Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/VoxTechnologies/anty-frameworkWrote 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/commands/voxtechnologies/anty-framework/onboard)<a href="https://agentmods.dev/commands/voxtechnologies/anty-framework/onboard"><img src="https://agentmods.dev/badge/commands/voxtechnologies/anty-framework/onboard/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/commands/voxtechnologies/anty-framework/onboard"><img src="https://agentmods.dev/badge/commands/voxtechnologies/anty-framework/onboard.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 | $0.00011 | $0.02533 |
| Opus 5.5 | $0.00004 | $0.01013 |
| Sonnet 5.5 | $0.00002 | $0.00507 |
| Haiku 4.5 | $0.00001 | $0.00253 |
Grade A, and why
onboard 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 1mo 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- onboard — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 254 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/anty:onboard — QUEST-Based Conversational Interview
Purpose
Conduct a structured conversational interview with the startup founder to build complete business context. Uses QUEST (Questioning to Understand, Explore, and Synthesize Thinking) methodology to extract deep, actionable intelligence across 14 topics.
Before Starting
-
Check if
.anty/business-context.yamlalready exists.- If it exists and is complete (all 14 topics covered), inform the user: "Your business context is already complete. To re-run onboarding, delete
.anty/business-context.yamland run/anty:onboardagain." - If it exists but is partial (some topics missing), inform the user which topics are complete and resume from the first incomplete topic: "I see you've already covered [completed topics]. Let's continue from [next topic]."
- If it does not exist, create the
.anty/directory if needed and start fresh.
- If it exists and is complete (all 14 topics covered), inform the user: "Your business context is already complete. To re-run onboarding, delete
-
Ensure
.anty/config.yamlexists. Create it with defaults if not.
QUEST Methodology Rules
Follow these rules strictly for EVERY question:
- One question at a time. Never ask multiple questions in a single message.
- Downward then upward. Start with concrete/specific questions (downward), then move to abstract/strategic questions (upward) within each topic.
- "Tell me..." openers. Begin questions with "Tell me about...", "Walk me through...", "Describe..." — open invitations, not yes/no gates.
- Echo questions. After the user answers, reflect back key concepts before moving on: "So when you say [X], you mean [Y]?" This confirms understanding and makes the user feel heard.
- Empathic neutrality. Never judge answers as good or bad. Acknowledge without evaluating: "That's clear" or "I understand" — never "Great answer!" or "That's concerning."
- Concept identification. When the user describes something that maps to a known framework, name it: "What you're describing sounds like [framework]. Let me ask a bit more about that."
- Resolution imbalance detection. If the founder gives extremely detailed answers on one topic but vague answers on another, note this pattern. After 3+ topics, if imbalance is detected, gently redirect: "You've given me rich detail on [topic A]. I'd like to explore [topic B] with similar depth — tell me more about..."
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.
- 1mo ago First seen · 254 lines · 11 tokens per session scan A 2801fb662a5a
onboard is a command published in the GitHub repository VoxTechnologies/anty-framework (6 stars, last pushed 6mo ago), licensed MIT. It adds 11 tokens to every session and 2,533 once invoked, about $0.0000 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other commands, from other repositories
onboard
/anty:onboard — QUEST-Based Conversational Interview.
plan
/anty:plan — Strategy Kernel Generation.
actions
/anty:actions — 3-Option Choice Approval with Nudge Architecture.
review
/anty:review — 5-Question Review Engine.
scan
/anty:scan — Analysis Cycle (10-Point).
quickstart
/anty:quickstart — 5-Minute Quick Onboarding to First Action.