Observal Ops

OrganizationPopular

Observal

observal-ops

Inspects Observal traces, sessions, rankings, feedback, telemetry health, logs, and Agent insight reports. Use when the user wants operational evidence, current activity, telemetry diagnosis, ratings, report generation, regression analysis, or recommendations grounded in Agent usage.

Overview

Publisher	Observal
Repository	`Observal`
Skill name	`observal-ops`
Stars	2.4K
Forks	472
Bundled files	2
License	Apache-2.0
Links	Skill source Repository Homepage

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 Observal on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
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.

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/Observal/Observal.git /tmp/Observal
mkdir -p .claude/skills
cp -r /tmp/Observal/observal_cli/skills/observal-ops .claude/skills/observal-ops

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Observal Ops 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 Observal Ops 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 Observal Ops 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.

Observing Observal

Execution contract

Execute commands with a 60 second timeout. Use a longer timeout only for report generation or an intentional stream.
Use machine output by default: add --output json whenever supported. Parse list envelopes, finite objects, and JSON Lines separately.
Run --help before acting when a path or flag is uncertain.
Start with the narrowest read that answers the question. Do not generate a new report when a completed report already suffices.
Ground every conclusion in returned fields, report period, and sample size. Distinguish missing data from healthy data.
Verify rating mutations and report generation results.
Never repeat secrets or sensitive trace and log content unless the user explicitly requests the specific data and is authorized.
After an uncertain rating or report-generation failure, read current state before retrying.

Choose the workflow

User intent	Read
Sessions, traces, rankings, ratings, telemetry, or logs	Operational workflows
Agent health, friction, costs, versions, regressions, or suggestions	Insight reports

Read the selected reference completely before executing.

Analysis rules

A zero exit status from telemetry diagnosis can still contain issues or warnings. Read the JSON health fields.
No events is not automatically a hook problem. Check authentication, server reachability, local outbox, and hook state in that order.
Quote report evidence accurately and say when session count is thin.
Only component_ref proves an insight suggestion maps to a Registry component. Never reconstruct a component identity from prose.
Lead with reuse suggestions before create-new suggestions.
For logs and traces, summarize the minimum sensitive content needed to answer the question.

Completion

Report the time range, filters, counts, health state, strongest evidence, uncertainty, and concrete next action. Do not present popularity fallback or sparse reports as personalized certainty.

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 Observal Ops AI skill do?

Why use Observal Ops on TypingMind?

Because you install it once and use it with any model. Observal Ops 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 Observal Ops in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Observal/Observal/tree/main/observal_cli/skills/observal-ops. 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 Observal Ops?

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 Observal Ops?

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

Is the Observal Ops AI skill free?

Yes. It is published on GitHub by Observal 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Observing Observal

Execution contract

Choose the workflow

Analysis rules

Completion

Bundled files

Frequently asked questions

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