Agent skill

Taskuary Setup

by ldbumble in ldbumble/taskuary

Walk the owner through setting Taskuary up - the AI brain, where work arrives, the operator documents, reports and workflows - by reading the install's real state and using the screens that already…

MITAuto-check passedProductivity & Automation

Install Taskuary Setup

skills CLI
$ npx skills add ldbumble/taskuary --skill taskuary-setup -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install ldbumble/taskuary taskuary-setup --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/ldbumble/taskuary.git skills-src && mkdir -p .claude/skills && cp -r skills-src/taskuary/skills/taskuary-setup .claude/skills/taskuary-setup && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
taskuary-setup
GitHub stars
137
Token cost
~1.5k tokens
SKILL.md length
918 words
Files
1
Skills in repo
2
Repo updated
First seen
Licence
MIT

At a glance

Walk the owner through setting Taskuary up - the AI brain, where work arrives, the operator documents, reports and workflows - by reading the install's real state and using the screens that already…

  • Works in 4 steps: The owner's name (owner). It signs every… → One AI (ai). Either an AI coding CLI… → One work source (inbound). A mailbox,… → …
  • A task was opened as a Taskuary setup walkthrough
  • SKILL.md covers Read the real state before you…, Prerequisites, in order, Each area has its own road;… and Secrets never pass through…, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Taskuary Setup is an agent skill from ldbumble/taskuary. Walk the owner through setting Taskuary up - the AI brain, where work arrives, the operator documents, reports and workflows - by reading the install's real state and using the screens that already exist. Use when a task was opened as a Taskuary setup walkthrough.

Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Productivity & Automation, covering Task management. It works with Model Context Protocol, FastAPI, React and Python. The repository describes itself as: Your work, already underway. A personal AI assistant for your job: mail, chats and tickets become tasks, the agents you already use (Claude Code, Codex, Gemini) do the work, and… The licence is MIT.

When your agent uses it

  • A task was opened as a Taskuary setup walkthrough
  • Tasks that involve Task management

Example prompts

  • “/taskuary-setup”

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. The owner's name (owner). It signs every reply and fills {{owner}} in the operator
  2. One AI (ai). Either an AI coding CLI installed and signed in on this machine
  3. One work source (inbound). A mailbox, chat, or issue tracker enabled as an input, with
  4. The first result (sync). Press Read first items to start a real read, wait for its

What it can do on your machine

Read from SKILL.md and the folder at commit 439e457. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Taskuary Setup loads about 1.5k tokens when it runs. Until then it costs about 70 tokens; SKILL.md has 918 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~70
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from ldbumble/taskuary at commit 439e457, republished under its MIT licence (© ldbumble). 918 words, ~1,460 tokens.

Download SKILL.mdSave it as .claude/skills/taskuary-setup/SKILL.md (or your agent's skills folder).
name
taskuary-setup
description
Walk the owner through setting Taskuary up - the AI brain, where work arrives, the operator documents, reports and workflows - by reading the install's real state and using the screens that already exist. Use when a task was opened as a Taskuary setup walkthrough.

Taskuary setup walkthrough

You are walking one person through configuring THIS install, in conversation. You are not a wizard and you are not building anything: every piece of configuration already has a screen, and your job is to read what is true now, explain the choice in their terms, and take them to the control that makes it.

Read the real state before you say anything

GET /api/setup returns the whole model: steps (each with key, title, why, done, detail, goto), plus done, total, complete and dismissed. The step keys are owner, ai, inbound, sync. Each goto is {tab, hash, label} - the tab to send them to and the position within it. first_items is a review sample of at most five processed inbound items, not a total or an import limit. pending says whether items still await triage.

Every done is computed from real state, never from anything anyone said. A step un-ticks itself when the connection behind it is removed. So: read it at the start of the walk, read it again after each change, and describe readiness from what came back. Never report a step done because the conversation covered it, and never ask a question the state already answers.

GET /api/connectors lists the cards and which are active; GET /api/sources lists what is being read; the Reports screen (report sources) lists scheduled work.

Prerequisites, in order

  1. The owner's name (owner). It signs every reply and fills {{owner}} in the operator documents. The first setup step has the name and email fields; About you in Settings also does.
  2. One AI (ai). Either an AI coding CLI installed and signed in on this machine (GET /api/cli/detect detects them, and Taskuary can install and sign in to one in a pane it hosts) or an API key on a provider card. Without it nothing is triaged: the app runs and does nothing. A CLI they already pay for is the cheaper answer; say so.
  3. One work source (inbound). A mailbox, chat, or issue tracker enabled as an input, with its active source assigned to that connection. Start with one account or project. Connections screen. A tool-only card does not satisfy the step.
  4. The first result (sync). Press Read first items to start a real read, wait for its source/triage progress, then open one result to review its verdict or draft. If it fails or returns no items, explain the source error or scope and offer a retry. A successful HTTP start is not evidence that messages were fetched or processed.

All four are what complete means. Existing model defaults are enough to start; reviewing model assignments, personalising SOUL.md, generating STYLE.md and TRIAGE.md, adding other sources, coding agents, reports and the Hub are optional afterwards. They remain stops on the scripted walk (GET /api/setup/walk); never report them as outstanding first-run setup. Preserve the owner's existing model assignments, source scope and other configuration.

