Plan Ledger Tasks Yylo

Community

Dianel555

plan-ledger-tasks-yylo

Create a concise Product Development Requirement and one or more implementation-sized YYLO Ledger tasks when the user explicitly asks to plan or register work.

Overview

Publisher	Dianel555
Repository	`DSkills`
Skill name	`plan-ledger-tasks-yylo`
Stars	65
Forks	8
Bundled files	Instructions only
License	MIT
Links	Skill source Repository

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 Dianel555 on GitHub. Read the source before you install it.

Installation

Install the Plan Ledger Tasks Yylo 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.
https://github.com/Dianel555/DSkills/tree/main/skills/plan-ledger-tasks-yylo
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/Dianel555/DSkills.git /tmp/DSkills
mkdir -p .claude/skills
cp -r /tmp/DSkills/skills/plan-ledger-tasks-yylo .claude/skills/plan-ledger-tasks-yylo

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

Use it in TypingMind

Enable Plan Ledger Tasks Yylo 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 Plan Ledger Tasks Yylo 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 Plan Ledger Tasks Yylo 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.

Plan Kanban work

Read the project instructions and relevant product code from the integration or feature worktree. Read existing task/spec metadata through the canonical controller; do not assume .juno_task/plan.md exists.
Produce one concise PDR covering the goal, current behavior, scope, exclusions, risks, dependencies, acceptance criteria, and focused tests. Draft it in a fresh external file; do not place it in the product tree or a task body.
Preflight yy ledger --help and yy ledger artifact --help. Capture the PDR as a local immutable report Artifact Record with task/request provenance, then verify its ID, digest, size, retention, retrieval, and history. If the artifact API is unavailable, stop with the external draft intact and request an upgrade; never fall back to product docs/, task bodies/responses, new .juno_task/specs, or direct store edits.
Split only when pieces can be implemented and validated independently. Concurrent tasks must have explicit path ownership and dependencies.
Create tasks through routed yy ledger commands. Put concise durable requirements and acceptance criteria in each task body, record the PDR artifact ID in supported task fields/provenance, and relate follow-ups instead of reopening archived IDs.
Product documentation is only documentation shipped with the product. Never create controller-private tasks, ledger, state, artifacts, objects, specs, or receipts inside a product or feature worktree.
Do not start implementation, create worktrees, push, deploy, or mutate production unless the user separately asks.

Use --id, not legacy --ID, for Kanban mutations. Return the task IDs and a short dependency/order summary.

Retrieve the PDR by ID

Preflight yy ledger get --help; use yy ledger get RECORD_ID -f json to read back a known PDR without guessing its storage type. If installed get is task-only, use yy ledger record get RECORD_ID -f json after checking native help; stop for an upgrade if unavailable. New PDRs remain artifact/report (artifact_ IDs on supporting runtimes); historical document/pdr remains readable. Existing IDs remain unchanged: do not invent pdr_ or rewrite stored references.

Unknown IDs require bounded record search --projection summary --limit 20, not trial-and-error typed gets. Exact reads include hot/archive in the selected project; cold discovery needs explicit scope. Metadata/history alone is not byte round-trip proof. Verify included text or explicitly retrieve local/inline bytes with --content --max-content-bytes N (64 KiB default, 16 MiB maximum). Check exit status and digest/size; never download external payloads implicitly. If exact-byte retrieval is unavailable, retain the draft and request a compatible runtime.

User-facing Record results

After creation, update, discovery, or handoff, report the Record kind/profile, actual immutable Record ID, and actual Ledger slug from the returned Record or a native get readback. Never invent a slug from the title or confuse it with the ID. If the selected API omits a field, say it is unavailable rather than fabricate it. IDs remain authoritative for relations and lifecycle operations; slugs aid discovery.

$ARGUMENTS

Frequently asked questions

What does the Plan Ledger Tasks Yylo AI skill do?

Create a concise Product Development Requirement and one or more implementation-sized YYLO Ledger tasks when the user explicitly asks to plan or register work.

Why use Plan Ledger Tasks Yylo on TypingMind?

Because you install it once and use it with any model. Plan Ledger Tasks Yylo 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 Plan Ledger Tasks Yylo in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Dianel555/DSkills/tree/main/skills/plan-ledger-tasks-yylo. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Plan Ledger Tasks Yylo?

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 Plan Ledger Tasks Yylo?

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

Is the Plan Ledger Tasks Yylo AI skill free?

Yes. It is published on GitHub by Dianel555 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Plan Kanban work

Retrieve the PDR by ID

User-facing Record results

Frequently asked questions

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