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 alexastrum/skl --skill golang-troubleshootinggit clone --depth 1 https://github.com/alexastrum/sklWrote 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/alexastrum/skl/golang-troubleshooting)<a href="https://agentmods.dev/skills/alexastrum/skl/golang-troubleshooting"><img src="https://agentmods.dev/badge/skills/alexastrum/skl/golang-troubleshooting/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/alexastrum/skl/golang-troubleshooting"><img src="https://agentmods.dev/badge/skills/alexastrum/skl/golang-troubleshooting.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 | $0.00130 | $0.02759 |
| Opus 5 | $0.00065 | $0.01380 |
| Sonnet 5 | $0.00026 | $0.00552 |
| Haiku 4.5 | $0.00013 | $0.00276 |
Grade A, and why
golang-troubleshooting scanned grade A with 1 finding 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 11d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
→ curl localhost:6060/debug/pprof/goroutine?debug=2 This is a copy
94% identical to golang-troubleshooting — 20 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 189 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Persona: You are a Go systems debugger. You follow evidence, not intuition — instrument, reproduce, and trace root causes systematically.
Thinking mode: Use ultrathink for debugging and root cause analysis. Rushed reasoning leads to symptom fixes — deep thinking finds the actual root cause.
Modes:
- Single-issue debug (default): Follow the sequential Golden Rules — read the error, reproduce, one hypothesis at a time. Do not launch sub-agents; focused sequential investigation is faster for a single known symptom.
- Codebase bug hunt (explicit audit of a large codebase): Launch up to 5 parallel sub-agents, one per bug category (nil/interface, resources, error handling, races, context/slice/map). Use this mode when the user asks for a broad sweep, not when debugging a specific reported issue.
Go Troubleshooting Guide
NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST. Symptom fixes create new bugs and waste time. This process applies ESPECIALLY under time pressure — rushing leads to cascading failures that take longer to resolve.
When the user reports a bug, crash, performance problem, or unexpected behavior in Go code:
- Start with the Decision Tree below to identify the symptom category and jump to the relevant section.
- Follow the Golden Rules — especially: reproduce before you fix, one hypothesis at a time, find the root cause.
- Work through the General Debugging Methodology step by step. Do not skip steps.
- Watch for Red Flags in your own reasoning. If you catch yourself guessing at fixes without understanding the cause, stop and gather more evidence.
- Escalate tools incrementally. Start with the simplest diagnostic (
fmt.Println, test isolation) and only reach for pprof, Delve, or GODEBUG when simpler tools are insufficient. - Never propose a fix you cannot explain. If you do not understand why the bug happens, say so and investigate further.
Quick Decision Tree
WHAT ARE YOU SEEING?
"Build won't compile"
→ go build ./... 2>&1, go vet ./...
→ See [compilation.md](./references/compilation.md)
"Wrong output / logic bug"
→ Write a failing test → Check error handling, nil, off-by-one
→ See [common-go-bugs.md](./references/common-go-bugs.md), [testing-debug.md](./references/testing-debug.md)
"Random crashes / panics"
→ GOTRACEBACK=all ./app → go test -race ./...
→ See [common-go-bugs.md](./references/common-go-bugs.md), [diagnostic-tools.md](./references/diagnostic-tools.md)
"Sometimes works, sometimes fails"
→ go test -race ./...
→ See [concurrency-debug.md](./references/concurrency-debug.md), [testing-debug.md](./references/testing-debug.md)
"Program hangs / frozen"
→ curl localhost:6060/debug/pprof/goroutine?debug=2
→ See [concurrency-debug.md](./references/concurrency-debug.md), [pprof.md](./references/pprof.md)
"High CPU usage"
→ pprof CPU profiling
→ See [performance-debug.md](./references/performance-debug.md), [pprof.md](./references/pprof.md)
"Memory growing over time"
→ pprof heap profiling
→ See [performance-debug.md](./references/performance-debug.md), [concurrency-debug.md](./references/concurrency-debug.md)
"Slow / high latency / p99 spikes"
→ CPU + mutex + block profiles
→ See [performance-debug.md](./references/performance-debug.md), [diagnostic-tools.md](./references/diagnostic-tools.md)
"Simple bug, easy to reproduce"
→ Write a test, add fmt.Println / log.Debug
→ See [testing-debug.md](./references/testing-debug.md)
What ships with it
11 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.
- evals/evals.json 45 KB
- references/code-review-flags.md 1.9 KB
- references/common-go-bugs.md 23 KB
- references/compilation.md 647 B
- references/concurrency-debug.md 2.9 KB
- references/diagnostic-tools.md 3.0 KB
- references/methodology.md 9.3 KB
- references/performance-debug.md 1.5 KB
- references/pprof.md 4.7 KB
- references/production-debug.md 3.1 KB
- references/testing-debug.md 3.2 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.
- 11d ago First seen · 189 lines · 130 tokens per session scan A b5a57ea62ec6
golang-troubleshooting is a skill published in the GitHub repository alexastrum/skl (11 stars, last pushed 3mo ago), licensed MIT. It adds 130 tokens to every session and 2,759 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 94% identical to golang-troubleshooting, differing in 20 lines, and is treated as a copy.
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