system-prompt-creator skillA
system-prompt-creator is agent-read markdown (skill) from tronghieu/agent-skills: Create high-quality, model-aware system prompts for any LLM (Claude, GPT, Gemini, open-source, etc.). Use this skill whenever the user wants to create, write, build, design, draft, or improve a system prompt, system instructions, or custom instructions for any AI model. Also trigger when the user asks about prompt engineering, prompt design, prompt optimization, or wants to define behavior for an AI assistant, chatbot, agent, or any LLM-powered application — even if they don't explicitly say "sy.
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.
What the file says
# System Prompt Creator Build effective system prompts for any LLM using a structured, research-backed process derived from the official prompting guides of Claude (Anthropic), GPT-5 (OpenAI), and Gemini (Google). This skill guides you through interview, analysis, structuring, drafting, and optimization — producing system prompts that are clear, well-structured, and tailored to the target model. ## Workflow Follow these 5 steps in order. Each step builds on the previous. ### Step 1: Interview — Gather Requirements Before writing anything, collect these essentials from the user: 1. **Target model** — Which LLM? (Claude, GPT, Gemini, open-source, or model-agnostic) 2. **Use case** — What will the AI do? (chatbot, agent, content generator, data extractor, code assistant, etc.) 3. **Persona** — Who should the AI be? (role, expertise level, personality traits) 4. **Audience** — Who interacts with it? (developers, end users, internal team, customers) 5. **Input types** — What will users send? (free text, code, documents, images, structured data) 6. **Output format** — What should responses look like? (prose, JSON, markdown, code, tables) …
Read the whole file at its exact version.
How to install
mdr add tronghieu/agent-skills/system-prompt-creator@git:20260326.caac78emdr add tronghieu/agent-skills/system-prompt-creator@sha256:7193f20189ce86cdPin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
[](https://markdownregistry.com/a/art_npgngg43bwuv2yoj)
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Versions
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (13064 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
tronghieu/agent-skills · 72 stars · license MIT · pushed 2026-09-22 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_npgngg43bwuv2yoj GET https://markdownregistry.com/api/v1/resolve?ref=tronghieu/agent-skills/system-prompt-creator GET https://markdownregistry.com/api/v1/blob/7193f20189ce86cdf2aa21212e1722570a67ed8c100a90bc989210236c1a4a7b
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