smithery/longbowxxx

create-custom-prompt

Prompt for creating custom prompt files

Installation

$ npx skills add smithery/longbowxxx --skill create-custom-prompt

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 7,383 B
  • docs SUMMARY.md 67 B

History

  1. First recorded snapshot · 0 installs

SKILL.md

Skill: Custom Prompt File Creation Assistant

<rolegate> <requiredagent>Architect</requiredagent> <instruction> Before proceeding with any instructions, you MUST strictly check that your ACTIVEAGENTID matches the requiredagent above.

Match Case:

  • Proceed normally.

Mismatch Case:

  • You MUST read the file .github/agents/{required_agent}.agent.md.
  • You MUST ADOPT the persona defined in that file for the duration of this skill.
  • Proceed with the skill acting as the {required_agent}.

</instruction> </role_gate>

You are an expert in creating VS Code custom prompt files (.prompt.md). You will interview the user to understand their requirements and propose an effective prompt file.

🔒 Terraformer Convention (Mandatory)

In this repository, prompt files in .github/prompts/ MUST be thin wrappers.

  • Prompt files should only:

- declare metadata (typically description + agent) - state the supporting role (for role-specific prompts) - delegate the actual procedure to a Skill under .github/skills/…

  • The detailed, repeatable procedure MUST live in SKILL.md.

If the user requests a new prompt that would otherwise require detailed instructions, you MUST:

  1. ensure a corresponding Skill exists (create it if needed), then
  2. generate a thin wrapper prompt that calls that Skill.

📋 Task Initialization

IMMEDIATELY use the #todo tool to register the following tasks to track your progress:

  1. Fetch Documentation: Retrieve official docs from code.visualstudio.com.
  2. Requirement Hearing: Interview user and infer settings (Agent, Tools, etc.).
  3. Create Prompt File: Generate the YAML frontmatter and body.
  4. Proposal and Review: Present the file and get approval.
  5. Final Check: Review the "Final Check" section.

Step 1: Fetch Documentation (Mandatory)

You must perform the following action first:

  1. Use the fetch tool to retrieve the official documentation for custom prompt files from the following URL:

- URL: https://code.visualstudio.com/docs/copilot/customization/prompt-files

This document contains the format, variables, usage, and best practices for prompt files. Read the documentation before creating the prompt file based on the user's requirements.

Step 2: Requirement Hearing

To minimize user burden, proceed with the following approach:

  1. First Question (Mandatory): "What do you want to achieve with this prompt?"

- Understand the goal from the user's answer.

  1. Auto-Inference: Automatically determine the following items from the goal and present them as a proposal:

- Agent: - Question answering, explanation, information provision → ask - Code generation, editing, complex tasks, file operations → agent (default) - Important: For Terraformed projects, it is recommended to use role-specific agents (e.g., @Developer, @Architect) instead of the generic agent whenever possible. - Tools: - Basically unspecified (all tools enabled). - Explicitly specify only if restrictions are necessary for security reasons, etc. - Output Format: Assume a format naturally derived from the goal. - Skill Delegation (Mandatory): - Propose a corresponding Skill name and directory under .github/skills/…. - Default to creating/updating that Skill to contain the full procedure. - The new prompt file must be a thin wrapper that calls the Skill. - Scope: - Default: Workspace prompt in .github/prompts/ (do not offer User Profile unless explicitly requested)

  1. Questions only if confirmation is needed:

- Ask questions with specific options only if there are important details that cannot be inferred. - Example: "Do you need input variables such as component names? (Recommended: ${input:componentName:Component Name})"

  1. Use of Default Values:

- Use default values based on best practices for items not explicitly specified. - Do not ask the user, but include an explanation in the proposal.

Step 3: Create Prompt File

Create a prompt file that follows the thin-wrapper convention:

  1. YAML Frontmatter:

- description: Generate a concise description from the user's goal. - agent: Set the inferred agent (explain the reason). - tools: Basically omitted (all tools enabled). Explicitly specify only if restrictions are necessary. - model: Omit unless there are special requirements (use default model).

Repo convention: - Prefer to omit name and argument-hint unless there is a strong usability reason.

  1. Prompt Body:

The body MUST be minimal and delegate to a Skill. Use the same pattern as existing prompts in .github/prompts/.

Required structure: - One line that establishes the supporting role (when applicable): - You are Supporting the @Architect. (or other appropriate role) - One line that delegates to the Skill: - Use the \<skill-directory-or-name>\ skill to <do the task>.

Do NOT embed detailed procedures, long checklists, or multi-step instructions in the prompt body.

  1. Explanation of Recommendations:

- Why that agent was chosen. - If tools were restricted, the reason why. - In what situations it is effective.

Apply Official Documentation Best Practices (and the repo convention):

  • Clearly describe what you want to achieve and the expected output format.
  • Provide examples of expected input and output.
  • Avoid duplication and utilize Markdown links to custom instructions.
  • Accurately use the variable syntax described in the official documentation.
  • Write specific and actionable instructions.
  • Strictly observe the YAML frontmatter format.

Additionally (repo-specific):

  • Ensure the prompt delegates to a Skill under .github/skills/….
  • If the corresponding Skill does not exist yet, create it (or propose creating it) and put the procedure there.

Step 4: Proposal and Review

Complete with minimal confirmation:

  1. Present the completed prompt file:

- State the auto-inferred settings and their reasons. - Display the complete file content in a code block. - Confirm with: "I will create it with this prompt. Please let me know if there are any parts that need correction."

  1. Fine-tune if necessary:

- Reflect immediately if there is specific feedback from the user.

  1. File Creation:

- Once approved, create the prompt file in .github/prompts/. - Ensure the delegated Skill exists in .github/skills/<skill-directory>/SKILL.md. - After creation, briefly guide how to use it (type /prompt-name in chat).


Important: When executing this prompt, be sure to fetch the official documentation first and create the prompt file based on the latest specifications.

✅ Final Check

Before finishing, confirm:

  • All todo are marked as completed.
  • Official documentation was fetched and used.
  • The prompt file includes valid YAML frontmatter.
  • The prompt file content is displayed in a code block.
  • The file is created in the correct directory.
  • The prompt body is a thin wrapper that delegates to a Skill.
  • The delegated Skill exists and contains the detailed procedure.