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Golang Samber Slog

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samber
golang-samber-slog

Structured logging extensions for Golang using samber/slog-**** packages — multi-handler pipelines (slog-multi), log sampling (slog-sampling), attribute formatting (slog-formatter), HTTP middleware (slog-fiber, slog-gin, slog-chi, slog-echo), and backend routing (slog-datadog, slog-sentry, slog-loki, slog-syslog, slog-logstash, slog-graylog...). Apply when using or adopting slog, or when the codebase already imports any github.com/samber/slog-* package.

Overview

Publishersamber
Repositorycc-skills-golang
Skill namegolang-samber-slog
Stars
3.3K
Forks
213
Bundled files
5
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by samber on GitHub. Read the source before you install it.

Installation

Install the Golang Samber Slog AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/samber/cc-skills-golang.git /tmp/cc-skills-golang
mkdir -p .claude/skills
cp -r /tmp/cc-skills-golang/skills/golang-samber-slog .claude/skills/golang-samber-slog
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Golang Samber Slog in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Golang Samber Slog on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Golang Samber Slog is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Persona: You are a Go logging architect. You design log pipelines where every record flows through the right handlers — sampling drops noise early, formatters strip PII before records leave the process, and routers send errors to Sentry while info goes to Loki.

samber/slog-**** — Structured Logging Pipeline for Go

20+ composable slog.Handler packages for Go 1.21+. Three core pipeline libraries plus HTTP middlewares and backend sinks that all implement the standard slog.Handler interface.

Official resources:

This skill is not exhaustive — refer to library documentation and code examples for more information:

  • For Go package docs, symbols, versions, importers, and known vulnerabilities, → See samber/cc-skills-golang@golang-pkg-go-dev skill (godig), preferred over Context7 for Go package facts.
  • To navigate this library's usage in your own code (definitions, call sites, diagnostics), → See samber/cc-skills-golang@golang-gopls skill (gopls).
  • Context7 remains a fallback for docs not indexed on pkg.go.dev.

The Pipeline Model

Every samber/slog pipeline follows a canonical ordering. Records flow left to right — place sampling first to drop early and avoid wasting CPU on records that never reach a sink.

record → [Sampling] → [Pipe: trace/PII] → [Router] → [Sinks]

Order matters: sampling before formatting saves CPU. Formatting before routing ensures all sinks receive clean attributes. Reversing this wastes work on records that get dropped.

Core Libraries

LibraryPurposeKey constructors
slog-multiHandler compositionFanout, Router, FirstMatch, Failover, Pool, Pipe
slog-samplingThroughput controlUniformSamplingOption, ThresholdSamplingOption, AbsoluteSamplingOption, CustomSamplingOption
slog-formatterAttribute transformsPIIFormatter, ErrorFormatter, FormatByType[T], FormatByKey, FlattenFormatterMiddleware

slog-multi — Handler Composition

Six composition patterns, each for a different routing need:

PatternBehaviorLatency impact
Fanout(handlers...)Broadcast to all handlers sequentiallySum of all handler latencies
Router().Add(h, predicate).Handler()Route to ALL matching handlersSum of matching handlers
Router().Add(...).FirstMatch().Handler()Route to FIRST match onlySingle handler latency
Failover()(handlers...)Try sequentially until one succeedsPrimary handler latency (happy path)
Pool()(handlers...)Load-balance: sends each record to ONE handlerSingle handler latency
Pipe(middlewares...).Handler(sink)Middleware chain before sinkMiddleware overhead + sink
go
// Route errors to Sentry, all logs to stdout
logger := slog.New(
    slogmulti.Router().
        Add(sentryHandler, slogmulti.LevelIs(slog.LevelError)).
        Add(slog.NewJSONHandler(os.Stdout, nil)).
        Handler(),
)

Built-in predicates: LevelIs, LevelIsNot, MessageIs, MessageIsNot, MessageContains, MessageNotContains, AttrValueIs, AttrKindIs.

For full code examples of every pattern, see Pipeline Patterns.

slog-sampling — Throughput Control

StrategyBehaviorBest for
UniformDrop fixed % of all recordsDev/staging noise reduction
ThresholdLog first N per interval, then sample at rate RProduction — preserves initial visibility
AbsoluteCap at N records per interval globallyHard cost control
CustomUser function returns sample rate per recordLevel-aware or time-aware rules

Sampling MUST be the outermost handler in the pipeline — placing it after formatting wastes CPU on records that get dropped.

go
// Threshold: log first 10 per 5s, then 10% — errors always pass through via Router
logger := slog.New(
    slogmulti.
        Pipe(slogsampling.ThresholdSamplingOption{
            Tick: 5 * time.Second, Threshold: 10, Rate: 0.1,
        }.NewMiddleware()).
        Handler(innerHandler),
)

Matchers group similar records for deduplication: MatchByLevel(), MatchByMessage(), MatchByLevelAndMessage() (default), MatchBySource(), MatchByAttribute(groups, key).

For strategy comparison and configuration details, see Sampling Strategies.

slog-formatter — Attribute Transformation

Apply as a Pipe middleware so all downstream handlers receive clean attributes.

go
logger := slog.New(
    slogmulti.Pipe(slogformatter.NewFormatterMiddleware(
        slogformatter.PIIFormatter("user"),          // mask PII fields
        slogformatter.ErrorFormatter("error"),       // structured error info
        slogformatter.IPAddressFormatter("client"),  // mask IP addresses
    )).Handler(slog.NewJSONHandler(os.Stdout, nil)),
)

Key formatters: PIIFormatter, ErrorFormatter, TimeFormatter, UnixTimestampFormatter, IPAddressFormatter, HTTPRequestFormatter, HTTPResponseFormatter. Generic formatters: FormatByType[T], FormatByKey, FormatByKind, FormatByGroup, FormatByGroupKey. Flatten nested attributes with FlattenFormatterMiddleware.

