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Openspec Propose

OrganizationPopular
MemeMeow-Studio
openspec-propose

Propose a new change with all artifacts generated in one step. Use when the user wants to quickly describe what they want to build and get a complete proposal with design, specs, and tasks ready for implementation.

Overview

PublisherMemeMeow-Studio
RepositoryMemeMeow
Skill nameopenspec-propose
Stars
1.3K
Forks
37
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 MemeMeow-Studio on GitHub. Read the source before you install it.

Installation

Install the Openspec Propose 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.
    https://github.com/MemeMeow-Studio/MemeMeow/tree/main/.agents/skills/openspec-propose
  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/MemeMeow-Studio/MemeMeow.git /tmp/MemeMeow
mkdir -p .claude/skills
cp -r /tmp/MemeMeow/.agents/skills/openspec-propose .claude/skills/openspec-propose
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Openspec Propose 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 Propose 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 Propose 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.

Propose a new change - create the change and generate all artifacts in one step.

Planning boundary: This workflow creates planning artifacts only. The user request that selected or triggered this workflow authorizes planning only, even if it asks to build or fix something. Do not edit project code. After the planning artifacts are complete, stop. Do not start implementation in the same response, even if the initial request asks for it. Wait for a new user request after the artifacts are presented; then start the apply workflow.

I'll create a change with the artifacts your schema defines. With the default spec-driven schema that is:

  • proposal.md (what & why)
  • specs/<capability-path>/spec.md (what the system must do - a delta, not the main spec)
  • design.md (how)
  • tasks.md (implementation steps)

<capability-path> is the spec directory relative to specs/ (for example, user-auth or identity/user-auth). Preserve an existing capability's full path and follow the project's established organization for new capabilities.

When the user is ready to implement, they must start the apply workflow explicitly.


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, 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.

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

Steps

  1. Understand the request and clarify material ambiguity

    If no clear input is provided, 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.

    If the request contains ambiguity that would materially affect scope, externally observable behavior, compatibility, or acceptance criteria, ask the user before creating the change. For minor details, make a reasonable assumption and record it in the planning artifacts.

  2. Determine the workflow schema

    Use the configured default schema unless the user explicitly requests a different workflow.

    Use a different schema only if the user:

    • Explicitly requests a specific schema by name → use --schema <schema-name>
    • Asks to "show workflows" or asks "what workflows" exist → resolve the authoritative root by running openspec context --json from the current working directory. If the user explicitly selected a registered store, use openspec context --json --store "<store-id>". Then run openspec schemas --json with its working directory set to the returned root.path and let them choose. This preserves roots selected by a local store: pointer or the global defaultStore; schemas does not accept --store. If context reports only no_openspec_root, run openspec schemas --json from the current working directory instead. Do not use this fallback for invalid or unavailable stores.

    Otherwise, omit --schema to preserve the configured default.

  3. Create the change directory

    Choose one schema form below. If a registered store is selected, append --store "<store-id>" to that command and each later OpenSpec command shown below that accepts --store.

    Using the configured default:

    bash
    openspec new change "<name>"

    Using an explicitly requested schema:

    bash
    openspec new change "<name>" --schema "<schema-name>"

    This creates a scaffolded change in the planning home resolved by the CLI with .openspec.yaml.

  4. Get the artifact build order

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

    Parse the JSON to get:

    • applyRequires: array of artifact IDs needed before implementation (e.g., ["tasks"])
    • artifacts: list of all artifacts, each with its status and its requires edges (the artifact IDs it directly depends on)
    • planningHome, changeRoot, artifactPaths, and actionContext: path and scope context. Use these instead of assuming repo-local paths.
  5. Create every artifact in the required set

    Use a todo list to track progress through the artifacts.

