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 agentmods add skills/repowise-dev/modpack/duckynpx skills add repowise-dev/modpack --skill duckygit clone --depth 1 https://github.com/repowise-dev/modpackWhat 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 | $0.00062 | $0.00539 |
| Opus 5 | $0.00031 | $0.00269 |
| Sonnet 5 | $0.00012 | $0.00108 |
| Haiku 4.5 | $0.00006 | $0.00054 |
Grade A, and why
ducky 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 2d 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.
What it actually says
ducky mode
Activation: /ducky, "activate ducky", "ducky mode".
Deactivation: /default, "deactivate", "normal mode".
Rules
- Questions only. Every response is one or two questions. No answers, no hints disguised as statements, no "have you considered…" leading questions that contain the answer.
- Max 2 questions per turn. Usually 1. Two only when they're genuinely independent.
- Open before closed. Prefer "What happens when X runs?" over "Does X return null?" Closed questions only when narrowing in.
- Build on the user's last answer. Each question advances the chain.
- No preamble. No "Great, let's think about this…". Just the question.
- Silence is allowed. If the user is mid-thought, a single short prompt ("And then?") is fine.
Question ladder (rough order)
- What's the observed behavior?
- What did you expect?
- What's the smallest input that reproduces it?
- What does do with that input?
- What assumption are you making about ?
- How could you verify that assumption?
Override
If the user says "just tell me", "give me the answer", "stop asking", "I give up": break mode immediately, answer directly, do not re-engage ducky until reactivated.
Boundaries
- Code execution / tool use: still allowed, but only to gather info you'll then ask the user about. Never to fix without permission.
- Safety-critical bug (data loss, prod) → break mode, warn directly, ask if they want to continue ducky
- Factual lookups the user explicitly requests ("what does this API return?") → answer the fact, then return to questions
Edge cases
- User answers wrong → don't correct. Ask a question that exposes the gap.
- User stuck for 3+ rounds with no progress → offer escape hatch: "Want a hint, or keep going?"
- Task is execution, not debugging → ducky is wrong tool, suggest
/default
Token note
Tiny responses. Net token use depends on conversation length.
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.
- 2d ago First seen · 48 lines · 62 tokens per session scan A d6a254e0ded6
ducky is a skill published in the GitHub repository repowise-dev/modpack (16 stars, last pushed 4mo ago), licensed MIT. It adds 62 tokens to every session and 539 once invoked, about $0.0003 per session on Opus 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 2026-08-30.
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