If a prerequisite cannot be met, say exactly what is missing and what it costs them - do not leave them in a chat with no usable AI and no explanation.

Show full SKILL.md (403 more words)Show less

Each area has its own road; use it

  • Connections - one card per system. Credentials, OAuth and sign-in all live on the card, and the card's Test button proves it before anyone waits for a schedule.
  • Reports - the composer builds a scheduled read; a workflow is the one that writes. Propose it as a configuration the owner confirms, and preview a report before it is saved where preview exists.
  • Docs - SOUL.md, STYLE.md, TRIAGE.md, COUNSEL.md. Blanking a document restores the shipped default, so nothing is ever permanently lost by trying.
  • Settings - agents and the coding CLI.

Anything consequential goes out as a proposal the owner confirms, on the shared operations road. Do not describe an action as done until the refreshed state says it is.

Secrets never pass through this chat

Never ask for, repeat, echo or store an API key, password, token or connection string in the conversation. Point at the connector card's own secure field, or its OAuth / device-code sign-in, and wait there. If the owner pastes a secret anyway, do not repeat it back, do not put it in a document or a task, and tell them to rotate it. A secret in a transcript is a leaked secret.

Verify, do not claim

  • A connection is proved by its card's Test, not by a saved form.
  • Reading is proved by the first sync putting real rows on the Timeline (sync ticks off actual messages, not a sample count).
  • A report is proved by a run - use its preview or Run now, then look at what it filed.

State readiness as the numbers: how many of the four are done, and which remain.

Resuming, and never doing it twice

Setup is resumable and areas can be revisited on their own. Before proposing anything:

  • Re-read /api/setup and the relevant list endpoint. A step whose done is true is finished - say so and move on; never rerun it, and never ask its questions again.
  • Never create a second connector for a system that already has an active card, or a second report with the same job. Amend the existing one.
  • Preserve what the owner already wrote. A personalised document (SOUL.md, STYLE.md, TRIAGE.md) is never replaced silently: generate a draft, show it, and let them confirm or keep theirs.
  • The owner can stop at any point. Leave the walk where it stands, say what remains, and make clear they can come back to this same conversation.

© ldbumble, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in taskuary/skills/taskuary-setup of ldbumble/taskuary.

Open the folder on GitHubat commit 439e457

Compare with similar skills

Taskuary Setup next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Taskuary Setup compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Taskuary Setup this skillldbumble/taskuary137—~1.5kAutomated safety check: PassMIT
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Claap Weekly RecapOthmane-Khadri/YALC-the-GTM-operating-system317—~5.4kAutomated safety check: PassMIT
Olore A2a Latestolorehq/olore104—~721Automated safety check: PassMIT
LangBot Core Developmentlangbot-app/LangBot18k—~1.4kAutomated safety check: NotesApache-2.0
Create PRbeyonders-studio/initiative171—~2.7kAutomated safety check: PassAGPL-3.0

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Questions about Taskuary Setup

What does Taskuary Setup do?

Walk the owner through setting Taskuary up - the AI brain, where work arrives, the operator documents, reports and workflows - by reading the install's real state and using the screens that already…. Taskuary Setup is an agent skill from ldbumble/taskuary. Walk the owner through setting Taskuary up - the AI brain, where work arrives, the operator documents, reports and workflows - by reading the install's real state and using the screens that already exist.

When should I use Taskuary Setup?

Taskuary Setup fits situations like: A task was opened as a Taskuary setup walkthrough; tasks that involve Task management.

How do I install Taskuary Setup in Claude Code?

Run `npx skills add ldbumble/taskuary --skill taskuary-setup -a claude-code`. Or copy the skill folder (taskuary/skills/taskuary-setup in ldbumble/taskuary) into .claude/skills/taskuary-setup in your project. Claude Code loads it when a task matches its description.

How do I install Taskuary Setup in Codex?

Run `npx skills add ldbumble/taskuary --skill taskuary-setup -a codex`. Or copy the skill folder (taskuary/skills/taskuary-setup in ldbumble/taskuary) into .agents/skills/taskuary-setup in your project. Codex loads it when a task matches its description.

Can I use Taskuary Setup in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ldbumble/taskuary --skill taskuary-setup -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/taskuary-setup, .gemini/skills/taskuary-setup, .github/skills/taskuary-setup and .opencode/skills/taskuary-setup in your project.

What does Taskuary Setup need to run?

SKILL.md names no scripts, command-line tools or credentials: Taskuary Setup is instructions for the agent only.

Does Taskuary Setup access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Taskuary Setup safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Taskuary Setup use?

Taskuary Setup is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Taskuary Setup use?

About 1.5k tokens (SKILL.md is roughly 5.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Taskuary Setup?

Skills that share tags, products or a category with Taskuary Setup: Retinue (jklthinking/retinue, 112 stars), Claap Weekly Recap (Othmane-Khadri/YALC-the-GTM-operating-system, 317 stars), Olore A2a Latest (olorehq/olore, 104 stars) and LangBot Core Development (langbot-app/LangBot, 18k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Taskuary Setup?

ldbumble (a GitHub user) maintains it in ldbumble/taskuary, which has 137 GitHub stars. The repository holds 2 skills in this directory. The repository was last updated on October 8, 2026.

Source: ldbumble/taskuary on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.