dashboard-mid — for Claude Code dashboard-mid, dashboard_mid, community, for Claude Code, ide skills, README.md, scripts, Dashboard, Mirror, Canonical

v1.2.0
GitHub

이 스킬 정보

적합한 상황: Ideal for AI agents that need dashboard mid skill (mirror). 현지화된 요약: # Dashboard Mid Skill (Mirror) Canonical skill path: ./skills/dashboard-mid/SKILL.md. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

기능

Dashboard Mid Skill (Mirror)
Canonical skill path: ./skills/dashboard-mid/SKILL.md.
Fixed Workflow (Mandatory)
Read and understand the repository before editing.
Read docs/ai/README.md and src/prompts/README.md.

# Core Topics

for Claude Code README.md scripts Dashboard Mirror Canonical
ltchcmus ltchcmus
[0]
[0]
Updated: 4/20/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 8/11

This page remains useful for operators, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution
Review Score
8/11
Quality Score
34
Canonical Locale
en
Detected Body Locale
en

적합한 상황: Ideal for AI agents that need dashboard mid skill (mirror). 현지화된 요약: # Dashboard Mid Skill (Mirror) Canonical skill path: ./skills/dashboard-mid/SKILL.md. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

이 스킬을 사용하는 이유

추천 설명: dashboard-mid helps agents dashboard mid skill (mirror). Dashboard Mid Skill (Mirror) Canonical skill path: ./skills/dashboard-mid/SKILL.md. This AI agent skill supports Claude Code, Cursor, and Windsurf

최적의 용도

적합한 상황: Ideal for AI agents that need dashboard mid skill (mirror).

↓ 실행 가능한 사용 사례 for dashboard-mid

사용 사례: Applying Dashboard Mid Skill (Mirror)
사용 사례: Applying Canonical skill path: ./skills/dashboard-mid/SKILL.md
사용 사례: Applying Fixed Workflow (Mandatory)

! 보안 및 제한 사항

  • 제한 사항: src/ is source code only.
  • 제한 사항: Do not move outputs into the wrong folder.
  • 제한 사항: A task is done only when:

Why this page is reference-only

  • - Current locale does not satisfy the locale-governance contract.
  • - The underlying skill quality score is below the review floor.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

After The Review

Decide The Next Action Before You Keep Reading Repository Material

Killer-Skills should not stop at opening repository instructions. It should help you decide whether to install this skill, when to cross-check against trusted collections, and when to move into workflow rollout.

Install Path

Start With Installation And Validation

If this skill is worth continuing with, the next step is to confirm the install command, CLI write path, and environment validation.
Trusted Recheck

Cross-Check Against Trusted Picks

If you are still comparing multiple skills or vendors, go back to the trusted collection before amplifying repository noise.
Workflow

Move To Workflow Collections For Team Rollout

When the goal shifts from a single skill to team handoff, approvals, and repeatable execution, move into workflow collections.
Labs Demo

Browser Sandbox Environment

⚡️ Ready to unleash?

Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is dashboard-mid?

적합한 상황: Ideal for AI agents that need dashboard mid skill (mirror). 현지화된 요약: # Dashboard Mid Skill (Mirror) Canonical skill path: ./skills/dashboard-mid/SKILL.md. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

How do I install dashboard-mid?

Run the command: npx killer-skills add ltchcmus/dashboard_mid/dashboard-mid. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for dashboard-mid?

Key use cases include: 사용 사례: Applying Dashboard Mid Skill (Mirror), 사용 사례: Applying Canonical skill path: ./skills/dashboard-mid/SKILL.md, 사용 사례: Applying Fixed Workflow (Mandatory).

Which IDEs are compatible with dashboard-mid?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for dashboard-mid?

제한 사항: src/ is source code only.. 제한 사항: Do not move outputs into the wrong folder.. 제한 사항: A task is done only when:.

↓ How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add ltchcmus/dashboard_mid/dashboard-mid. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use dashboard-mid immediately in the current project.

! Reference-Only Mode

This page remains useful for installation and reference, but Killer-Skills no longer treats it as a primary indexable landing page. Read the review above before relying on the upstream repository instructions.

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

dashboard-mid

# Dashboard Mid Skill (Mirror) Canonical skill path: ./skills/dashboard-mid/SKILL.md. This AI agent skill supports Claude Code, Cursor, and Windsurf

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

Dashboard Mid Skill (Mirror)

Canonical skill path: ./skills/dashboard-mid/SKILL.md.

Fixed Workflow (Mandatory)

  1. Read and understand the repository before editing.
    • Read README.md.
    • Read docs/ai/README.md and src/prompts/README.md.
    • Inspect the active folder tree under .agents/, data/, docs/, scripts/, and src/.
  2. Confirm structure and ownership.
    • src/ is source code only.
    • data/outputs/slides/ is for generated slide artifacts.
    • scripts/individual/ and scripts/final/ are for speaking scripts.
  3. Implement the user request.
    • Keep modules and responsibilities separated.
    • Do not move outputs into the wrong folder.
  4. Log prompts after implementation (required).
    • Save reusable prompts or final prompts in src/prompts/.
    • Preferred file naming: src/prompts/YYYY-MM-DD-task-slug.md.
    • Minimum sections: Objective, Context, Final Prompt, Expected Output.
  5. Log AI handover notes after implementation (required).
    • Save concise implementation notes in docs/ai/.
    • Preferred file naming: docs/ai/YYYY-MM-DD-task-slug.md.
    • Minimum sections: Request Summary, Files Changed, Key Decisions, Next Steps.
  6. Verify and synchronize docs.
    • If folder structure changes, update README.md and both skill files.
    • Verify paths, commands, and runtime assumptions.

Folder Contracts

  • src/: Application source code.
  • data/raw/: Raw immutable input data.
  • data/outputs/slides/markdown/: Generated markdown slide content.
  • data/outputs/slides/pptx/: Exported PowerPoint files.
  • scripts/individual/: Per-speaker presentation scripts.
  • scripts/final/: Final merged presentation scripts.
  • docs/ai/: AI-facing notes and handover documents.
  • docs/human/: Human-facing guides and presentation materials.

Guardrails

  • Never write speaking scripts into data/outputs/.
  • Never write generated artifacts into src/.
  • Never finish a task without updating prompt logs and AI notes.

Definition of Done

A task is done only when:

  • The requested change is implemented.
  • Prompt logs are updated in src/prompts/.
  • AI notes are updated in docs/ai/.
  • Folder responsibilities remain correct.
  • Documentation matches the current repository state.

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