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Openspec Bulk Archive Change

OrganizationPopular
rpamis
openspec-bulk-archive-change

Archive multiple completed changes at once. Use when archiving several parallel changes.

Overview

Publisherrpamis
Repositorycomet
Skill nameopenspec-bulk-archive-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 Bulk Archive 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-bulk-archive-change .claude/skills/openspec-bulk-archive-change
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Openspec Bulk Archive 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 Bulk Archive 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 Bulk Archive 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.

Archive multiple completed changes in a single operation.

This skill allows you to batch-archive changes, handling spec conflicts intelligently by checking the codebase to determine what's actually implemented.

Input: None required (prompts for selection)

Steps

  1. Get active changes

    Run openspec list --json to get all active changes.

    If no active changes exist, inform user and stop.

  2. Prompt for change selection

    Use AskUserQuestion tool with multi-select to let user choose changes:

    • Show each change with its schema
    • Include an option for "All changes"
    • Allow any number of selections (1+ works, 2+ is the typical use case)

    IMPORTANT: Do NOT auto-select. Always let the user choose.

  3. Batch validation - gather status for all selected changes

    For each selected change, collect:

    a. Artifact status - Run openspec status --change "<name>" --json

    • Parse schemaName and artifacts list
    • Note which artifacts are done vs other states

    b. Task completion - Read openspec/changes/<name>/tasks.md

    • Count - [ ] (incomplete) vs - [x] (complete)
    • If no tasks file exists, note as "No tasks"

    c. Delta specs - Check openspec/changes/<name>/specs/ directory

    • List which capability specs exist
    • For each, extract requirement names (lines matching ### Requirement: <name>)
  4. Detect spec conflicts

    Build a map of capability -> [changes that touch it]:

    auth -> [change-a, change-b]  <- CONFLICT (2+ changes)
    api  -> [change-c]            <- OK (only 1 change)

    A conflict exists when 2+ selected changes have delta specs for the same capability.

  5. Resolve conflicts agentically

    For each conflict, investigate the codebase:

    a. Read the delta specs from each conflicting change to understand what each claims to add/modify

    b. Search the codebase for implementation evidence:

    • Look for code implementing requirements from each delta spec
    • Check for related files, functions, or tests

    c. Determine resolution:

    • If only one change is actually implemented -> sync that one's specs
    • If both implemented -> apply in chronological order (older first, newer overwrites)
    • If neither implemented -> skip spec sync, warn user

    d. Record resolution for each conflict:

    • Which change's specs to apply
    • In what order (if both)
    • Rationale (what was found in codebase)
  6. Show consolidated status table

    Display a table summarizing all changes:

    | Change              | Artifacts | Tasks | Specs   | Conflicts | Status |
    |---------------------|-----------|-------|---------|-----------|--------|
    | schema-management   | Done      | 5/5   | 2 delta | None      | Ready  |
    | project-config      | Done      | 3/3   | 1 delta | None      | Ready  |
    | add-oauth           | Done      | 4/4   | 1 delta | auth (!)  | Ready* |
    | add-verify-skill    | 1 left    | 2/5   | None    | None      | Warn   |

    For conflicts, show the resolution:

    * Conflict resolution:
      - auth spec: Will apply add-oauth then add-jwt (both implemented, chronological order)

    For incomplete changes, show warnings:

    Warnings:
    - add-verify-skill: 1 incomplete artifact, 3 incomplete tasks
  7. Confirm batch operation

    Use AskUserQuestion tool with a single confirmation:

    • "Archive N changes?" with options based on status
    • Options might include:
      • "Archive all N changes"
      • "Archive only N ready changes (skip incomplete)"
      • "Cancel"

    If there are incomplete changes, make clear they'll be archived with warnings.

  8. Execute archive for each confirmed change

    Process changes in the determined order (respecting conflict resolution):

    a. Sync specs if delta specs exist:

    • Use the openspec-sync-specs approach (agent-driven intelligent merge)
    • For conflicts, apply in resolved order
    • Track if sync was done

    b. Perform the archive:

    bash
    mkdir -p openspec/changes/archive
    mv openspec/changes/<name> openspec/changes/archive/YYYY-MM-DD-<name>

    c. Track outcome for each change:

    • Success: archived successfully
    • Failed: error during archive (record error)
    • Skipped: user chose not to archive (if applicable)
  9. Display summary

    Show final results:

    ## Bulk Archive Complete
    
    Archived 3 changes:
    - schema-management-cli -> archive/2026-01-19-schema-management-cli/
    - project-config -> archive/2026-01-19-project-config/
    - add-oauth -> archive/2026-01-19-add-oauth/
    
    Skipped 1 change:
    - add-verify-skill (user chose not to archive incomplete)
    
    Spec sync summary:
    - 4 delta specs synced to main specs
    - 1 conflict resolved (auth: applied both in chronological order)

    If any failures:

    Failed 1 change:
    - some-change: Archive directory already exists

Conflict Resolution Examples

Example 1: Only one implemented

Conflict: specs/auth/spec.md touched by [add-oauth, add-jwt]

Checking add-oauth:
- Delta adds "OAuth Provider Integration" requirement
- Searching codebase... found src/auth/oauth.ts implementing OAuth flow

Checking add-jwt:
- Delta adds "JWT Token Handling" requirement
- Searching codebase... no JWT implementation found

Resolution: Only add-oauth is implemented. Will sync add-oauth specs only.

Example 2: Both implemented

Conflict: specs/api/spec.md touched by [add-rest-api, add-graphql]

Checking add-rest-api (created 2026-01-10):
- Delta adds "REST Endpoints" requirement
- Searching codebase... found src/api/rest.ts

Checking add-graphql (created 2026-01-15):
- Delta adds "GraphQL Schema" requirement
- Searching codebase... found src/api/graphql.ts

Resolution: Both implemented. Will apply add-rest-api specs first,
then add-graphql specs (chronological order, newer takes precedence).

Output On Success

## Bulk Archive Complete

Archived N changes:
- <change-1> -> archive/YYYY-MM-DD-<change-1>/
- <change-2> -> archive/YYYY-MM-DD-<change-2>/

Spec sync summary:
- N delta specs synced to main specs
- No conflicts (or: M conflicts resolved)

Output On Partial Success

## Bulk Archive Complete (partial)

Archived N changes:
- <change-1> -> archive/YYYY-MM-DD-<change-1>/

Skipped M changes:
- <change-2> (user chose not to archive incomplete)

Failed K changes:
- <change-3>: Archive directory already exists

Output When No Changes

## No Changes to Archive

No active changes found. Create a new change to get started.

Guardrails

  • Allow any number of changes (1+ is fine, 2+ is the typical use case)
  • Always prompt for selection, never auto-select
  • Detect spec conflicts early and resolve by checking codebase
  • When both changes are implemented, apply specs in chronological order
  • Skip spec sync only when implementation is missing (warn user)
  • Show clear per-change status before confirming
  • Use single confirmation for entire batch
  • Track and report all outcomes (success/skip/fail)
  • Preserve .openspec.yaml when moving to archive
  • Archive directory target uses current date: YYYY-MM-DD-
  • If archive target exists, fail that change but continue with others

Frequently asked questions

What does the Openspec Bulk Archive Change AI skill do?

Archive multiple completed changes at once. Use when archiving several parallel changes.

Why use Openspec Bulk Archive Change on TypingMind?

Because you install it once and use it with any model. Openspec Bulk Archive 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 Bulk Archive 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-bulk-archive-change. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Openspec Bulk Archive 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 Bulk Archive Change?

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

Is the Openspec Bulk Archive 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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