Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Notysoty/openagentskills --skill prompt-refinergit clone --depth 1 https://github.com/Notysoty/openagentskillsWrote 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.
[](https://agentmods.dev/skills/notysoty/openagentskills/prompt-refiner)<a href="https://agentmods.dev/skills/notysoty/openagentskills/prompt-refiner"><img src="https://agentmods.dev/badge/skills/notysoty/openagentskills/prompt-refiner/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.
<a href="https://agentmods.dev/skills/notysoty/openagentskills/prompt-refiner"><img src="https://agentmods.dev/badge/skills/notysoty/openagentskills/prompt-refiner.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00021 | $0.01612 |
| Opus 5 | $0.00010 | $0.00806 |
| Sonnet 5 | $0.00004 | $0.00322 |
| Haiku 4.5 | $0.00002 | $0.00161 |
Grade A, and why
Prompt Refiner 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 10d 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.
How it starts
The opening of the file, as written. The whole thing — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prompt Refiner
What this skill does
This skill takes a rough or underperforming AI prompt and rewrites it to be clearer, more specific, and more likely to produce consistent, high-quality output from a language model. It identifies the root causes of vague or ineffective prompts — missing context, absent output format specs, ambiguous instructions — and systematically addresses each one. It also explains every change so you can learn the principles, not just get a one-time fix.
Use this when your prompts produce inconsistent results, when the model frequently misunderstands what you want, or when you're building a prompt that will run in production.
How to use
Claude Code / Cline
Copy this file to .agents/skills/prompt-refiner/SKILL.md in your project root.
Then paste your prompt and ask:
- "Use the Prompt Refiner skill to improve this prompt."
- "Refine this system prompt using the Prompt Refiner skill — it's producing inconsistent outputs."
Include what the prompt is for (the model it targets, the task, what's going wrong with current outputs) to get more targeted improvements.
Cursor
Add the "Prompt / Instructions" section to your .cursorrules file. Paste your prompt into the chat and ask for a refinement.
Codex
Paste your original prompt and a description of what output you're trying to achieve, then include the instructions below.
The Prompt / Instructions for the Agent
When asked to refine a prompt, follow these steps:
-
Analyze the original prompt for these weaknesses:
- Vague task definition — the model has to guess what "good" looks like
- No role assignment — not telling the model what persona or expertise to adopt
- Missing output format — no specification of length, structure, format (JSON, markdown, bullet list, etc.)
- Missing context — no background about the user, use case, or constraints
- Ambiguous pronouns or references — "it", "this", "the thing" without clear antecedents
- Conflicting instructions — asking for brevity and comprehensiveness in the same breath
- No examples — complex tasks benefit from at least one example of desired input/output
- No constraints — no guidance on what to avoid or exclude
- Negative-only instructions — "don't use jargon" without specifying the preferred alternative
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.
- 10d ago First seen · 175 lines · 21 tokens per session scan A 6d4ba315ab25
Prompt Refiner is a skill published in the GitHub repository Notysoty/openagentskills (9 stars, last pushed 26d ago), licensed MIT. It adds 21 tokens to every session and 1,612 once invoked, about $0.0001 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 2026-08-31.
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