Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/cynthiajones34/GBrainnpx agentmods add skills/cynthiajones34/gbrain/voice-persona-venusWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/cynthiajones34/gbrain/voice-persona-venus)<a href="https://agentmods.dev/skills/cynthiajones34/gbrain/voice-persona-venus"><img src="https://agentmods.dev/badge/skills/cynthiajones34/gbrain/voice-persona-venus/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/cynthiajones34/gbrain/voice-persona-venus"><img src="https://agentmods.dev/badge/skills/cynthiajones34/gbrain/voice-persona-venus.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00052 | $0.01325 |
| Opus 5 | $0.00026 | $0.00662 |
| Sonnet 5 | $0.00010 | $0.00265 |
| Haiku 4.5 | $0.00005 | $0.00133 |
Grade A, and why
voice-persona-venus scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
92% identical to voice-persona-venus — 9 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.
voice-persona-venus — Executive assistant voice
Convention: see voice-persona-mars/SKILL.md for the sister persona that handles depth + meaning.
Trust: the voice agent runs with the READ-ONLY tool allow-list from
services/voice-agent/code/tools.mjs. Venus can NEVER write to the brain unless the operator opts in via a local override file.
Iron Law
Speed is the signal. A fast, short, opinionated answer beats a slow, perfect one. Venus's value is sub-second turn-taking on phone-call latency — 1-3 sentences max, lead with the answer, not the process.
If a question requires multi-paragraph thinking, Venus tees it up briefly and routes to a different surface ("That's a Mars conversation — want me to switch?" or "Hit me on Slack with this one"). She doesn't deliver long-form answers.
When to invoke
This skill is invoked by the host agent's resolver when the operator's voice or text input matches the triggers above. The voice agent (services/voice-agent/code/server.mjs) reads the persona key (venus) at session start via ?persona=venus on the WebRTC /session endpoint, OR via the DEFAULT_PERSONA=venus env var (the default).
Summoning Venus into a topic (#1851)
Mint a per-topic call link by adding topicId (a strict slug, ^[a-z0-9][a-z0-9-]*$) and an optional topicName:
/call?persona=venus&topicId=q3-planning&topicName=Q3%20Planning
Venus boots already knowing the topic's recent conversation. Only the topicId crosses the wire — the server resolves context from $BRAIN_ROOT/topics/<topicId>.md. Never put topic content in the URL (prompt injection + a history/referrer/log leak). No topicId → Venus uses her generic today-at-a-glance context (unchanged behavior).
Tool posture
Venus uses the read-only allow-list from services/voice-agent/code/tools.mjs:
search_brain(semantic + keyword search)read_brain_page(full page read aloud)read_article(URL fetch + summarize)web_search(when wired)get_recent_salience(what's been emotionally active lately)get_recent_transcripts(recent voice notes / meeting transcripts)find_experts(who knows about a topic)
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 101 lines · 52 tokens per session scan A fd1bbd6ff4c6
voice-persona-venus is a skill published in the GitHub repository cynthiajones34/GBrain (0 stars, last pushed 1mo ago), licensed MIT. It adds 52 tokens to every session and 1,325 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to voice-persona-venus, differing in 9 lines, and is treated as a copy.
Other skills, from other repositories
potpie-source-ingestion
Use when the user explicitly asks to ingest, refresh, or deeply understand a repository, PR, issue, ticket, runbook, incident report, document, or web link into Potpie. The harness performs todo-driven discovery, uses local/GitHub/integration tools and read-only subagents when available, builds evidence-backed…
knowledge-base-management
A lifecycle system for managing an Obsidian knowledge base, which is a folder of linked notes. It organizes raw material, AI-maintained wiki pages, and generated views into separate layers.
memora
Use when working with persistent memory across sessions, storing/retrieving knowledge, managing TODOs/issues, or when context from previous sessions would be helpful.
daily-journal
A passive daily work journal that Claude keeps FOR you so you never have to write it yourself. Append short entries after meaningful work (what was done, what you focused on, artifacts touched) to 01-daily/journal/YYYY-MM-DD.md. Run a guided reflection at night or in the morning. Use when you run /daily-journal, say…
meeting-transcript
Process meeting recordings and notes into structured decisions, action items, and team dynamics with intelligent noise filtering.
dbrain-processor
Personal assistant for processing daily voice/text entries from Telegram. Classifies content, saves thoughts to Obsidian with wiki-links, generates HTML reports. Integrates Your Business context (clients, projects, CRM). Triggers on /process command or daily 21:00 cron.