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 verifying-final-artifactsgit 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/verifying-final-artifacts)<a href="https://agentmods.dev/skills/flyfission/nuclear-grade-context-engineering/verifying-final-artifacts"><img src="https://agentmods.dev/badge/skills/flyfission/nuclear-grade-context-engineering/verifying-final-artifacts/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/verifying-final-artifacts"><img src="https://agentmods.dev/badge/skills/flyfission/nuclear-grade-context-engineering/verifying-final-artifacts.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 | $0.00098 | $0.02012 |
| Opus 5.5 | $0.00039 | $0.00805 |
| Sonnet 5.5 | $0.00020 | $0.00402 |
| Haiku 4.5 | $0.00010 | $0.00201 |
Grade A, and why
verifying-final-artifacts 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 — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Verifying Final Artifacts
Overview
Reviewing the code, config, or markup that produces a figure, chart, PDF, or interface -- and calling it done without opening the actual output -- is validating the recipe, not the meal. The generator is not the artifact. A plotting script can be correct line by line and still emit a figure with overlapping labels, a substituted font, a clipped axis, or a legend off the page. A LaTeX source can compile "cleanly" into a PDF whose table breaks across a page boundary. A UI component can look right in source and render broken. A deploy config can be valid and the live endpoint still return the wrong body.
The delivered artifact is the only thing the consumer ever sees, and the only place these defects appear. None of them is reliably predictable from a source read. This skill holds that line: it regenerates the artifact fresh, observes the real output the way a consumer would, compares it to the spec, and loops -- fix the source, regenerate, look again -- until the observed artifact is right or a stop condition is hit. It ends in one honest verdict, not a verdict inferred from "the diff looks correct."
Decision contract
- Claim checked: the final delivered artifact, freshly regenerated this pass and directly observed, meets its spec or acceptance criteria -- the source that generates it was not accepted as a stand-in for the output.
- Artifact observed: the regenerated output itself (the image opened, every PDF page rasterized and read, the UI screenshotted, the endpoint response fetched) compared against the spec or reference -> a findings list, each defect tied to a location in the output and the source line responsible, plus one verdict.
- Decision affected: block -- whether the artifact ships as-is, or the source must change and the artifact be regenerated and re-observed before it can ship.
- Failure class: source-proxy error (approving the generator in place of the thing it generates) or stale-artifact error (reviewing a cached or old export instead of a freshly regenerated one).
- Next action: NOT VERIFIED routes the fix back to the source and then back into the same regenerate-and-observe loop; it does not exit on "the diff looks right."
What ships with it
1 file 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.
- 1mo ago First seen · 114 lines · 98 tokens per session scan A cf64f93d0e04
verifying-final-artifacts is a skill published in the GitHub repository FlyFission/nuclear-grade-context-engineering (33 stars, last pushed 3d ago), licensed MIT. It adds 98 tokens to every session and 2,012 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 2026-09-06.
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