Ring:Using Runtime logo

Ring:Using Runtime

Organization
LerianStudio
ring:using-runtime

Using lib-observability/runtime, which turns silent goroutine deaths into log/span/metric signal, in two modes. Sweep Mode detects naked goroutines, unobservable defer recover(), missing InitPanicMetrics, and lib-commons/v5 shim imports. Reference Mode catalogs SafeGo, RecoverWithPolicy, the policy decision tree, and Fiber/gRPC/RabbitMQ integration. Go-only. Skip for non-Go or frontend code.

Overview

PublisherLerianStudio
Repositoryring
Skill namering:using-runtime
Stars
215
Forks
28
Bundled files
2
LicenseApache-2.0
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.

  • 2 bundled files

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

  • Open source

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

Installation

Install the Ring:Using Runtime 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/LerianStudio/ring.git /tmp/ring
mkdir -p .claude/skills
cp -r /tmp/ring/dev-team/skills/using-runtime .claude/skills/lerianstudio-ring-using-runtime
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ring:Using Runtime 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 Ring:Using Runtime 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 Ring:Using Runtime 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.

ring:using-runtime

Moved from lib-commons

The runtime package lived in lib-commons through v4 and the v5 shim period. Its canonical home is now github.com/LerianStudio/lib-observability/runtime (v1.0.0+). lib-commons v5 keeps a deprecated compatibility shim at github.com/LerianStudio/lib-commons/v5/commons/runtime that re-exports every symbol from lib-observability — existing imports keep compiling, but the shim is marked Deprecated: in package docs and will be removed in a future lib-commons major. New code MUST import from lib-observability/runtime directly; sweeps SHOULD also flag imports still pointing at the lib-commons shim as a follow-up migration.

When to use

Sweep mode:

  • "Sweep / audit panic handling"
  • "Find naked goroutines"
  • "Migrate this service to lib-observability/runtime"
  • "Are our defer recover() calls observable?"

Reference mode:

  • "Which SafeGo variant do I use for X?"
  • "How does the observability trident fire on panic?"
  • "Show me the policy decision tree"
  • "How do I wire runtime into Fiber / gRPC / RabbitMQ?"

Skip when

  • Working on non-Go services
  • Working on frontend code

Related

Parent: ring:using-lib-observability (canonical home of the runtime package) Similar: ring:using-lib-commons (lifecycle / App glue still lives there), ring:using-assert

Extends ring:using-lib-observability panic-handling coverage into 6 focused sub-angles with deeper detection patterns, full API reference, policy decision tree, and framework integrations. Also extends ring:using-lib-commons Angle 15 (Panic handling DIY) for codebases still on the v5 shim path. Use when panic handling is the primary concern or when the parent sweep surfaced significant findings.

Mode Selection

Request ShapeMode
"Sweep / audit panic handling / find naked goroutines"Sweep
"Which SafeGo variant do I use?"Reference
"Policy decision tree"Reference
"Framework integration (Fiber/gRPC/RabbitMQ)"Reference

SWEEP MODE

4-phase sweep. Each phase has a hard gate.

Phase 1: Version Reconnaissance   → runtime-version-report.json
Phase 2: CHANGELOG Delta Analysis → runtime-delta-report.json
Phase 3: Multi-Angle DIY Sweep    → 6 × runtime-sweep-{N}-{angle}.json
Phase 4: Consolidated Report      → runtime-sweep-report.md + runtime-sweep-tasks.json

Phase 1: Version Reconnaissance

  1. Read go.mod — extract pinned version of github.com/LerianStudio/lib-observability (canonical) AND any pinned github.com/LerianStudio/lib-commons/vN (shim path)
  2. WebFetch https://api.github.com/repos/LerianStudio/lib-observability/releases/latest — extract tag_name for the canonical library
  3. If the target imports lib-commons/v5/commons/runtime (deprecated shim), record shim_import_detected: true — this is itself a follow-up migration finding
  4. Classify drift; emit /tmp/runtime-version-report.json

Phase 2: CHANGELOG Delta Analysis

  1. WebFetch https://raw.githubusercontent.com/LerianStudio/lib-observability/main/CHANGELOG.md
  2. Filter entries affecting the runtime package
  3. If shim_import_detected from Phase 1, also WebFetch https://raw.githubusercontent.com/LerianStudio/lib-commons/main/CHANGELOG.md and filter for commons/runtime shim-deprecation entries
  4. Emit /tmp/runtime-delta-report.json

Phase 3: Multi-Angle DIY Sweep

⛔ STOP-CHECK BEFORE DISPATCH

Before emitting any Task call, count the explorers you intend to launch in this turn.

