skills/implement/SKILL.md
Use when you need quick code implementation for features, bug fixes, or utilities.
npx skillsauth add seokan-jeong/team-shinchan team-shinchan:implementInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
If args is empty or only whitespace:
Ask user: "What would you like me to implement?"
STOP and wait for user response
If args length > 2000 characters:
Truncate to 2000 characters
Warn user: "Request was truncated to 2000 characters"
Read ${CLAUDE_PLUGIN_ROOT}/agents/_shared/domain-router.json to determine the target agent.
Detection logic (apply in order):
.tsx → frontend)Routing decision:
subagent_type="team-shinchan:aichan"subagent_type="team-shinchan:buriburi"subagent_type="team-shinchan:masao"subagent_type="team-shinchan:bo" (fallback)Do not read further. Execute this Task NOW:
Task(
subagent_type="{detected_agent from Step 2}",
model="sonnet",
prompt=`/team-shinchan:implement has been invoked.
## Implementation Request
Handle coding tasks including:
| Area | Capabilities |
|------|-------------|
| Feature Implementation | New features, functions, classes |
| Bug Fixes | Debugging, error correction |
| Code Modification | Refactoring, updates, changes |
| Utilities | Helper functions, utilities |
| Tests | Unit tests, integration tests |
## Implementation Requirements
- Read existing code first to understand patterns
- Follow project conventions
- Write clean, maintainable code
- Handle errors gracefully
- Keep functions small and focused
- Add comments only for complex logic
## Post-Implementation Verification
After writing code:
1. Run existing tests if available (detect test framework from package.json/config)
2. If tests fail, fix the issues before reporting completion
3. If no tests exist, verify the code compiles/loads without errors
## Output Format
After implementation:
- Summary of changes made
- Files modified with line references
- Test results (pass/fail/skipped)
- Any follow-up recommendations
User request: ${args || '(Please describe what to implement)'}
`
)
STOP HERE. The above Task handles everything.
testing
Default-on interview option-quality panel — N diverse generators produce structure-free options, a SelfCheckGPT majority-vote consensus filters hallucinations, a SteerConf cautious-confidence judge scores survivors, and a deterministic top-K is returned. Workflow tier; the single fierce-* skill that is ON by default.
development
Deterministic adversarial code review for high-stakes scope — independent per-dimension review, a non-skippable per-finding refutation, completeness + interaction critics, and a deterministic 3-lens rubric judge panel. Opt-in main-loop Workflow tier.
data-ai
Deterministic loop-until-done for high-stakes long-running tasks — a worker/verifier loop the script bounds by iteration cap, token budget, and stagnation, closed by an Action-Kamen gate. Opt-in main-loop Workflow tier.
testing
Deterministic adversarial debate for high-stakes or irreversible decisions — mandatory refutation plus a scored judge panel. Opt-in main-loop Workflow tier.