Twg Engineering Work logo

Twg Engineering Work

Organization
zenobi-us
twg-engineering-work

Use with root `twg` for code search, repositories using an API/package, implementation and reverse-dependency discovery, PR status and reviews, repo contributors, hot areas, and issue-to-PR lookups.

Overview

Publisherzenobi-us
Repositorydotfiles
Skill nametwg-engineering-work
Stars
67
Forks
6
Bundled files
2
LicenseMIT
Links
Skill sourceRepository
  • 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 zenobi-us on GitHub. Read the source before you install it.

Installation

Install the Twg Engineering Work 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-engineering-work .claude/skills/twg-engineering-work
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Twg Engineering Work 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 Engineering Work 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 Engineering Work 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-engineering-work

Use together with the root twg skill. Exact command grammar must come from live twg help, twg help <terms>, 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

  • "Which PRs are waiting for my review?"
  • "Where is this API implemented or used?"
  • "Which repositories directly depend on this package?"
  • "Latest PRs for this issue"
  • "Who contributed most to this repo/topic?"
  • "Repos I created PRs in"
  • "Stale reviews"
  • "Review flow or bottlenecks"
  • "PR-only status for a user, team, or repo"
  • "PR status for Alice" or "this person's PRs"
  • "My PRs this week"
  • "Summarize my pull requests for a time window"
  • "Open bugs/tasks with PRs in flight"

First Move

Resolve the engineering anchor:

  • Repo prompt: identify workspace and repo from URL, local checkout, or repo query.
  • PR prompt: resolve exact PR URL, ID, workspace, and repo.
  • Workitem prompt: fetch/context the Jira workitem to discover linked PRs, commits, branches, and repos.
  • Topic prompt: resolve/search once, then find linked repos, PRs, and workitems.
  • Code prompt: search the concrete package, API, symbol, or behavior, then inspect only the source locations needed to verify the requested relationship.

Use matching typed pull-request, Bitbucket, Jira, context, and search commands. Provider-native PR commands apply only to their host; Bitbucket activity/comment/task commands never apply to GitHub PRs. Use focused help for uncertain routes/contracts.

Route Selection

  • For queues, query candidate PRs first, then hydrate selected PRs needing action.
  • For stale reviews, group by repo, author, reviewer, and stage before fetching detailed comments or diffs.
  • For issue-to-PR lookup, use workitem context before broad PR text search.
  • For repo contributors and hot areas, combine PR/commit/file-area signals with ownership and review evidence.
  • For PR leadership/team/org rollups, use twg-status-rollups; this skill supplements PR details.
  • For person/repo status, collect merged/open PRs for relevant people, repos, and window.
  • Code: load references/code-search.md.
  • For person-scoped summaries with Jira, docs, meetings, planning, or notifications, use twg-status-rollups plus ../twg-status-rollups/references/personal-work-summary.md; this skill owns PR-only work.

Evidence Policy

  • Hydrate PR details, comments, tasks, pipeline status, and diff only for stale, blocked, central, or high-impact PRs.
  • For PR rollups, stop after the evidence set identifies the main themes, repos/services, owners, and recency. Do not keep searching for more PRs when the next batch would only add more examples of the same theme.
  • For review status, include age, requested reviewers, comments/tasks, approval state, CI/check or pipeline state, and last activity when the provider surface exposes them.
  • For repo/team reports, group by repo, service, or workstream rather than only person counts.
  • Inspect PR titles/descriptions and linked issues to infer themes; do not rank solely by PR count.
  • Keep Bitbucket, GitHub connector/tool, and Atlassian auth failures separate.
  • If PR graph or repo-wide query calls repeatedly fail, make one narrower fallback using known repos, people, workitems, or search anchors. If that also fails, answer from the successful evidence and call out the PR coverage gap.

Recipe Cards

Review Queue

Query reviewer-scoped open PRs. Sort by waiting time, requested action, unresolved tasks/comments, failing CI, and project relevance. Hydrate only PRs that need action.

Stale Reviews / Review Bottlenecks

Find PRs open or waiting beyond the threshold. Group by repo, author, reviewer, and stage. Identify bottleneck patterns such as missing reviewer, unresolved tasks, failing CI, repeated request-changes, or owner unavailable.

Issue PRs

Use workitem context to find linked PRs, commits, branches, and repos. Fetch PRs only if the user asks for details, status, or next action.

Repo Contributors / Hot Areas

Query PRs/commits for the repo and time window. Group by files/areas, authors, reviewers, and themes. For hot areas, prioritize changed area plus frequency and ownership signals.

PR-Based Status Rollup

Resolve org/team first, then collect PRs for members or repos in the time window. Group into themes and repos/services. Call out gaps where PR-only evidence omits Jira, docs, planning, or customer context. For a single person where the prompt is broader than PRs, switch to twg-status-rollups and load ../twg-status-rollups/references/personal-work-summary.md.

Output Shape

For queues, include PR, repo, owner, state, reason, next action, and evidence. For engineering reports, summarize workstreams, contributors, bottlenecks, risks, and gaps. Include stable URLs or IDs for key artifacts.

Anti-Patterns

  • Do not guess Bitbucket workspace or repo.
  • Do not fetch every PR body, diff, or comment in a large queue.
  • Do not treat PR counts as impact.
  • Do not mix Bitbucket, GitHub connector/tool, and Atlassian auth failures.

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 Engineering Work AI skill do?

Use with root `twg` for code search, repositories using an API/package, implementation and reverse-dependency discovery, PR status and reviews, repo contributors, hot areas, and issue-to-PR lookups.

Why use Twg Engineering Work on TypingMind?

Because you install it once and use it with any model. Twg Engineering Work 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 Engineering Work 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-engineering-work. 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 Engineering Work?

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 Engineering Work?

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

Is the Twg Engineering Work 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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