StarNet is a local-first desktop harness for creating AI agents and arranging them in a pixel-art space station whose layout represents their capabilities, permissions, and workflow. It lets people run real model calls and tools through multiple bounded agents, using their own provider keys or accounts and optionally messaging the station through chat services. The catalogue entries are skills that extend or support work performed by StarNet agents.
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.
npx skills add androoAGI/starnet --skill decision-questionnairegit clone --depth 1 https://github.com/androoAGI/starnetWrote 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/androoagi/starnet/decision-questionnaire)<a href="https://agentmods.dev/skills/androoagi/starnet/decision-questionnaire"><img src="https://agentmods.dev/badge/skills/androoagi/starnet/decision-questionnaire/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/androoagi/starnet/decision-questionnaire"><img src="https://agentmods.dev/badge/skills/androoagi/starnet/decision-questionnaire.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 | $0.00036 | $0.00957 |
| Opus 5.5 | $0.00014 | $0.00383 |
| Sonnet 5.5 | $0.00007 | $0.00191 |
| Haiku 4.5 | $0.00004 | $0.00096 |
Grade A, and why
decision-questionnaire 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Decision Questionnaire
Turn something the Commander cannot answer alone into a questionnaire: a Markdown document they hand to one person to fill in async, or fill out together in a meeting. The recipient holds knowledge the Commander lacks; the questionnaire pulls it out of them.
When to use
- A decision is blocked on facts or judgment held by someone else (a domain expert, a stakeholder, a vendor contact, operations).
- The Commander says "I need to ask X about this", or keeps deferring a decision until someone else weighs in.
- Preparing for a meeting where specific answers must come back.
Do NOT use it when the answer is discoverable from the environment (the codebase, documents, the web). Find it yourself first with fs.search, fs.read, web_search, and web_fetch.
Core principle: interview the send, not the subject
The Commander cannot answer the subject-matter questions (that is the point), but they can ALWAYS answer questions about the send. Interview them only about that, in two short exchanges:
- Who is it going to? Role, expertise, relationship to the Commander. This fixes the questionnaire's tone and how much context it must carry. Done when you know who the recipient is and what they know that the Commander does not.
- What do you need back? The specific decisions or facts the Commander cannot resolve alone. Done when you have a concrete list of what the Commander must walk away able to do or decide.
Then write the questionnaire: draft questions aimed at the gap between what the recipient knows and what the Commander needs, following the structure below. Save it with fs.write as decision-questionnaire-<slug>.md (slug from the topic) and give the Commander the full path. Done when the file exists and every item from step 2 is covered by a question.
Document structure
Frame it as a discovery questionnaire: the Commander lacks context, the recipient holds it. Order questions most-important-first (async means you may only get one pass). Group them under ## headings by theme once there are more than a handful.
What ships with it
2 files 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.
- 12d ago First seen · 90 lines · 36 tokens per session scan A 2d9c76df5870
decision-questionnaire is a skill published in the GitHub repository androoAGI/starnet (1,468 stars, last pushed 3d ago), licensed MIT. It adds 36 tokens to every session and 957 once invoked, about $0.0001 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 2026-10-04.
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