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 adamwang99/NEUTRON-EVO-OS --skill go-reviewergit clone --depth 1 https://github.com/adamwang99/NEUTRON-EVO-OSWrote 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/adamwang99/neutron-evo-os/go-reviewer)<a href="https://agentmods.dev/skills/adamwang99/neutron-evo-os/go-reviewer"><img src="https://agentmods.dev/badge/skills/adamwang99/neutron-evo-os/go-reviewer/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/adamwang99/neutron-evo-os/go-reviewer"><img src="https://agentmods.dev/badge/skills/adamwang99/neutron-evo-os/go-reviewer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00003 | $0.00257 |
| Opus 5.5 | $0.00001 | $0.00103 |
| Sonnet 5.5 | $0.00001 | $0.00051 |
| Haiku 4.5 | $0.00000 | $0.00026 |
Grade A, and why
go-reviewer 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 2mo 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.
What it actually says
Go Reviewer Skill
Purpose
Expert Go code reviewer: goroutines, channels, error handling, interface design.
What It Checks
- Goroutine leaks — goroutines started but never terminated
- Race conditions — unsynchronized access to shared state
- Error wrapping —
%wvs%v, proper error chain - Context propagation —
ctxpassed correctly, never stored in struct - Interface segregation — small interfaces, dependency inversion
- Dependency hygiene —
go.modclean,go.sumcomplete - go vet / golangci-lint — static analysis violations
Output Format
Structured findings with severity:
[CRITICAL]— goroutine leak, race condition[HIGH]— missing error wrap, context misuse[MEDIUM]— lint warnings, interface design[LOW]— suggestions
Based On
Inspired by everything-claude-code's go-reviewer agent.
What ships with it
2 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.
- 2mo ago First seen · 37 lines · 3 tokens per session scan A 877088f1bae8
go-reviewer is a skill published in the GitHub repository adamwang99/NEUTRON-EVO-OS (20 stars, last pushed 6mo ago), licensed MIT. It adds 3 tokens to every session and 257 once invoked, about $0.0000 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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