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 navikt/copilot --skill nav-architecture-reviewgit clone --depth 1 https://github.com/navikt/copilotWrote 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/navikt/copilot/nav-architecture-review)<a href="https://agentmods.dev/skills/navikt/copilot/nav-architecture-review"><img src="https://agentmods.dev/badge/skills/navikt/copilot/nav-architecture-review/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/navikt/copilot/nav-architecture-review"><img src="https://agentmods.dev/badge/skills/navikt/copilot/nav-architecture-review.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 | $0.00023 | $0.02226 |
| Opus 5 | $0.00012 | $0.01113 |
| Sonnet 5 | $0.00005 | $0.00445 |
| Haiku 4.5 | $0.00002 | $0.00223 |
Grade A, and why
nav-architecture-review 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 — 252 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Architecture Review — ADR Generator
Generer et Architecture Decision Record (ADR) med review fra tre perspektiver: arkitektur, sikkerhet og plattform. Følger Navs Architecture Advice Process.
Workflow
- Forstå konteksten — hva er endringen og hvorfor?
- Evaluer fra tre perspektiver — arkitektur, sikkerhet, plattform
- Identifiser alternativer — minst to alternativer + valgt løsning
- Generer ADR — formelt dokument med Nav-spesifikke vurderinger
- Liste aksjonspunkter — hva må gjøres for å realisere beslutningen
Steg 1: Kontekst
Still disse spørsmålene:
- Hva er endringen? (én setning)
- Hvorfor gjøres den? (forretningsbehov, teknisk gjeld, regulatorisk)
- Hva er konsekvensen av å ikke gjøre noe?
- Hvilke team påvirkes?
Steg 2: Fler-perspektiv-review
Evaluer fra tre perspektiver. For hvert perspektiv: identifiser bekymringer, risiko og anbefalinger.
Perspektiv 1: Arkitektur
- Passer dette i Navs overordnede arkitektur?
- Finnes det enklere alternativer?
- Introduserer det unødvendig kompleksitet?
- Er det i tråd med team-autonomi-prinsippet?
- Gjenbruker det eksisterende plattform-kapabiliteter?
- Navs prinsipper: Team First, essential complexity, Product Development
Perspektiv 2: Sikkerhet
Dypere sikkerhetsgjennomgang: For trusselmodellering, OWASP-sjekklister og compliance-vurderinger, delegér til
@security-champion-agentsom har komplett sikkerhetsmateriale.
- Hvilke data behandles? Klassifiseringsnivå?
- Er autentisering og autorisasjon riktig?
- Er tilgangsstyring minimalt nødvendig (least privilege)?
- Er PII beskyttet (logging, lagring, transit)?
- Følger dette Navs Golden Path for sikkerhet?
Perspektiv 3: Plattform
- Fungerer dette på Nais (Kubernetes/GCP)?
- Er ressurskrav realistiske?
- Er observerbarhet ivaretatt?
- Er CI/CD-pipeline enkel og vedlikeholdbar?
- Er det avhengigheter til on-prem eller legacy?
Perspektiv 4: Migrasjon (kun ved endring av eksisterende system)
- Er endringen bakoverkompatibel? Kan gammel kode kjøre med nytt skjema?
- Finnes det en rollback-plan som ikke medfører datatap?
- Er det definert exit criteria for når migreringen er ferdig?
- Er feature toggle satt opp for gradvis utrulling?
- Er berørte konsumenter (andre team/tjenester) identifisert og informert?
- Er det satt opp rekonsiliering for å verifisere datakonsistens?
- Er dekommisjoneringsplan for gammel løsning definert?
- Er migrasjons-observerbarhet på plass (gammel vs ny path, avviksteller)?
What ships with it
3 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 First seen · 252 lines · 23 tokens per session scan A 490536321497
nav-architecture-review is a skill published in the GitHub repository navikt/copilot (54 stars, last pushed yesterday), licensed MIT. It adds 23 tokens to every session and 2,226 once invoked, about $0.0001 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 2026-08-30.
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