ck-help

name	ck-help
version	1.0.0
description	[Utilities] Use when you need claudeKit usage guide - just type naturally.
disable-model-invocation	true

Quick Summary

Goal: Provide ClaudeKit usage guidance by running the help script and presenting results based on output type.

Workflow:

1. Translate — Convert user arguments to English if needed
2. Execute — Run python .claude/scripts/ck-help.py "$ARGUMENTS"
3. Detect Type — Read @CK_OUTPUT_TYPE marker (comprehensive-docs, category-guide, command-details, search-results, task-recommendations)
4. Present — Show COMPLETE script output verbatim, then add practical context and examples

Key Rules:

• Never replace or summarize script output; always show it fully then enhance
• /plan then /code is the correct flow; NEVER suggest /plan then /cook
• /cook is standalone (has its own planning)

Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).

Think harder. All-in-one ClaudeKit guide. Run the script and present output based on type markers.

Pre-Processing

IMPORTANT: Always translate $ARGUMENTS to English before passing to script.

The Python script only understands English keywords. If $ARGUMENTS is in another language:

1. Translate $ARGUMENTS to English
2. Pass the translated English string to the script

Execution

python .claude/scripts/ck-help.py "$ARGUMENTS"

Output Type Detection

The script outputs a type marker on the first line: @CK_OUTPUT_TYPE:<type>

Read this marker and adjust your presentation accordingly:

@CK_OUTPUT_TYPE:comprehensive-docs

Full documentation (config, schema, setup guides).

Presentation:

1. Show the COMPLETE script output verbatim - every section, every code block
2. THEN ADD helpful context:
   • Real-world usage examples ("For example, if you're working on multiple projects...")
   • Common gotchas and tips ("Watch out for: ...")
   • Practical scenarios ("This is useful when...")
3. End with a specific follow-up question

Example enhancement after showing full output:

## Additional Tips

**When to use global vs local config:**
- Use global (~/.claude/.ck.json) for personal preferences like language, issue prefix style
- Use local (./.claude/.ck.json) for project-specific paths, naming conventions

**Common setup for teams:**
Each team member sets their locale globally, but projects share local config via git.

Need help setting up a specific configuration?

@CK_OUTPUT_TYPE:category-guide

Workflow guides for command categories (fix, plan, cook, etc.).

Presentation:

1. Show the complete workflow and command list
2. ADD practical context:
   • When to use this workflow vs alternatives
   • Real example: "If you encounter a bug in authentication, start with..."
   • Transition tips between commands
3. Offer to help with a specific task

@CK_OUTPUT_TYPE:command-details

Single command documentation.

Presentation:

1. Show full command info from script
2. ADD:
   • Concrete usage example with realistic input
   • When this command shines vs alternatives
   • Common flags or variations
3. Offer to run the command for them

@CK_OUTPUT_TYPE:search-results

Search matches for a keyword.

Presentation:

1. Show all matches from script
2. HELP user navigate:
   • Group by relevance if many results
   • Suggest most likely match based on context
   • Offer to explain any specific command
3. Ask what they're trying to accomplish

@CK_OUTPUT_TYPE:task-recommendations

Task-based command suggestions.

Presentation:

1. Show recommended commands from script
2. EXPLAIN the reasoning:
   • Why these commands fit the task
   • Suggested order of execution
   • What each step accomplishes
3. Offer to start with the first recommended command

Key Principle

Script output = foundation. Your additions = value-add.

Never replace or summarize the script output. Always show it fully, then enhance with your knowledge and context.

Important: Correct Workflows

• /plan → /code: Plan first, then execute the plan
• /cook: Standalone - plans internally, no separate /plan needed
• NEVER suggest /plan → /cook (cook has its own planning)

---

[IMPORTANT] Use TaskCreate to break ALL work into small tasks BEFORE starting — including tasks for each file read. This prevents context loss from long files. For simple tasks, AI MUST ATTENTION ask user whether to skip.

AI Mistake Prevention — Failure modes to avoid on every task: Check downstream references before deleting. Deleting components causes documentation and code staleness cascades. Map all referencing files before removal. Verify AI-generated content against actual code. AI hallucinates APIs, class names, and method signatures. Always grep to confirm existence before documenting or referencing. Trace full dependency chain after edits. Changing a definition misses downstream variables and consumers derived from it. Always trace the full chain. Trace ALL code paths when verifying correctness. Confirming code exists is not confirming it executes. Always trace early exits, error branches, and conditional skips — not just happy path. When debugging, ask "whose responsibility?" before fixing. Trace whether bug is in caller (wrong data) or callee (wrong handling). Fix at responsible layer — never patch symptom site. Assume existing values are intentional — ask WHY before changing. Before changing any constant, limit, flag, or pattern: read comments, check git blame, examine surrounding code. Verify ALL affected outputs, not just the first. Changes touching multiple stacks require verifying EVERY output. One green check is not all green checks. Holistic-first debugging — resist nearest-attention trap. When investigating any failure, list EVERY precondition first (config, env vars, DB names, endpoints, DI registrations, data preconditions), then verify each against evidence before forming any code-layer hypothesis. Surgical changes — apply the diff test. Bug fix: every changed line must trace directly to the bug. Don't restyle or improve adjacent code. Enhancement task: implement improvements AND announce them explicitly. Surface ambiguity before coding — don't pick silently. If request has multiple interpretations, present each with effort estimate and ask. Never assume all-records, file-based, or more complex path.

Critical Thinking Mindset — Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination.

MUST ATTENTION apply critical thinking — every claim needs traced proof, confidence >80% to act. Anti-hallucination: never present guess as fact.

MUST ATTENTION apply AI mistake prevention — holistic-first debugging, fix at responsible layer, surface ambiguity before coding, re-read files after compaction.

Closing Reminders

IMPORTANT MUST ATTENTION break work into small todo tasks using TaskCreate BEFORE starting IMPORTANT MUST ATTENTION search codebase for 3+ similar patterns before creating new code IMPORTANT MUST ATTENTION cite file:line evidence for every claim (confidence >80% to act) IMPORTANT MUST ATTENTION add a final review todo task to verify work quality

[TASK-PLANNING] Before acting, analyze task scope and systematically break it into small todo tasks and sub-tasks using TaskCreate.