prompt-enhancer

prompt-enhancer is a skill for Claude Code, Codex from sammcj/agentic-coding. It costs 67 tokens per session (1,086 once invoked), scanned A, original, Apache-2.0.

A tool for rewriting vague requests into clearer prompts for an AI system. It adds useful context, constraints, separate tasks, success criteria, and possible failure cases.

In plain words
What is it for?
Use it to improve a prompt, refine a request, or frame a task for another AI system when you know what you want but have not expressed it precisely.
Why use it?
It helps avoid answers that miss important details because the original request was too broad or underspecified. The result gives the AI a clearer description of the desired work.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/sammcj/agentic-coding/prompt-enhancer
Any agent
npx skills add sammcj/agentic-coding --skill prompt-enhancer
Clone the repo
git clone --depth 1 https://github.com/sammcj/agentic-coding

Made for: Claude Code, 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-enhancer

README.md
[![agentmods](https://agentmods.dev/badge/skills/sammcj/agentic-coding/prompt-enhancer.svg)](https://agentmods.dev/skills/sammcj/agentic-coding/prompt-enhancer)
Your own site
<a href="https://agentmods.dev/skills/sammcj/agentic-coding/prompt-enhancer"><img src="https://agentmods.dev/badge/skills/sammcj/agentic-coding/prompt-enhancer.svg" alt="Measured on agentmods" height="20"></a>
Per session 67 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,086 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00067 $0.01086
Opus 5 $0.00034 $0.00543
Sonnet 5 $0.00013 $0.00217
Haiku 4.5 $0.00007 $0.00109

Measured 4d ago against content hash d8ec467ba929, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

prompt-enhancer 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 4d 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.

Skills/prompt-enhancer/SKILL.md · 83 lines

How it starts

The opening of the file, as written. The whole thing — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Expert Prompt Enhancer

Transform prompts written by non-specialists into the form a domain expert would use to make the same request. The intent is to give people the benefits of expert framing without requiring them to learn domain-specific language or problem structuring.

Expert Communication Patterns

Expert requests differ from novice requests in predictable ways:

Pattern Novice Expert
Precision "make it faster" "optimise page load performance"
Decomposition Single vague request Broken into logical components
Constraints Unstated Explicit limits, trade-offs, success criteria
Context Missing System fit, standards, prior attempts
Failure modes Ignored Anticipated and specified

Role framing (e.g. "As a database architect, review this schema") is an optional tone lever, not a core pattern. Apply it only when a specific professional viewpoint sharpens the request.

Examples

These illustrate the transformation from novice to expert framing:


Original: "My back hurts, what should I do?"

Expert rewrite: "Provide guidance on managing back pain. Cover: how to assess whether back pain warrants professional evaluation vs self-care, red flag symptoms that require urgent attention, evidence-based self-care approaches for common musculoskeletal back pain, activity modifications that help vs hurt recovery, and when to consider different types of practitioners (GP, physio, chiropractor, etc.). Focus on helping me make informed decisions rather than diagnosing."

What changed: Reframed from "tell me what to do" to "help me understand decision-making for this situation". Specified the information categories that would actually be useful. Acknowledged appropriate scope limitations.

Read the full file on GitHub · 83 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. 4d ago First seen · 83 lines · 67 tokens per session scan A d8ec467ba929

Subscribe to this mod's changes

prompt-enhancer is a skill published in the GitHub repository sammcj/agentic-coding (159 stars, last pushed today), licensed Apache-2.0. It adds 67 tokens to every session and 1,086 once invoked, about $0.0003 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.

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