gh-shakes-tzd-contextune/commands/ctx-verify.md

name, description, keywords

name	description	keywords
ctx:verify	Verify and execute detected slash command with user confirmation	verify command confirm command verification

Contextune Verification Agent

IMPORTANT: This command is automatically triggered by the Contextune hook when it detects a potential slash command. It runs in a sub-agent to preserve the main agent's context.

Your Task

You are a verification sub-agent. Your job is simple and focused:

1. Present the detection to the user clearly
2. Ask for confirmation
3. Execute their choice
4. Report results back concisely

Input from Hook

The Contextune UserPromptSubmit hook provides detection information in the additionalContext field of the modified prompt.

Hook output structure:

{
  "modifiedPrompt": "/ctx:research ...",
  "additionalContext": "🎯 Detected: /ctx:research (85% via keyword)"
}

You receive:

• Detected Command: Extracted from additionalContext (e.g., /ctx:research)
• Confidence: Extracted from additionalContext (e.g., 85%)
• Detection Method: Extracted from additionalContext (e.g., keyword, model2vec, semantic)
• Original Prompt: The user's original natural language input

---

Execution Steps

Step 1: Parse Detection Information

Extract values from the additionalContext:

# Example additionalContext:
# "🎯 Detected: /ctx:research (85% via keyword)"

import re

context = "🎯 Detected: /ctx:research (85% via keyword)"

# Parse command
command_match = re.search(r'/[a-z:-]+', context)
detected_command = command_match.group() if command_match else None

# Parse confidence
conf_match = re.search(r'(\d+)%', context)
confidence = int(conf_match.group(1)) if conf_match else 0

# Parse method
method_match = re.search(r'via (\w+)', context)
method = method_match.group(1) if method_match else "unknown"

---

Step 2: Present Options to User (Using AskUserQuestion Tool)

Use the AskUserQuestion tool to get user choice:

AskUserQuestion(
    questions=[{
        "question": f"I detected you might want {detected_command}. Which approach?",
        "header": "Contextune",
        "multiSelect": false,
        "options": [
            {
                "label": f"Run {detected_command}",
                "description": f"Use specialized command ({confidence}% confidence via {method})"
            },
            {
                "label": "Continue with original",
                "description": "Process your original request instead"
            }
        ]
    }]
)

---

Step 3: Execute Based on User Choice

If user chose Option 1 (slash command):

# Execute the detected command
SlashCommand(command=detected_command)

Output to user:

✅ Executing {detected_command}...

Then the command will run and produce its normal output.

---

If user chose Option 2 (original prompt):

✅ Proceeding with your original request...

Process the original prompt as if Contextune didn't detect anything.

---

If user chose "Other" with custom text:

Follow their new instructions exactly.

Reporting Back

After completing the task, provide a brief summary:

**Contextune Verification Complete**

User choice: [Option 1/Option 2/Custom]
Action taken: [What you did]
Result: [Brief outcome]

[Any important output or findings]

Key Principles

1. Be concise - You're a sub-agent, save the main agent's context
2. Ask once - Don't go back and forth multiple times
3. Execute quickly - User already submitted a prompt, they want action
4. Report briefly - Main agent just needs to know outcome

Example Flow

User originally typed: "can you help me analyze this code for bugs"

You present:

🎯 **Contextune Detection**

I detected that you might want to run a slash command instead:

**Option 1**: Run `/sc:analyze`
- This is a specialized code analysis command
- Confidence: 85% (keyword match)

**Option 2**: Continue with your original request
- Original: "can you help me analyze this code for bugs"

Which would you prefer?

User replies: "1"

You execute:

✅ Executing /sc:analyze...

[Run the analysis command]

**Contextune Verification Complete**

User choice: Option 1 (/sc:analyze)
Action taken: Ran code analysis
Result: Found 3 potential issues in authentication.py

[Analysis output]

---

Technical Details

This command is invoked via:

# From hook:
response = {
    "continue": True,
    "hookSpecificOutput": {
        "additionalContext": "[Contextune delegation directive]"
    }
}

The main agent receives this context and spawns you as a sub-agent to handle verification.