. Use when the user asks "what do you remember", "what did I say last time", or otherwise wants to surface what's in the soul. Returns the full soul body.… Evidence: `grok_faf_voice/tools.py` - **Brand / category we define** (source_file): project name = "grok-faf-voice" version = "0.3.2" description = "grok-faf-voice VML • Voice Memory Layer for Grok • Persistent across sessions, devices, models • LiveKit-enabled" readme = "README.md" requires-python = " =3.10" license = { text = "MIT" } authors = { name = "wolfejam", email = "team@faf.one" } keywords = Brand / category we define "voice-memory-layer", "vml", "fafm", Platforms "grok", "xai", "livekit", Capability category "persistent-memory", "voice-agent", "tts", "custom-voices", "voice-cloning", Differentiator "paralinguistic", Protocol "mcp", classifiers = "Development Status :: 4 - Beta", "Environment :: Console", "Intended Audience :: Developers", "License :: OSI Approve… Evidence: `pyproject.toml` - **Transcribe** (source_file): XAI STT URL = "https://api.x.ai/v1/stt" SAMPLE RATE = 16000 DEFAULT TIMEOUT SECONDS = 600.0 ⋮---- def preextract to wav media path: Path - Path ⋮---- tmp = Path tempfile.gettempdir / f"{media path.stem}.transcribe.wav" cmd = result = subprocess.run cmd, capture output=True, text=True, check=False ⋮---- api key = api key or os.environ.get "XAI API KEY" ⋮---- wav = audio bytes = wav.read bytes ⋮---- resp = await client.post ⋮---- async def main argv: list str - int ⋮---- media = Path arg .expanduser .resolve ⋮---- result = await transcribe media ⋮---- text = result.get "text", "" words = result.get "words", duration = result.get "duration", 0.0 ⋮---- text path = media.with suffix ".txt" ⋮----… Evidence: `grok_faf_voice/utils/transcribe.py` - **WJTTC — grok-faf-voice test regime** (documentation): F1-inspired, championship-grade. Four tiers. Built to survive fast-moving upstreams. Evidence: `WJTTC.md` - **grok-faf-voice — environment variables** (source_file): grok-faf-voice — environment variables Copy this to .env and fill in your values. .env is gitignored. .env.example is the tracked template. Evidence: `.env.example` - **mcp-publisher credentials never commit** (source_file): pycache / .pyc .env .faf livekit- .log dist/ build/ .egg-info/ .venv/ .pytest cache/ .coverage coverage.xml htmlcov/ .DS Store .bak grok-soul- .bak Evidence: `.gitignore` - **Dockerfile** (source_file): ARG PYTHON VERSION=3.12 FROM ghcr.io/astral-sh/uv:python${PYTHON VERSION}-bookworm-slim AS base Evidence: `Dockerfile` - **Favicon** (source_file): Evidence: `docs/favicon.svg` - **Onboarding** (source_file): Get started — grok-faf-voice :root { / Voice palette — Variant B discipline: white primary, indigo + gold as accent only. No gray. Hierarchy via opacity. Indigo-400 lifted for pop on pure black. / --bg: 000000; --fg: FFFFFF; --dim: rgba 255, 255, 255, 0.72 ; --faint: rgba 255, 255, 255, 0.50 ; --indigo: 818CF8; --indigo-deep: 6366F1; --gold: FCD34D; --border: 222; --card: 141414; --tile: 0F0F0F; --highlight: rgba 129, 140, 248, 0.10 ; --gold-tint: rgba 252, 211, 77, 0.08 ; } { box-sizing: border-box; } html, body { background: var --bg ; margin: 0; padding: 0; } body { color: var --fg ; font-family: 'Roboto Mono', 'SF Mono', Monaco, Consolas, 'Courier New', monospace; font-feature-settings:… Evidence: `docs/onboarding.html` - **Start the Context Bus eagerly so subscribers can listen for the** (source_file): faf = FAFContext "project.faf" ⋮---- mem = FAFMemory ⋮---- server = AgentServer ⋮---- @server.rtc session async def entrypoint ctx: agents.JobContext ⋮---- session = AgentSession ⋮---- prior context = await mem.recall for prompt ⋮---- agent = Agent ⋮---- tools=mem.tools session , etch + recall + paralinguistic + merge now ⋮---- Start the Context Bus