  • Count MUST equal 6.
  • If count < 6 → STOP. Do not partial-dispatch. Reconcile against the 6 angles below and try again.
  • The 6 angles are the canonical sweep. No substitutions, no omissions.

⛔ MUST NOT trickle-dispatch

All 6 explorers leave in the SAME TURN, before reading any explorer output.

Forbidden sequences:

  • Dispatch explorer 1 → read result → dispatch explorer 2
  • Dispatch a subset → wait → dispatch the rest
  • Dispatch follow-up explorers conditioned on partial output
  • Loop sequentially over the angle list

If you find yourself about to dispatch an explorer in a turn AFTER any explorer has already returned a result → STOP. You violated parallel dispatch. Report the violation and mark the phase INCOMPLETE rather than completing the trickle.

Self-verify after dispatch

After the dispatch turn, verify all 6 Task calls were emitted in that single turn. If fewer than 6 went out, the phase did NOT execute correctly. Mark INCOMPLETE and surface the dispatch failure — do NOT silently continue with a partial pool.

Parallel dispatch — atomic batch

Emit all 6 Task calls in a SINGLE TURN, as one atomic batch.

If your runtime exposes a multi_tool_use.parallel wrapper, use it to dispatch the complete pool in one wrapped invocation. This is the canonical fan-out mechanism on OpenAI-style tool envelopes and on certain Anthropic SDK consumers — naming it explicitly activates parallel emission on runtimes where trickle-dispatch is the default behavior.

If your runtime emits parallel tool_use blocks natively (Claude Code with Claude models), multi_tool_use.parallel may not be needed — but naming it is harmless and serves as an enforcement anchor.

The STOP-CHECK, anti-trickle, and self-verify guards above remain binding regardless of which mechanism your runtime uses.

Dispatch all 6 explorer angles in one parallel batch. Wait for all before Phase 4.

Per-explorer dispatch (subagent_type: ring:codebase-explorer):

## Target: <absolute path>
## Your Angle: <angle number + name>
## Severity / DIY Patterns / Replacement / Migration Complexity / Version Context
<verbatim from sub-files/sweep-angles.md for this angle>

## Output
Write to: /tmp/runtime-sweep-{N}-{angle-slug}.json
Schema: { angle_number, angle_name, severity, migration_complexity,
  findings: [{file, line, diy_pattern, replacement, evidence_snippet, notes}],
  summary, requires_major_upgrade }
If no findings: write file with empty findings array.

Full angle specifications: sub-files/sweep-angles.md

The 6 angles cover:

  1. Naked goroutine launches (CRITICAL)
  2. Unobservable defer recover() (CRITICAL)
  3. Missing InitPanicMetrics at startup (HIGH)
  4. Missing SetProductionMode(true) in production (HIGH)
  5. Framework panic handlers bypassing HandlePanicValue (HIGH)
  6. Policy mismatch — KeepRunning vs CrashProcess (MEDIUM)

Phase 4: Consolidated Report

Dispatch synthesizer to read all 6 files and emit:

  1. /tmp/runtime-sweep-report.md
  2. /tmp/runtime-sweep-tasks.json

Surface report path + task count; offer handoff to ring:running-dev-cycle.


REFERENCE MODE

Full API reference in sub-files/reference.md. Load sections relevant to your task.

Quick Navigation

#SectionWhat you'll find
1API SurfaceSafeGo / RecoverWithPolicy / HandlePanicValue / Init / SetProductionMode
2Policy Decision TreeKeepRunning vs CrashProcess
3Pattern CatalogConsumer loops, fan-out, tickers, Fiber/gRPC/RabbitMQ
4Observability TridentLog + span event + metric on panic
5Testing PatternsProving recovery fires
6Anti-Pattern CatalogSix failure modes
7Bootstrap OrderWhere runtime setup fits in init
8–10Cross-Cutting, Breaking Changes, Cross-Referencesv4→v5 delta

Read sub-files/reference.md for full API detail.

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 Ring:Using Runtime AI skill do?

Using lib-observability/runtime, which turns silent goroutine deaths into log/span/metric signal, in two modes. Sweep Mode detects naked goroutines, unobservable defer recover(), missing InitPanicMetrics, and lib-commons/v5 shim imports. Reference Mode catalogs SafeGo, RecoverWithPolicy, the policy decision tree, and Fiber/gRPC/RabbitMQ integration. Go-only. Skip for non-Go or frontend code.

Why use Ring:Using Runtime on TypingMind?

Because you install it once and use it with any model. Ring:Using Runtime 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 Ring:Using Runtime in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/LerianStudio/ring/tree/main/dev-team/skills/using-runtime. 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 Ring:Using Runtime?

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 Ring:Using Runtime?

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

Is the Ring:Using Runtime AI skill free?

Yes. It is published on GitHub by LerianStudio under the Apache-2.0 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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