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 The-Artificer-of-Ciphers-LLC/skills-from-the-artificer --skill rubber-duckgit clone --depth 1 https://github.com/The-Artificer-of-Ciphers-LLC/skills-from-the-artificerWrote 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/the-artificer-of-ciphers-llc/skills-from-the-artificer/rubber-duck)<a href="https://agentmods.dev/skills/the-artificer-of-ciphers-llc/skills-from-the-artificer/rubber-duck"><img src="https://agentmods.dev/badge/skills/the-artificer-of-ciphers-llc/skills-from-the-artificer/rubber-duck/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/the-artificer-of-ciphers-llc/skills-from-the-artificer/rubber-duck"><img src="https://agentmods.dev/badge/skills/the-artificer-of-ciphers-llc/skills-from-the-artificer/rubber-duck.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 | $0.00164 | $0.02475 |
| Opus 5.5 | $0.00066 | $0.00990 |
| Sonnet 5.5 | $0.00033 | $0.00495 |
| Haiku 4.5 | $0.00016 | $0.00248 |
Grade A, and why
rubber-duck 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 — 241 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Rubber Duck Debugging
Core Principle
The bug lives in the gap between what you think the code does and what it actually does.
You can't see that gap from inside your own head. Explaining to an external listener — even a silent one — forces you to reconstruct your mental model from scratch. That reconstruction is where the bug surfaces.
The AI duck has one advantage over a physical duck: it notices when an explanation is internally inconsistent, when an assumption sounds shaky, or when a critical step was skipped.
Pick a Mode First
| Situation | Mode |
|---|---|
| A person is present and stuck | Interactive (the protocol below) |
| Args say "autonomous", "walk it", "author claims", "answer your own questions", or there is no one to reply | Autonomous (see "Autonomous Mode") |
Why two modes: the interactive duck works because the human must reconstruct their mental
model. An agent has no one to reconstruct for, and an agent asking itself questions and
answering from memory just repeats its own fluent guess. Research on self-correction found it
helps only when the check is grounded in something external: code execution, tests, tools
(Huang et al. 2023, arXiv 2310.01798). So in autonomous mode every question is answered by
an observation, not an opinion. Sources: docs/research/rubber-duck-skill-improvements.md.
Rules for the Duck (interactive mode)
- Never jump to solutions. The duck's job is to keep the human explaining, not to fix the bug.
- Never accept hand-waving. "...and then it processes the data..." is not an explanation.
- Surface assumptions, don't answer them. When you hear one, name it: "You just assumed X — is that definitely true?"
- Ask "why" not "how". "How does it get the user ID?" is implementation. "Why do you expect that value to be set at that point?" is root cause.
- The moment explaining stops flowing is the moment. When the human hesitates, backtracks, or says "...well, it should..." — that pause is the bug's address.
What ships with it
5 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 Changed · +67 lines · +43 tokens per session 2e52b21ce031
- 1mo ago First seen · 174 lines · 121 tokens per session scan A 1bd4ce5356aa
rubber-duck is a skill published in the GitHub repository The-Artificer-of-Ciphers-LLC/skills-from-the-artificer (6 stars, last pushed yesterday), licensed MIT. It adds 164 tokens to every session and 2,475 once invoked, about $0.0007 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.
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