    Loop through artifacts in dependency order (artifacts with no pending dependencies first):

    a. For each artifact that is ready (dependencies satisfied):

    • Get instructions:
      bash
      openspec instructions <artifact-id> --change "<name>" --json
    • The instructions JSON includes:
      • 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 for this artifact type
      • skipped/warning: present when the change declares skip_specs and this artifact must NOT be created - stop and pick another artifact
      • resolvedOutputPath: Resolved path or pattern to write the artifact
      • dependencies: Completed artifacts to read for context
    • Read any completed dependency files for context - always re-read them from disk, even if you saw them earlier in the conversation (the user may have edited them)
    • If the instruction field delegates creation to a specific skill or command, invoke it to produce the artifact instead of writing the file yourself, then verify the artifact file exists at resolvedOutputPath
    • Otherwise create the artifact file using template as the structure and write it to resolvedOutputPath. If resolvedOutputPath is a glob, follow instruction to choose the concrete file path
    • Apply context and rules as constraints - but do NOT copy them into the file
    • Show brief progress: "Created "

    b. Continue until every artifact in the required set exists (not just apply.requires)

    • After creating each artifact, re-run openspec status --change "<name>" --json
    • The required set is applyRequires plus every artifact reachable from those by following the requires edges in status --json - walk them transitively (spec-driven closes over proposal, specs, design, tasks). Leave artifacts outside that set alone
    • status is file-existence only, so an applyRequires artifact reading done does NOT mean its dependencies exist - writing tasks.md early marks tasks done while specs was never written. Use each artifact's requires edges, not its status, to build the required set: a done artifact still lists what it depends on
    • An artifact already reading status: "skipped" is satisfied: the change declares skip_specs in .openspec.yaml, so its files must NOT exist. Never try to create one
    • Create every artifact in the required set that is missing, then re-check - creating one can unblock others
    • Skip one only when status already reports it skipped, or when its own instruction says it is conditional: run openspec instructions <artifact-id> --change "<name>" --json and skip only if its instruction field marks it optional (e.g. "create only if..."). Spec-driven's design.md qualifies; specs qualifies only via the skipped status above, never by your own judgment. Tell the user, and do not reconsider it
    • Dependencies are enablers, not gates: if a required artifact is still blocked only because you skipped a conditional dependency, write it anyway
    • Stop when every artifact in the required set is done, skipped, or was deliberately skipped

    c. If an artifact requires user input (unclear context):

    • Ask the user to clarify
    • Then continue with creation
  6. Show final status

    bash
    openspec status --change "<name>"

Output

After completing all artifacts, summarize:

  • Change name and location
  • List of artifacts created with brief descriptions, plus any conditional artifact you skipped and why
  • What's ready: "All artifacts needed for implementation are ready."
  • Prompt: "The artifacts are ready for review. When you are ready, run $openspec-apply-change (Codex) or /openspec-apply-change (other agents) or ask me to apply this change."

Artifact Creation Guidelines

  • Follow the instruction field from openspec instructions for each artifact type - it is the authoritative guidance, even for familiar artifact names
  • If the instruction field directs you to use a specific skill or command to create the artifact, invoke it instead of writing the artifact directly
  • The schema defines what each artifact should contain - follow it
  • Read dependency artifacts for context before creating new ones
  • Use template as the structure for your output file - fill in its sections
  • 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

Guardrails

  • The request that invoked this workflow authorizes planning only. Any implementation or apply instruction in that request does not carry forward. Do NOT implement the change, start the apply workflow, or edit project code during this workflow. After presenting the artifacts, stop and wait for a new user request to start the apply workflow
  • Create every artifact the apply phase transitively depends on, not just the ids listed in apply.requires
  • Always read dependency artifacts before creating a new one - re-read from disk, not from conversation memory (files may have changed since you last saw them)
  • Ask about ambiguities that would materially change scope, externally observable behavior, compatibility, or acceptance criteria; for minor details, make reasonable assumptions and record them
  • If a change with that name already exists, ask if user wants to continue it or create a new one
  • Verify each artifact file exists after writing before proceeding to next

Frequently asked questions

What does the Openspec Propose AI skill do?

Propose a new change with all artifacts generated in one step. Use when the user wants to quickly describe what they want to build and get a complete proposal with design, specs, and tasks ready for implementation.

Why use Openspec Propose on TypingMind?

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

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

Which AI models can use Openspec Propose?

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 Propose?

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

Is the Openspec Propose AI skill free?

Yes. It is published on GitHub by MemeMeow-Studio 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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