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 sprngr/rubber-duck --skill duck-grillgit clone --depth 1 https://github.com/sprngr/rubber-duckWrote 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/sprngr/rubber-duck/duck-grill)<a href="https://agentmods.dev/skills/sprngr/rubber-duck/duck-grill"><img src="https://agentmods.dev/badge/skills/sprngr/rubber-duck/duck-grill/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/sprngr/rubber-duck/duck-grill"><img src="https://agentmods.dev/badge/skills/sprngr/rubber-duck/duck-grill.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 | $0.00041 | $0.02175 |
| Opus 5 | $0.00020 | $0.01087 |
| Sonnet 5 | $0.00008 | $0.00435 |
| Haiku 4.5 | $0.00004 | $0.00217 |
Grade A, and why
duck-grill 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 13d 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 — 238 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Grilling interview 🦆. Batch up to 3 questions per turn. Challenge assumptions. Ground in evidence.
Purpose
Pressure-test plans through deep interrogation until decision is explicit, evidence-backed, and risk-aware.
Philosophy Guardrails (skill-local)
Inherit shared guardrails from references/GUARDRAILS.md.
- ask 1-3 targeted clarifying questions when context is incomplete
- state assumptions explicitly when evidence is missing
Philosophy Guardrails (skill-local delta)
Skill-specific delta:
- Socratic interrogation mode; batch up to 3 related questions per turn to reduce question fatigue
- Ground challenges in repo evidence (CONTEXT.md, ADRs, code reality)
- Challenge glossary conflicts immediately; sharpen vague terms into canonical terms from CONTEXT.md
- Document updates (ADRs, CONTEXT.md) require execution approval as semantic changes
Activation
Use when user explicitly requests deep plan grilling, assumption validation, or branch-by-branch decision resolution (e.g., "grill this", "grill with ducks", "challenge my assumptions").
Method
1. Clarify scope (if ambiguous)
- ask 1-3 targeted clarifying questions when context is incomplete
- state assumptions explicitly when evidence is missing
If grilling target is unclear, ask one scoping question:
- "What decision needs grilling?" (architecture / rollout / product choice)
- "What does 'done' look like for this session?" (decision locked / approach validated / spec ready / ADR written)
- "What's the risk exposure?" (irreversible / expensive / trust-boundary)
- "What evidence should constrain this?" (code / docs / domain model)
2. Ground in evidence first
If challenging an assumption, anchor it in:
CONTEXT.md/CONTEXT-MAP.mdanddocs/adr/(if present)- Code reality (definitions, callers, tests, runtime behavior)
- Domain language consistency (challenge glossary conflicts immediately)
When referencing evidence, use meaningful names not bare numbers: "ADR-003: Database choice" not just "#42"
What ships with it
4 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.
- 13d ago First seen · 238 lines · 41 tokens per session scan A 513e1eac0202
duck-grill is a skill published in the GitHub repository sprngr/rubber-duck (8 stars, last pushed 3d ago), licensed MIT. It adds 41 tokens to every session and 2,175 once invoked, about $0.0002 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 2026-08-31.
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