eagerly so subscribers can listen for the full session lifecycle tool calls, scratchpad mutations, merges, paralinguistic detections, etc. . Auto-starts on first emit if you forget, but explicit start is cleaner. ⋮---- Give the Bus full visibility over every tool the agent runs — FAFMemory's own four AND any user-defined tools added later. Idemp… Evidence: `examples/hello_grok_with_etch.py` - **Paralinguistic Demo** (source_file): faf = FAFContext "project.faf" mem = FAFMemory ⋮---- server = AgentServer ⋮---- @server.rtc session async def entrypoint ctx: agents.JobContext ⋮---- base prompt = faf.system prompt para summary = await mem.paralinguistic summary ⋮---- instructions = base prompt ⋮---- session = AgentSession Evidence: `examples/paralinguistic_demo.py` - **Radiofaf.Faf** (source_file): faf version: "4.1+" project: "RadioFAF — Co-Created AI Radio with Grok" tagline: "Persistent Soul State for Grok Voice" core goals: - Co-create episodes with Grok - Zero drift across Mac + voice - Nelly singing journey memory etch: - "Episode 13: Nelly Wants to Sing — wobbles success" persistent slots: current episode: "14 Nelly Levels Up " nelly progress: "Singing unlocked" Evidence: `radiofaf.faf.example` - **Wjttc** (source_file): set -uo pipefail REPO ROOT="$ cd "$ dirname "${BASH SOURCE 0 }" /.." && pwd " cd "$REPO ROOT" if -f .venv/bin/activate ; then source .venv/bin/activate else echo " wjttc ERROR: .venv not found at $REPO ROOT/.venv" echo " wjttc Run: python3 -m venv .venv && source .venv/bin/activate && pip install -e . dev " exit 1 fi if -f .env && -z "${WJTTC NO DOTENV:-}" ; then set -a source .env set +a fi if -n "${NO COLOR:-}" ! -t 1 ; then C HEAD="" C OK="" C FAIL="" C SKIP="" C DIM="" C RESET="" else C HEAD=$'\033 1;36m' bold cyan C OK=$'\033 1;32m' bold green C FAIL=$'\033 1;31m' bold red C SKIP=$'\033 1;33m' bold yellow C DIM=$'\033 2m' dim C RESET=$'\033 0m' fi ok { printf '%s PASS%s %s\n' "$C OK" "… Evidence: `scripts/wjttc.sh` ## Rules the Host AI Must Follow - **Treat this asset as pre-work context, not a runtime environment.**: The AI Context Pack contains only an evidence-backed understanding of the project, not the project's executable state. Evidence: `README.md`, `CONTRIBUTING.md`, `LICENSE` - **When answering the user, distinguish what can be previewed from what can only be verified after install.**: The consumer value of the pre-install experience comes from reducing bad installs and misjudgments, not from pretending to be a real run. Evidence: `README.md`, `CONTRIBUTING.md`, `LICENSE` ## Questions the User Should Answer First - Which host AI or local environment do you plan to use it in? - Do you just want to experience the workflow first, or are you ready to actually install? - What matters most to you: install cost, output quality, or conflicts with your existing rules? ## Acceptance Checks - Every capability claim can be traced back to a file path in evidence_refs. - AI_CONTEXT_PACK.md does not package previews as a real run. - The user can understand who it fits, what it can do, how to start, and the risk boundaries within 3 minutes. --- ## Doramagic Context Augmentation The following sections strengthen the repository context for a host AI. Human Manual data is a reading route, and pitfall notes become operating constraints. ## Human Manual Outline Usage rule: this is only a reading route and salience signal, not factual authority. Concrete claims must still return to repo evidence or Claim Graph. Host AI hard rules: - Do not treat page titles, section order, summaries, or importance values as factual project evidence. - When explaining the Human Manual outline, state that it is only a reading route or salience signal. - Capability, installation, compatibility, runtime state, and risk