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Iii Observability

OrganizationPopular
iii-hq
iii-observability

OpenTelemetry-backed tracing, structured logs, metrics with rollups, alerts, sampling, and baggage for the engine — emit and query telemetry through `engine::*` functions and react to logs with a `log` trigger.

Overview

Publisheriii-hq
Repositoryiii
Skill nameiii-observability
Stars
18.8K
Forks
1.3K
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by iii-hq on GitHub. Read the source before you install it.

Installation

Install the Iii Observability 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.
    https://github.com/iii-hq/iii/tree/main/engine/src/workers/observability/skills
  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/iii-hq/iii.git /tmp/iii
mkdir -p .claude/skills
cp -r /tmp/iii/engine/src/workers/observability/skills .claude/skills/iii-observability
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Iii Observability 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 Iii Observability 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 Iii Observability 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.

iii-observability

The iii-observability worker provides OpenTelemetry-backed observability for the iii engine: distributed tracing, structured logs, metrics with rollups, alert rules, sampling configuration, and baggage propagation. Every surface is a callable engine::* function, plus a single log reactive trigger that fires on every ingested log entry. Functions span nine sub-namespaces — emit, query stored telemetry, inspect configuration, and propagate context.

The worker is on by default (enabled: true). When disabled, the emit and read functions still register but become no-ops and the trigger never fires. Core config: service_name/service_version/service_namespace (OTel resource attributes), exporter (memory | otlp | both), endpoint (OTLP collector URL, default http://localhost:4317), sampling_ratio (0.0–1.0), memory_max_spans, and per-pillar toggles/limits (metrics_enabled, logs_enabled, retention and count caps). Most fields accept OTEL_* env overrides. The in-memory query functions (logs, traces) require the memory or both exporter.

Traces and metrics use OTLP/gRPC by default; https:// endpoints enable TLS and http:// endpoints use cleartext. Set OTEL_EXPORTER_OTLP_PROTOCOL=http/protobuf to use OTLP/HTTP protobuf for traces and metrics, or use OTEL_EXPORTER_OTLP_TRACES_PROTOCOL / OTEL_EXPORTER_OTLP_METRICS_PROTOCOL for signal-specific overrides. The HTTP/protobuf path is appended automatically (/v1/traces, /v1/metrics) when the configured endpoint is a base collector URL. Logs export over OTLP/HTTP to /v1/logs.

Use OTEL_EXPORTER_OTLP_HEADERS for collector headers and the signal-specific OTEL_EXPORTER_OTLP_TRACES_HEADERS, OTEL_EXPORTER_OTLP_METRICS_HEADERS, or OTEL_EXPORTER_OTLP_LOGS_HEADERS when needed. The logs exporter reads OTEL_EXPORTER_OTLP_LOGS_HEADERS first and falls back to OTEL_EXPORTER_OTLP_HEADERS. Keep credentials in environment variables or a secret manager, not in config files.

When to Use

  • Emit structured logs or read back stored logs/spans/metrics from inside a function instead of shelling out to a collector.
  • React in real time to log entries (page on errors, archive everything) without polling.
  • Inspect engine health, active sampling rules, or alert state operationally.
  • Propagate OpenTelemetry baggage across calls for cross-cutting context.

Boundaries

  • engine::baggage::set does not propagate back to the caller — baggage propagation happens at the SDK/invocation level via headers.
  • The in-memory query functions return nothing useful unless the memory (or both) exporter is configured; with otlp-only the data lives in your collector.
  • When logs_enabled is off the log pipeline is dormant and the log trigger never fires; the ingest level sets the minimum severity stored.
  • This worker observes telemetry — it is not a general event bus (pubsub) or durable queue (queue); those are standalone Compose workers.

Functions

  • engine::log::info, engine::log::warn, engine::log::error, engine::log::debug, engine::log::trace — emit a log entry at the named severity; same input shape, only the level differs.
  • engine::logs::list — read stored OTel logs, filtered by time, trace correlation, or severity.
  • engine::logs::clear — wipe the in-memory log store.
  • engine::traces::list — list compact trace summaries with aggregate status/counts and optional attribute projection.
  • engine::traces::spans — list full span records for detail/timeline consumers.
  • engine::traces::tree — walk a single trace as a parent/child tree.
  • engine::traces::group_by — aggregate stored spans by an attribute value (counts, duration, errors per group).
  • engine::traces::clear — wipe stored spans.
  • engine::metrics::list — list metrics with aggregated stats and optional time bucketing.
  • engine::rollups::list — list metric rollup aggregations across 1-minute, 5-minute, and 1-hour windows.
  • engine::baggage::get, engine::baggage::get_all — read one or all OpenTelemetry baggage keys.
  • engine::baggage::set — set a baggage key locally (does not propagate to the caller).
  • engine::sampling::rules — list the active sampling rules.
  • engine::health::check — return engine health (status, per-component breakdown, version).
  • engine::alerts::list — inspect configured alert rules and current state.
  • engine::alerts::evaluate — manually run an alert evaluation pass.

Reactive triggers

Bind a log trigger when a function should run every time a log entry lands in the engine's OTel log pipeline — emitted via engine::log::*, ingested via OTLP, or recorded by any worker using structured logging. Each subscription receives the same OTel-shaped record, so handlers can route by severity, attribute, or trace correlation.

Reach for it when:

  • A specific severity (typically error) should page a human, post to Slack, or open a ticket.
  • You want real-time fan-out of log entries to a downstream sink (archive, analytics, transformer) without polling engine::logs::list.

Use engine::logs::list instead when you need to query stored entries on demand rather than react to each as it arrives.

How to bind

  1. Register a handler: iii.registerFunction('monitoring::on-error', handler).
  2. Register the trigger:
typescript
iii.registerTrigger({
  type: "log",
  function_id: "monitoring::on-error",
  config: {
    level: "error", // optional. trace|debug|info|warn|error. Omit to fire on every level.
  },
});

The log trigger only fires when the logs pipeline is enabled, and level filters to that minimum severity. The handler's return value is ignored; invocations are spawned asynchronously after each entry is stored.

For the OTel log record shape, call iii get function info on the trigger type or handler function id.

Frequently asked questions

What does the Iii Observability AI skill do?

OpenTelemetry-backed tracing, structured logs, metrics with rollups, alerts, sampling, and baggage for the engine — emit and query telemetry through `engine::*` functions and react to logs with a `log` trigger.

Why use Iii Observability on TypingMind?

Because you install it once and use it with any model. Iii Observability 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 Iii Observability in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/iii-hq/iii/tree/main/engine/src/workers/observability/skills. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Iii Observability?

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 Iii Observability?

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

Is the Iii Observability AI skill free?

It is published on GitHub by iii-hq. Check the repository for licensing terms. 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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