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Openspec Verify Change

CommunityPopular
Draculabo
openspec-verify-change

Verify implementation matches change artifacts. Use when the user wants to validate that implementation is complete, correct, and coherent before archiving.

Overview

PublisherDraculabo
RepositoryAntigravityManager
Skill nameopenspec-verify-change
Stars
2.4K
Forks
285
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 Draculabo on GitHub. Read the source before you install it.

Installation

Install the Openspec Verify 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.
    https://github.com/Draculabo/AntigravityManager/tree/main/.agent/skills/openspec-verify-change
  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/Draculabo/AntigravityManager.git /tmp/AntigravityManager
mkdir -p .claude/skills
cp -r /tmp/AntigravityManager/.agent/skills/openspec-verify-change .claude/skills/openspec-verify-change
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Openspec Verify 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 Verify 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 Verify 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.

Verify that an implementation matches the change artifacts (specs, tasks, design).

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. Use the AskUserQuestion tool to let the user select.

    Show changes that have implementation tasks (tasks artifact exists). Include the schema used for each change if available. Mark changes with incomplete tasks as "(In Progress)".

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

  2. Check status to understand the schema

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

    Parse the JSON to understand:

    • schemaName: The workflow being used (e.g., "spec-driven")
    • Which artifacts exist for this change
  3. Get the change directory and load artifacts

    bash
    openspec instructions apply --change "<name>" --json

    This returns the change directory and context files. Read all available artifacts from contextFiles.

  4. Initialize verification report structure

    Create a report structure with three dimensions:

    • Completeness: Track tasks and spec coverage
    • Correctness: Track requirement implementation and scenario coverage
    • Coherence: Track design adherence and pattern consistency

    Each dimension can have CRITICAL, WARNING, or SUGGESTION issues.

  5. Verify Completeness

    Task Completion:

    • If tasks.md exists in contextFiles, read it
    • Parse checkboxes: - [ ] (incomplete) vs - [x] (complete)
    • Count complete vs total tasks
    • If incomplete tasks exist:
      • Add CRITICAL issue for each incomplete task
      • Recommendation: "Complete task: " or "Mark as done if already implemented"

    Spec Coverage:

    • If delta specs exist in openspec/changes/<name>/specs/:
      • Extract all requirements (marked with "### Requirement:")
      • For each requirement:
        • Search codebase for keywords related to the requirement
        • Assess if implementation likely exists
      • If requirements appear unimplemented:
        • Add CRITICAL issue: "Requirement not found: "
        • Recommendation: "Implement requirement X: "
  6. Verify Correctness

    Requirement Implementation Mapping:

    • For each requirement from delta specs:
      • Search codebase for implementation evidence
      • If found, note file paths and line ranges
      • Assess if implementation matches requirement intent
      • If divergence detected:
        • Add WARNING: "Implementation may diverge from spec: "
        • Recommendation: "Review : against requirement X"

    Scenario Coverage:

    • For each scenario in delta specs (marked with "#### Scenario:"):
      • Check if conditions are handled in code
      • Check if tests exist covering the scenario
      • If scenario appears uncovered:
        • Add WARNING: "Scenario not covered: "
        • Recommendation: "Add test or implementation for scenario: "
  7. Verify Coherence

    Design Adherence:

    • If design.md exists in contextFiles:
      • Extract key decisions (look for sections like "Decision:", "Approach:", "Architecture:")
      • Verify implementation follows those decisions
      • If contradiction detected:
        • Add WARNING: "Design decision not followed: "
        • Recommendation: "Update implementation or revise design.md to match reality"
    • If no design.md: Skip design adherence check, note "No design.md to verify against"

    Code Pattern Consistency:

    • Review new code for consistency with project patterns
    • Check file naming, directory structure, coding style
    • If significant deviations found:
      • Add SUGGESTION: "Code pattern deviation: "
      • Recommendation: "Consider following project pattern: "
  8. Generate Verification Report

    Summary Scorecard:

    ## Verification Report: <change-name>
    
    ### Summary
    | Dimension    | Status           |
    |--------------|------------------|
    | Completeness | X/Y tasks, N reqs|
    | Correctness  | M/N reqs covered |
    | Coherence    | Followed/Issues  |

    Issues by Priority:

    1. CRITICAL (Must fix before archive):

      • Incomplete tasks
      • Missing requirement implementations
      • Each with specific, actionable recommendation
    2. WARNING (Should fix):

      • Spec/design divergences
      • Missing scenario coverage
      • Each with specific recommendation
    3. SUGGESTION (Nice to fix):

      • Pattern inconsistencies
      • Minor improvements
      • Each with specific recommendation

    Final Assessment:

    • If CRITICAL issues: "X critical issue(s) found. Fix before archiving."
    • If only warnings: "No critical issues. Y warning(s) to consider. Ready for archive (with noted improvements)."
    • If all clear: "All checks passed. Ready for archive."

Verification Heuristics

  • Completeness: Focus on objective checklist items (checkboxes, requirements list)
  • Correctness: Use keyword search, file path analysis, reasonable inference - don't require perfect certainty
  • Coherence: Look for glaring inconsistencies, don't nitpick style
  • False Positives: When uncertain, prefer SUGGESTION over WARNING, WARNING over CRITICAL
  • Actionability: Every issue must have a specific recommendation with file/line references where applicable

Graceful Degradation

  • If only tasks.md exists: verify task completion only, skip spec/design checks
  • If tasks + specs exist: verify completeness and correctness, skip design
  • If full artifacts: verify all three dimensions
  • Always note which checks were skipped and why

Output Format

Use clear markdown with:

  • Table for summary scorecard
  • Grouped lists for issues (CRITICAL/WARNING/SUGGESTION)
  • Code references in format: file.ts:123
  • Specific, actionable recommendations
  • No vague suggestions like "consider reviewing"

Frequently asked questions

What does the Openspec Verify Change AI skill do?

Verify implementation matches change artifacts. Use when the user wants to validate that implementation is complete, correct, and coherent before archiving.

Why use Openspec Verify Change on TypingMind?

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

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

Which AI models can use Openspec Verify 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 Verify Change?

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

Is the Openspec Verify Change AI skill free?

Yes. It is published on GitHub by Draculabo 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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