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 FlyFission/nuclear-grade-context-engineering --skill questioning-attitudegit clone --depth 1 https://github.com/FlyFission/nuclear-grade-context-engineeringWrote 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/flyfission/nuclear-grade-context-engineering/questioning-attitude)<a href="https://agentmods.dev/skills/flyfission/nuclear-grade-context-engineering/questioning-attitude"><img src="https://agentmods.dev/badge/skills/flyfission/nuclear-grade-context-engineering/questioning-attitude/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/flyfission/nuclear-grade-context-engineering/questioning-attitude"><img src="https://agentmods.dev/badge/skills/flyfission/nuclear-grade-context-engineering/questioning-attitude.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00088 | $0.01903 |
| Opus 5.5 | $0.00035 | $0.00761 |
| Sonnet 5.5 | $0.00018 | $0.00381 |
| Haiku 4.5 | $0.00009 | $0.00190 |
Grade A, and why
questioning-attitude 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.
How it starts
The opening of the file, as written. The whole thing — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Questioning Attitude
Overview
This is the front door. Before an agent builds, merges, or releases, find the real question the work has to answer. Trust facts over confidence. Say out loud what you are not sure about. And stop the moment a doubt would change what you decide.
Decision contract
- Claim checked: the change is restated as one decision question evidence could settle, each assumption is checked, marked a gap, or assigned, and the one fact that would change the decision is named.
- Artifact observed: the request/diff/plan/dependency -> a questioning-attitude write-up (or
questioning-attitude.md) of assumptions, unknowns, shaky sources, and stop conditions. - Decision affected: warn -- the Quick/Standard mode choice routed into
rating-change-risk, and whether to proceed, escalate, or stop. - Failure class: unexamined-assumption (an unchecked assumption driving the build, or a claim with no evidence).
- Next action: raise the mode or escalate/stop when a load-bearing assumption is a gap; otherwise proceed with the gaps named.
When to Use
- A request is vague, high-stakes, or easy to talk yourself into.
- A diff, plan, dependency, prompt, model, tool, or release claim needs a skeptical second look.
- A reviewer asks "what are we assuming?" or "what would make this wrong?"
- An agent is about to get power over files, commands, the network, credentials, approvals, or releases.
- You see the warning signs of mistakes: too many files, stale memory, hidden links between parts, a messy workspace, grabbing the first answer, or pressure to be done.
When Not to Use
- The task is a tiny edit with obvious proof and no new trust boundary.
- An incident is live and you must contain it before you analyze it.
- Someone is asking for a formal guarantee, a certification, a safety analysis, or regulatory approval.
Inputs
- The request, issue, pull request, diff, or path to the change record.
- The files, dependencies, prompts, models, tools, data, and release items the change touches.
- What you already know, what you are assuming, the evidence you have, and the gaps.
- Any related past records, lessons from operation, or source notes.
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 · 123 lines · 88 tokens per session scan A 0f3b86d0e1ed
questioning-attitude is a skill published in the GitHub repository FlyFission/nuclear-grade-context-engineering (33 stars, last pushed 3d ago), licensed MIT. It adds 88 tokens to every session and 1,903 once invoked, about $0.0004 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 2026-08-30.
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