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 equinor/fusion-skills --skill fusion-code-conventionsgit clone --depth 1 https://github.com/equinor/fusion-skillsWrote 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/equinor/fusion-skills/fusion-code-conventions)<a href="https://agentmods.dev/skills/equinor/fusion-skills/fusion-code-conventions"><img src="https://agentmods.dev/badge/skills/equinor/fusion-skills/fusion-code-conventions/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/equinor/fusion-skills/fusion-code-conventions"><img src="https://agentmods.dev/badge/skills/equinor/fusion-skills/fusion-code-conventions.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk 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 | $0.00152 | $0.01785 |
| Opus 5.5 | $0.00061 | $0.00714 |
| Sonnet 5.5 | $0.00030 | $0.00357 |
| Haiku 4.5 | $0.00015 | $0.00178 |
Grade A, and why
fusion-code-conventions 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 — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Conventions
When to use
Use when code needs review, writing, or explanation against project conventions. Applies at two layers:
- Language conventions — naming, file naming, type system, TSDoc/XML doc standards, code structure, error handling, async patterns, dead code policy. Each language has a dedicated agent and authoritative reference doc.
- Cross-cutting conventions — applied on every review: intent capture (every non-obvious decision must be documented well enough that code could be regenerated from comments alone) and constitution enforcement (ADRs and contributor docs are law; deviations require a new decision record; stale decisions flagged).
Typical triggers:
- "what are the naming conventions for this project?"
- "how should I write TSDoc for this function?"
- "does this file follow our code style?"
- "review this for convention violations"
- "what comment style should I use here?"
- "is this idiomatic TypeScript / React / C# / Markdown?"
- "apply code conventions to this file"
- "are these inline comments good enough?"
- "does this violate any ADR?"
- "is this ADR still current?"
- "we have a CONTRIBUTING.md — check if this change follows it"
When not to use
- Security vulnerability scanning (use a dedicated security review skill)
- Performance profiling or benchmarking
- High-level architecture or system design decisions
- Generating net-new code without a review target
- Mutating files without explicit user confirmation
Precedence and applicability
This skill provides org-wide baseline conventions. When installed in a repository with its own conventions, precedence (highest wins):
- Repository-level policy —
CONTRIBUTING.md, contributor guides (contribute/), ADRs,.github/copilot-instructions.md,AGENTS.md, or equivalent - Tooling configuration —
biome.json,tsconfig.json,.editorconfig, linter configs - This skill — all rules in
references/*.conventions.mdand agent modes
When a repository explicitly narrows, relaxes, or contradicts a rule from this skill, the repository policy wins. Don't flag code that conforms to repo's documented conventions, even if it deviates from the skill baseline.
What ships with it
14 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.
- agents/constitution.agent.md 7.0 KB
- agents/csharp.agent.md 2.5 KB
- agents/intent.agent.md 8.8 KB
- agents/markdown.agent.md 1.8 KB
- agents/react.agent.md 2.1 KB
- agents/typescript.agent.md 2.1 KB
- assets/core-service.follow-up.md 5.6 KB
- assets/framework-core-developer.follow-up.md 5.0 KB
- assets/react-app.follow-up.md 4.4 KB
- CHANGELOG.md 3.3 KB
- references/csharp.conventions.md 9.1 KB
- references/markdown.conventions.md 3.4 KB
- references/react.conventions.md 2.0 KB
- references/typescript.conventions.md 10 KB
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 Changed 7bce110974be
- 1mo ago First seen · 154 lines · 152 tokens per session scan A 67c7fbf7aa86
fusion-code-conventions is a skill published in the GitHub repository equinor/fusion-skills (2 stars, last pushed 14d ago), licensed MIT. It adds 152 tokens to every session and 1,785 once invoked, about $0.0006 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 2026-08-31.
Other skills, from other repositories
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
next-cache-components-optimizer
Optimize the meaningful UI available immediately from a Next.js route on an initial load (hard navigation) or named client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route and entry point at a time; the shipped test then guards…