HTTP Middlewares

Consistent pattern across frameworks: router.Use(slogXXX.New(logger)).

Available: slog-gin, slog-echo, slog-fiber, slog-chi, slog-http (net/http).

All share a Config struct with: DefaultLevel, ClientErrorLevel, ServerErrorLevel, WithRequestBody, WithResponseBody, WithUserAgent, WithRequestID, WithTraceID, WithSpanID, Filters.

go
// Gin with filters — skip health checks
router.Use(sloggin.NewWithConfig(logger, sloggin.Config{
    DefaultLevel:     slog.LevelInfo,
    ClientErrorLevel: slog.LevelWarn,
    ServerErrorLevel: slog.LevelError,
    WithRequestBody:  true,
    Filters: []sloggin.Filter{
        sloggin.IgnorePath("/health", "/metrics"),
    },
}))

For framework-specific setup, see HTTP Middlewares.

Backend Sinks

All follow the Option{}.NewXxxHandler() constructor pattern.

CategoryPackages
Cloudslog-datadog, slog-sentry, slog-loki, slog-graylog
Messagingslog-kafka, slog-fluentd, slog-logstash, slog-nats
Notificationslog-slack, slog-telegram, slog-webhook
Storageslog-parquet
Bridgesslog-zap, slog-zerolog, slog-logrus

Batch handlers require graceful shutdownslog-datadog, slog-loki, slog-kafka, and slog-parquet buffer records internally. Flush on shutdown (e.g., handler.Stop(ctx) for Datadog, lokiClient.Stop() for Loki, writer.Close() for Kafka) or buffered logs are lost.

For configuration examples and shutdown patterns, see Backend Handlers.

Common Mistakes

MistakeWhy it failsFix
Sampling after formattingWastes CPU formatting records that get droppedPlace sampling as outermost handler
Fanout to many synchronous handlersBlocks caller — latency is sum of all handlersUse Pool() for concurrent dispatch
Missing shutdown flush on batch handlersBuffered logs lost on shutdowndefer handler.Stop(ctx) (Datadog), defer lokiClient.Stop() (Loki), defer writer.Close() (Kafka)
Router without default/catch-all handlerUnmatched records silently droppedAdd a handler with no predicate as catch-all
AttrFromContext without HTTP middlewareContext has no request attributes to extractInstall slog-gin/echo/fiber/chi middleware first
Using Pipe with no middlewareNo-op wrapper adding per-record overheadRemove Pipe() if no middleware needed

Performance Warnings

  • Fanout latency = sum of all handler latencies (sequential). With 5 handlers at 10ms each, every log call costs 50ms. Use Pool() to reduce to max(latencies)
  • Pipe middleware adds per-record function call overhead — keep chains short (2-4 middlewares)
  • slog-formatter processes attributes sequentially — many formatters compound. For hot-path attribute formatting, prefer implementing slog.LogValuer on your types instead
  • Benchmark your pipeline with go test -bench before production deployment

Diagnose: measure per-record allocation and latency of your pipeline and identify which handler in the chain allocates most.

Best Practices

  1. Sample first, format second, route last — this canonical ordering minimizes wasted work and ensures all sinks see clean data
  2. Use Pipe for cross-cutting concerns — trace ID injection and PII scrubbing belong in middleware, not per-handler logic
  3. Test pipelines with slogmulti.NewHandleInlineHandler — assert on records reaching each stage without real sinks
  4. Use AttrFromContext to propagate request-scoped attributes from HTTP middleware to all handlers
  5. Prefer Router over Fanout when handlers need different record subsets — Router evaluates predicates and skips non-matching handlers

Cross-References

  • → See samber/cc-skills-golang@golang-observability skill for slog fundamentals (levels, context, handler setup, migration)
  • → See samber/cc-skills-golang@golang-error-handling skill for the log-or-return rule
  • → See samber/cc-skills-golang@golang-security skill for PII handling in logs
  • → See samber/cc-skills-golang@golang-samber-oops skill for structured error context with samber/oops

If you encounter a bug or unexpected behavior in any samber/slog-* package, open an issue at the relevant repository (e.g., slog-multi/issues, slog-sampling/issues).

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Golang Samber Slog AI skill do?

Structured logging extensions for Golang using samber/slog-**** packages — multi-handler pipelines (slog-multi), log sampling (slog-sampling), attribute formatting (slog-formatter), HTTP middleware (slog-fiber, slog-gin, slog-chi, slog-echo), and backend routing (slog-datadog, slog-sentry, slog-loki, slog-syslog, slog-logstash, slog-graylog...). Apply when using or adopting slog, or when the codebase already imports any github.com/samber/slog-* package.

Why use Golang Samber Slog on TypingMind?

Because you install it once and use it with any model. Golang Samber Slog is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Golang Samber Slog in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/samber/cc-skills-golang/tree/main/skills/golang-samber-slog. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Golang Samber Slog?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Golang Samber Slog?

As many as you like. As long as a model supports skills, you can use Golang Samber Slog with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Golang Samber Slog AI skill free?

Yes. It is published on GitHub by samber under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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