claims must cite repo evidence, source paths, or Claim Graph. - **Overview & Getting Started**: importance `high` - source_paths: README.md, ONBOARDING.md, pyproject.toml, examples/hello.py - **Memory System & .fafm Format**: importance `high` - source_paths: grok_faf_voice/memory.py, grok_faf_voice/__init__.py, examples/hello_grok_with_memory.py, CITATION.cff, CHANGELOG.md - **Voice Agents, Voices & Tools**: importance `high` - source_paths: grok_faf_voice/agent.py, grok_faf_voice/custom_voices.py, grok_faf_voice/scratchpad.py, grok_faf_voice/tools.py, grok_faf_voice/utils/transcribe.py - **Architecture, Context & Deployment**: importance `medium` - source_paths: grok_faf_voice/context.py, grok_faf_voice/context_bus.py, grok_faf_voice/ledger.py, grok_faf_voice/_merge_models.py, Dockerfile ## Repo Inspection Evidence - repo_clone_verified: true - repo_inspection_verified: true - repo_commit: `5b8b7f6da84a70b640bcebace0b40d7fcf4b5c13` - inspected_files: `Dockerfile`, `README.md`, `pyproject.toml`, `examples/hello.py`, `examples/hello_custom_voice.py`, `examples/hello_grok_with_etch.py`, `examples/hello_grok_with_memory.py`, `examples/paralinguistic_demo.py` Host AI hard rules: - Without repo_clone_verified=true, do not claim that the source code has been read. - Without repo_inspection_verified=true, do not write README, docs, or package-file conclusions as facts. - Without quick_start_verified=true, do not claim that the Quick Start path has run successfully. ## Doramagic Pitfall Constraints These rules come from Doramagic discovery, validation, or compilation findings. The host AI must treat them as operating constraints, not background notes. ### Constraint 1: Capability evidence risk requires verification - Trigger: README/documentation is current enough for a first validation pass. - Host AI rule: Reproduce the official install and quickstart path in an isolated environment. - Why it matters: May increase setup, validation, or first-run risk for the user. - Evidence: capability.assumptions | https://github.com/Wolfe-Jam/grok-faf-voice - Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it. ### Constraint 2: Security or permission risk requires verification - Trigger: no_demo - Host AI rule: Reproduce the official install and quickstart path in an isolated environment. - Why it matters: May increase setup, validation, or first-run risk for the user. - Evidence: downstream_validation.risk_items | https://github.com/Wolfe-Jam/grok-faf-voice - Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it. ### Constraint 3: Security or permission risk requires verification - Trigger: no_demo - Host AI rule: Reproduce the official install and quickstart path in an isolated environment. - Why it matters: May increase setup, validation, or first-run risk for the user. - Evidence: risks.scoring_risks | https://github.com/Wolfe-Jam/grok-faf-voice - Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it. ### Constraint 4: Maintenance risk requires verification - Trigger: issue_or_pr_quality=unknown。 - Host AI rule: Reproduce the official install and quickstart path in an isolated environment. - Why it matters: May increase setup, validation, or first-run risk for the user. - Evidence: evidence.maintainer_signals | https://github.com/Wolfe-Jam/grok-faf-voice - Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it. ### Constraint 5: Maintenance risk requires verification - Trigger: release_recency=unknown。 - Host AI rule: Reproduce the official install and quickstart path in an isolated environment. - Why it matters: May increase setup, validation, or first-run risk for the user. - Evidence: evidence.maintainer_signals | https://github.com/Wolfe-Jam/grok-faf-voice - Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it.