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 using-nuclear-gradegit 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/using-nuclear-grade)<a href="https://agentmods.dev/skills/flyfission/nuclear-grade-context-engineering/using-nuclear-grade"><img src="https://agentmods.dev/badge/skills/flyfission/nuclear-grade-context-engineering/using-nuclear-grade/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/using-nuclear-grade"><img src="https://agentmods.dev/badge/skills/flyfission/nuclear-grade-context-engineering/using-nuclear-grade.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Memory Poisoning · line 12 Skill injects content designed to persist in agent memory or context across interactions. Persistent injection can alter agent behavior long after the initial interaction.Fix: Do not allow untrusted input to persist in agent memory or context. Validate all content before storing and implement memory isolation between sessions.
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 | $0.00079 | $0.01828 |
| Opus 5.5 | $0.00032 | $0.00731 |
| Sonnet 5.5 | $0.00016 | $0.00366 |
| Haiku 4.5 | $0.00008 | $0.00183 |
Grade A, and why
using-nuclear-grade 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 — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Using Nuclear-grade
Overview
This is the always-first router for Nuclear-grade work. Before you act, classify the change by consequence and route to the matching rigor — move fast while ideas are throwaway, slow down the moment the work becomes a promise. Start by asking the real question the change must answer, then state the mode it earns and the one fact that sets it. Build the smallest change record that does the job, prove the claims that matter, and say the release decision out loud.
The repo charter (.nuclear/charter.md) holds the lasting rules every change follows. Each change also gets a goal anchor — what that one change is for — so the work does not drift off course.
Decision contract
- Claim checked: this change is named the cheapest-fitting mode -- the administrative floor, Quick, or Standard-plus -- with the one fact that sets it stated before the first tool call, and any Standard-plus trap (auth, user-visible, data, dependency, model/prompt/agent power, CI, release) forces the stronger mode.
- Artifact observed: the request, diff, and any record under
.nuclear/changes/-> the declared mode, its one-fact reason, and the change-record path that routes the work into its skill cluster. - Decision affected: block -- the mode declared before the first tool call (the administrative floor, Quick, or Standard-plus) and the skill cluster it routes into.
- Failure class: unclassified-or-downgraded-start (work begun before a mode, or a Standard-plus trap waved off as Quick).
- Next action: state the mode before the first tool call; raise to Standard or human review when a trap or outside-trust claim appears.
When to Use
- A person or an AI agent will change code, tests, docs, prompts, tools, dependencies, or release evidence.
- A reviewer needs more than a commit message and a test result to judge the risk.
- Agent power, dependency trust, security, or release readiness is on the line.
- A team needs to follow the workflow: take the chosen path, or write down why it no longer fits.
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 · 109 lines · 79 tokens per session scan A 13bfe5937607
using-nuclear-grade is a skill published in the GitHub repository FlyFission/nuclear-grade-context-engineering (33 stars, last pushed 3d ago), licensed MIT. It adds 79 tokens to every session and 1,828 once invoked, about $0.0003 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 2026-09-06.
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