Openspec New Change

OrganizationPopular

Fission-AI

openspec-new-change

Start a new OpenSpec change using the experimental artifact workflow. Use when the user wants to create a new feature, fix, or modification with a structured step-by-step approach. Also use when the user says "openspec new change" or "opsx new".

Overview

Publisher	Fission-AI
Repository	`OpenSpec`
Skill name	`openspec-new-change`
Stars	70.8K
Forks	4.9K
Bundled files	Instructions only
License	MIT
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.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by Fission-AI on GitHub. Read the source before you install it.

Installation

Install the Openspec New Change 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/Fission-AI/OpenSpec/tree/main/skills/openspec-new-change
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/Fission-AI/OpenSpec.git /tmp/OpenSpec
mkdir -p .claude/skills
cp -r /tmp/OpenSpec/skills/openspec-new-change .claude/skills/openspec-new-change

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

Use it in TypingMind

Enable Openspec New Change 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 Openspec New Change 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 Openspec New Change 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.

Start a new change using the experimental artifact-driven approach.

Store selection: If the user names a store (a store is a standalone OpenSpec repo registered on this machine) or the work lives in one, run openspec store list --json to discover registered store ids, then pass --store <id> on the commands that read or write specs and changes (new change, status, instructions, list, show, validate, archive, doctor, context, schemas, view). Once selected, treat --store <id> as sticky for the rest of the workflow. Every unscoped example of those commands below is shorthand: before running it, append the flag. For example, run openspec status --change "<name>" --json --store "<id>", not the unscoped form shown below. Other commands do not take the flag. Hints printed by commands already carry the flag; keep it on follow-ups. Without a store, commands act on the nearest local openspec/ root.

Project check: These steps expect a project that already uses OpenSpec. Before the first step that writes anything (new change, archive, sync specs, or authoring an artifact file), confirm the project has a root: run openspec list --json (with --store <id> when a store is selected, since the store is then the root) and read root. A root object means the project is set up. "root": null means it is not - there is no openspec/ directory here, and a write such as openspec new change would create one as a side effect. The command also exits non-zero, which is that answer rather than a broken CLI, so read the JSON instead of retrying or working around it.

One "root": null is not about setup: when a status error message starts with Declared in or Invalid store declaration in and names this project's openspec/config.yaml (or config.yml), the project does use OpenSpec through a store it declares, which this machine cannot resolve (the store is not registered, or the store: line is malformed). Do not treat it as uninitialized and skip the branches below: stop before writing and show the user that error's message and fix.

Otherwise, with no root, what happens next depends on how this workflow was reached:

Auto-selected: you chose this workflow yourself, without the user naming OpenSpec, naming this skill, or running its slash command. Stop using OpenSpec and answer the request normally, as you would with no OpenSpec installed. Do not ask them to set anything up and do not mention OpenSpec setup.
Explicit OpenSpec request: the user named OpenSpec, named this skill, or ran its slash command. Stop before writing and ask how to proceed: set this project up (openspec init), target a store they already have (--store <id>), or continue without OpenSpec for this request. Wait for their answer.

In both branches, never create the root as a side effect: do not run openspec init until the user asks for it, do not hand-create openspec/ files, and do not let a command create it.

Input: The user's request should include a change name (kebab-case) OR a description of what they want to build.

Steps

If no clear input provided, ask what they want to build

Ask the user (open-ended, no preset options):

"What change do you want to work on? Describe what you want to build or fix."

From their description, derive a kebab-case name (e.g., "add user authentication" → add-user-auth).

IMPORTANT: Do NOT proceed without understanding what the user wants to build.
Determine the workflow schema

Use the default schema (omit --schema) unless the user explicitly requests a different workflow.

Use a different schema only if the user mentions:
- A specific schema name → use --schema <name>
- "show workflows" or "what workflows" → run openspec schemas --json and let them choose
Otherwise: Omit --schema to use the default.
Create the change directory
```
bash
openspec new change "<name>"
```
Add --schema <name> only if the user requested a specific workflow. This creates a scaffolded change in the planning home resolved by the CLI.

Show the artifact status

bash
openspec status --change "<name>" --json

Use the returned planningHome, changeRoot, artifactPaths, and nextSteps instead of assuming repo-local paths.

Get instructions for the first artifact The first artifact depends on the schema (e.g., proposal for spec-driven). Check the status output to find the first artifact with status "ready".
```
bash
openspec instructions <first-artifact-id> --change "<name>"
```
This outputs the template and context for creating the first artifact.
STOP and wait for user direction

Output

After completing the steps, summarize:

Change name and location
Schema/workflow being used and its artifact sequence
Current status (0/N artifacts complete)
The template for the first artifact
Prompt: "Ready to create the first artifact? Just describe what this change is about and I'll draft it, or ask me to continue."

Guardrails

Do NOT create any artifacts yet - just show the instructions
Do NOT advance beyond showing the first artifact template
If the name is invalid (not kebab-case), ask for a valid name
If a change with that name already exists, suggest continuing that change instead
Pass --schema if using a non-default workflow

Frequently asked questions

What does the Openspec New Change AI skill do?

Why use Openspec New Change on TypingMind?

Because you install it once and use it with any model. Openspec New Change 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 Openspec New Change in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Fission-AI/OpenSpec/tree/main/skills/openspec-new-change. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Openspec New Change?

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 Openspec New Change?

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

Is the Openspec New Change AI skill free?

Yes. It is published on GitHub by Fission-AI 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

Frequently asked questions

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