Twg Operational Health logo

Twg Operational Health

Organization
zenobi-us
twg-operational-health

Use with the root `twg` skill for on-call handoffs, incident response and investigation, post-incident reviews, reliability reviews, Assets refresh, capacity views, meeting summaries, and operational risk readouts.

Overview

Publisherzenobi-us
Repositorydotfiles
Skill nametwg-operational-health
Stars
67
Forks
6
Bundled files
4
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.

  • 4 bundled files

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

  • Open source

    Published by zenobi-us on GitHub. Read the source before you install it.

Installation

Install the Twg Operational Health 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/zenobi-us/dotfiles.git /tmp/dotfiles
mkdir -p .claude/skills
cp -r /tmp/dotfiles/files/devtools/agent/bundles/developer/skills/atlassian/twg-operational-health .claude/skills/twg-operational-health
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Twg Operational Health 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 Twg Operational Health 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 Twg Operational Health 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.

twg-operational-health

Use together with the root twg skill. Exact command grammar comes from live twg help or twg help describe <path>.

CLI launcher fallback

Run twg <command>. On shell command not found, use $HOME/.local/bin/twg (macOS/Linux) / $env:LOCALAPPDATA\Programs\twg\bin\twg.exe (PowerShell), then tell user to add that directory to PATH. Do not treat auth or command errors as PATH failures.

Use When

  • "I'm taking over on-call"
  • "Reliability, incident, SEV, or post-incident review readout"
  • "Investigate an active incident and find mitigation"
  • "Analyze root cause or draft postmortem/PIR learning/action items"
  • "Open risks, blockers, overloaded people, operational health"

First Move

Resolve scope, window, anchors, owner/escalation path, status, recency, and follow-ups. Find the operational anchor before joining relevant surfaces. Run without --site; TWG inherits the user's pinned Jira/JSM site. Only add a site override when the user explicitly requests another tenant. Never assume a vendor-internal incident site.

Evidence Policy

  • Rank by impact, urgency, owner clarity, recurrence risk, and actionability; separate live risks from historical mentions.
  • Cluster compact incident, PIR, follow-up, runbook, owner, asset, or meeting evidence by service, theme, owner, and recency. Hydrate highest-risk clusters; stop once theme, owner signal, and confidence are clear.
  • Separate working theory, confirmed problem, mitigation, and root cause. Require a causal mechanism for confirmed root cause; a closed record is insufficient. Mark claims confirmed, supported, candidate, or missing evidence; use references for RCA details.
  • After one correction of a repeated backend, auth, or schema error, report the gap and use remaining evidence instead of nearby aliases or broad inventories.

Recipe Cards

Leadership Reliability Review / On-Call Handoff

Load references/reliability-review.md. Resolve leader, platform, and window; cluster supported themes, separate cause from mitigation, connect prevention work, and rank leadership actions. For handoffs, add a first-hour checklist and escalation map.

Incident Investigation / Mitigation

Use when the incident is active, newly mitigated, or pre-PIR. Anchor on the incident record, then pull responders, symptoms, impact, recent deploys/flags/config, topology, alert/log/metric pointers, ownership, runbooks, and similar incidents. If ticket fields are sparse, probe the four golden-signal families with bounded follow-ups. See references/incident-investigation.md. Output a four-signal matrix, hypotheses, confidence, next checks, and mitigation options; never call a mitigation the root cause without the causal mechanism.

Post-Incident Root Cause / Learning

Use after mitigation/recovery when drafting or evaluating a postmortem/PIR. Pair the incident with the PIR, linked docs, final comms, remediation PRs, and action items; cover confirmed mitigation, causal mechanism, 5-why chain, and detection/response gaps. See references/pir-root-cause.md. Output root cause, contributing factors, mitigation-versus-cause, and prioritized actions.

Assets / Asset Refresh

Build contributors from project/goal/Jira/PR/doc/activity evidence. Inspect Assets schema/type metadata before AQL; join people via discovered user-like attributes such as Calculated user. Rank by contribution centrality plus asset risk, and report confidence and gaps. See references/assets.md.

Capacity / Staffing / Meetings

For staffing, resolve project/topic/org and identify people by related work, ownership, review influence, docs, and project/goal involvement; check load before recommending. For meetings, query scoped recordings, preview transcripts first, fetch full transcripts only for central ones, then summarize decisions, action items, and gaps.

Output Shape

  • Lead with severity, urgency, or recommendation, then owner, status, recency, impact, confidence, and evidence.
  • For active investigations, add a four-signal evidence matrix and an incident-to-learning timeline with confirmed problem, mitigation, root-cause status, and prevention action.
  • Group patterns across artifacts, give ranked next actions with a suggested owner, and call out data gaps (missing transcripts, no asset match, stale update, ACL/auth gaps, weak ownership).

Anti-Patterns

  • Do not fetch every transcript or page body, or treat every incident mention as a live risk.
  • Do not wait for chat/comments to label RCA before surfacing directional hypotheses for pre-PIR investigation.
  • Do not call mitigation root cause without an established mechanism. Do not treat workflow panels, bot comments, or opaque fields as RCA narrative.
  • Do not use keyword matches alone as org ownership — cross-check assignee, service owner, PIR participants, or org-tree membership.
  • Do not join Assets by display-name guesses before inspecting schema/type fields, or recommend staffing from activity counts alone.

References

  • references/assets.md - schema-first Assets queries and person/device joins
  • references/reliability-review.md - bounded incident/PIR leadership review
  • references/incident-investigation.md - active investigation and mitigation
  • references/pir-root-cause.md - post-mitigation root-cause and PIR workflow

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 Twg Operational Health AI skill do?

Use with the root `twg` skill for on-call handoffs, incident response and investigation, post-incident reviews, reliability reviews, Assets refresh, capacity views, meeting summaries, and operational risk readouts.

Why use Twg Operational Health on TypingMind?

Because you install it once and use it with any model. Twg Operational Health 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 Twg Operational Health in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zenobi-us/dotfiles/tree/master/files/devtools/agent/bundles/developer/skills/atlassian/twg-operational-health. 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 Twg Operational Health?

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 Twg Operational Health?

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

Is the Twg Operational Health AI skill free?

Yes. It is published on GitHub by zenobi-us 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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