molyanov-ai-dev: Skill for Codex

.codex/skills/prompt-master/SKILL.md

prompt-master is a skill for Codex from pavel-molyanov/molyanov-ai-dev. It costs 49 tokens per session (944 once invoked), scanned A, original, MIT.

A guide for writing, improving, and checking instructions given to language models.

In plain words
What is it for?
Use it to create prompts, refine unclear ones, and review whether a prompt gives the model enough information to produce the intended result.
Why use it?
It helps make prompts clear about the task, needed context, limits, success criteria, and answer format.

Skill for Codex

Written for Codex: installed under .codex/. Also seen: mentions Codex.

This is pavel-molyanov/molyanov-ai-dev's own configuration. It tells Codex how to work on molyanov-ai-dev itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything molyanov-ai-dev configures →

Reuse

Borrowing it

Nothing to install: this file belongs to pavel-molyanov/molyanov-ai-dev. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/pavel-molyanov/molyanov-ai-dev/main/.codex/skills/prompt-master/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/pavel-molyanov/molyanov-ai-dev

Made for: Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for prompt-master

README.md
[![agentmods](https://agentmods.dev/badge/skills/pavel-molyanov/molyanov-ai-dev/prompt-master/github.svg)](https://agentmods.dev/skills/pavel-molyanov/molyanov-ai-dev/prompt-master)
Your own site
<a href="https://agentmods.dev/skills/pavel-molyanov/molyanov-ai-dev/prompt-master"><img src="https://agentmods.dev/badge/skills/pavel-molyanov/molyanov-ai-dev/prompt-master/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for prompt-master

Your own site · 80×15
<a href="https://agentmods.dev/skills/pavel-molyanov/molyanov-ai-dev/prompt-master"><img src="https://agentmods.dev/badge/skills/pavel-molyanov/molyanov-ai-dev/prompt-master.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 49 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 944 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00049 $0.00944
Opus 5 $0.00024 $0.00472
Sonnet 5 $0.00010 $0.00189
Haiku 4.5 $0.00005 $0.00094

Measured 12d ago against content hash 8faec5a9f075, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

prompt-master scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.codex/skills/prompt-master/SKILL.md · 84 lines

How it starts

The opening of the file, as written. The whole thing — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Prompt Master

Treat a prompt as a clear task contract. Add information that changes the result; do not add a technique merely because it is common in prompt-engineering guides.

Prompt Essentials

A prompt should communicate the applicable parts of:

  • the task and required result;
  • context the model cannot infer but needs to perform the task correctly;
  • real constraints and the reasons behind non-obvious requirements;
  • criteria that distinguish an acceptable result;
  • the response format when it matters to the user or a downstream system.

Use a role only when it changes the required expertise, tone, or behavior. Decorative claims such as "you are the best expert" do not replace relevant context or concrete requirements.

State each instruction once. Prefer direct positive guidance when it fully expresses the rule, and keep explicit prohibitions for genuine boundaries or common failures that positive wording would leave ambiguous. Explain why a non-obvious rule matters instead of relying on capitalization or repeated emphasis.

Conditional Techniques

  • Examples: Start with a clear task description. Add examples when the required format, tone, or decision boundary is difficult to specify in words, or when observed outputs reveal a concrete failure that an example can correct. Use realistic examples without a fixed count.
  • Structure: Use headings, XML, or other delimiters when they help distinguish instructions, context, examples, and input data. They improve readability and parsing; they do not create a security boundary by themselves.
  • Chaining: Split work across model calls when an intermediate result must be inspected, evaluated, or kept separate by the application. A coherent task may remain in one prompt.
  • Structured output: When software consumes the response, define the exact schema and use a structured-output feature when available rather than relying only on a request to return JSON.

Read the full file on GitHub · 84 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 84 lines · 49 tokens per session scan A 8faec5a9f075

Subscribe to this mod's changes

prompt-master is a skill published in the GitHub repository pavel-molyanov/molyanov-ai-dev (286 stars, last pushed 20d ago), licensed MIT. It adds 49 tokens to every session and 944 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

llm-app-patterns

Production-ready patterns for building LLM applications. Covers RAG pipelines, agent architectures, prompt IDEs, and LLMOps monitoring. Use when designing AI applications, implementing RAG, building agents, or setting up LLM observability.

davila7/claude-code-templates · 54 tokens

prompt-optimization

Improve a prompt on the evaluations workbench through a measured loop. Score the baseline first, then duplicate the target column, form a hypothesis from failing rows, edit the copy's prompt draft, run, compare pass rate and cost, and repeat until the numbers hold. Use when the user asks to optimize or improve a…

langwatch/langwatch · 105 tokens

enhance-prompt

Transforms vague UI ideas into polished, Stitch-optimized prompts. Enhances specificity, adds UI/UX keywords, injects design system context, and structures output for better generation results.

google-labs-code/stitch-skills · 41 tokens

prompt-engineer

Writes, refactors, and evaluates prompts for LLMs — generating optimized prompt templates, structured output schemas, evaluation rubrics, and test suites. Use when designing prompts for new LLM applications, refactoring existing prompts for better accuracy or token efficiency, implementing chain-of-thought or few-shot…

Jeffallan/claude-skills · 93 tokens

seedance-vocab-en

This skill should be used when an English Seedance 2.0 prompt needs clearer production wording, less generic prose, or precise vocabulary for camera, lighting, motion, VFX, audio, and constraints. Route blocked prompts through seedance-filter for context and boundary review.

Emily2040/seedance-2.0 · 61 tokens

ideogram4

Prompting patterns for Ideogram 4 text-to-image — best-in-class in-image text rendering and exact color/layout control via structured JSON captions. Use when generating images that need legible on-image text (title cards, thumbnails, logos, signage, CTAs), precise brand colors, or controlled spatial layout. Triggers…

digitalsamba/claude-code-video-toolkit · 99 tokens