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Openspec Continue Change

OrganizationPopular
rpamis
openspec-continue-change

Continue working on an OpenSpec change by creating the next artifact. Use when the user wants to progress their change, create the next artifact, or continue their workflow.

Overview

Publisherrpamis
Repositorycomet
Skill nameopenspec-continue-change
Stars
3.1K
Forks
295
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by rpamis on GitHub. Read the source before you install it.

Installation

Install the Openspec Continue Change 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/rpamis/comet.git /tmp/comet
mkdir -p .claude/skills
cp -r /tmp/comet/eval/local/skills/benchmarks/dependency/openspec/openspec-continue-change .claude/skills/openspec-continue-change
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Openspec Continue 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 Continue 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 Continue 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.

Continue working on a change by creating the next artifact.

Input: Optionally specify a change name. If omitted, check if it can be inferred from conversation context. If vague or ambiguous you MUST prompt for available changes.

Steps

  1. If no change name provided, prompt for selection

    Run openspec list --json to get available changes sorted by most recently modified. Then use the AskUserQuestion tool to let the user select which change to work on.

    Present the top 3-4 most recently modified changes as options, showing:

    • Change name
    • Schema (from schema field if present, otherwise "spec-driven")
    • Status (e.g., "0/5 tasks", "complete", "no tasks")
    • How recently it was modified (from lastModified field)

    Mark the most recently modified change as "(Recommended)" since it's likely what the user wants to continue.

    IMPORTANT: Do NOT guess or auto-select a change. Always let the user choose.

  2. Check current status

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

    Parse the JSON to understand current state. The response includes:

    • schemaName: The workflow schema being used (e.g., "spec-driven")
    • artifacts: Array of artifacts with their status ("done", "ready", "blocked")
    • isComplete: Boolean indicating if all artifacts are complete
  3. Act based on status:


    If all artifacts are complete (isComplete: true):

    • Congratulate the user
    • Show final status including the schema used
    • Suggest: "All artifacts created! You can now implement this change or archive it."
    • STOP

    If artifacts are ready to create (status shows artifacts with status: "ready"):

    • Pick the FIRST artifact with status: "ready" from the status output
    • Get its instructions:
      bash
      openspec instructions <artifact-id> --change "<name>" --json
    • Parse the JSON. The key fields are:
      • context: Project background (constraints for you - do NOT include in output)
      • rules: Artifact-specific rules (constraints for you - do NOT include in output)
      • template: The structure to use for your output file
      • instruction: Schema-specific guidance
      • outputPath: Where to write the artifact
      • dependencies: Completed artifacts to read for context
    • Create the artifact file:
      • Read any completed dependency files for context
      • Use template as the structure - fill in its sections
      • Apply context and rules as constraints when writing - but do NOT copy them into the file
      • Write to the output path specified in instructions
    • Show what was created and what's now unlocked
    • STOP after creating ONE artifact

    If no artifacts are ready (all blocked):

    • This shouldn't happen with a valid schema
    • Show status and suggest checking for issues
  4. After creating an artifact, show progress

    bash
    openspec status --change "<name>"

Output

After each invocation, show:

  • Which artifact was created
  • Schema workflow being used
  • Current progress (N/M complete)
  • What artifacts are now unlocked
  • Prompt: "Want to continue? Just ask me to continue or tell me what to do next."

Artifact Creation Guidelines

The artifact types and their purpose depend on the schema. Use the instruction field from the instructions output to understand what to create.

Common artifact patterns:

spec-driven schema (proposal → specs → design → tasks):

  • proposal.md: Ask user about the change if not clear. Fill in Why, What Changes, Capabilities, Impact.
    • The Capabilities section is critical - each capability listed will need a spec file.
  • specs//spec.md: Create one spec per capability listed in the proposal's Capabilities section (use the capability name, not the change name).
  • design.md: Document technical decisions, architecture, and implementation approach.
  • tasks.md: Break down implementation into checkboxed tasks.

For other schemas, follow the instruction field from the CLI output.

Guardrails

  • Create ONE artifact per invocation
  • Always read dependency artifacts before creating a new one
  • Never skip artifacts or create out of order
  • If context is unclear, ask the user before creating
  • Verify the artifact file exists after writing before marking progress
  • Use the schema's artifact sequence, don't assume specific artifact names
  • IMPORTANT: context and rules are constraints for YOU, not content for the file
    • Do NOT copy <context>, <rules>, <project_context> blocks into the artifact
    • These guide what you write, but should never appear in the output

Frequently asked questions

What does the Openspec Continue Change AI skill do?

Continue working on an OpenSpec change by creating the next artifact. Use when the user wants to progress their change, create the next artifact, or continue their workflow.

Why use Openspec Continue Change on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/rpamis/comet/tree/master/eval/local/skills/benchmarks/dependency/openspec/openspec-continue-change. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Openspec Continue 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 Continue Change?

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

Is the Openspec Continue Change AI skill free?

Yes. It is published on GitHub by rpamis 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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