Senior Prompt Engineer Agent Skill

Use when the user asks to optimize prompts, design prompt templates, evaluate LLM outputs with an eval set, measure RAG retrieval quality, validate agent/tool configurations, analyze token usage, or design structured-output contracts.

Context cost
2.5k tokensestimated from the bundle, loaded when it triggers
Bundle
1 file · 10.0 kBtext throughout, nothing executable
Licence
MITthe author’s own terms
Last change
—no release on file
Servers it uses
Noneruns standalone

What it does

Use when the user asks to optimize prompts, design prompt templates, evaluate LLM outputs with an eval set, measure RAG retrieval quality, validate agent/tool configurations, analyze token usage, or design structured-output contracts. Covers eval-driven prompt iteration, RAG metrics (relevance, faithfulness, coverage), agent workflow validation, and token/cost budgeting — all model-agnostic, with three stdlib Python tools.

What this skill changes about the agent has not been set out here as a list. Its SKILL.md, shown below, says it in the author’s own words.

data scienceprompt

The skill itself

A skill is instructions the model reads, so you can see what you are getting: below is the start of its SKILL.md. The front matter loads with every session, the body loads when the skill triggers, and the whole file comes with the install.

SKILL.md10.0 kB · preview
--- name: "senior-prompt-engineer" ---
6# Senior Prompt Engineer
7
8Eval-driven prompt engineering, RAG quality measurement, and agent workflow validation. Everything here is **model-agnostic by design**: techniques are framed by what they do, not by which model generation they were observed on, and the tools never hardcode model IDs or pricing — you supply your provider's current rates when you want dollar figures.
9
10## Operating Rules
11
121. **Never change a prompt without a baseline.** Capture metrics first (--analyze --output baseline.json), then compare every iteration against it.
132. **Eval set before optimization.** 10–20 representative cases with expected outputs minimum. If the user has no eval set, build one with them before touching the prompt — optimizing against vibes is the #1 failure mode.
143. **Prefer platform features over prompt hacks.** If the provider offers native structured outputs / JSON schema enforcement, tool-use APIs, or prompt caching, use those instead of "respond ONLY with JSON" incantations. Prompt-level format enforcement is the fallback, not the default.
154. **Current-generation models need less scaffolding.** Don't add chain-of-thought boilerplate, role framing, or few-shot examples reflexively — frontier models often do worse with redundant scaffolding. Add each element only when the eval set shows it helps.
165. **Cost numbers are always user-supplied.** Look up the provider's current per-Mtok pricing and pass it via --price-per-mtok (never trust a cached price table — including any you remember).
17
18## Tools (exact CLIs, all stdlib)
19
20### 1. Prompt Optimizer — scripts/prompt_optimizer.py
21
22Static analysis: token estimate, clarity/structure scores (0–100), ambiguity + redundancy detection, few-shot example extraction.
23
24```bash
This is a preview of SKILL.md. Download or install the skill to get the whole thing.
In the file
SKILL.md1,269 words
Files1
LicenceMIT
Why you can read it

Nothing in a skill executes. The client loads the text and the model follows it, so a skill can be audited the way a runbook is — by reading it.

What it costs in context

Skills are not billed by the call. They are paid for in context: every token the instructions occupy is a token your code, your diff and your conversation cannot use. Here is what this one takes and when it takes it.

≈120
always loaded
The name and description, so the model knows the skill exists and when to reach for it.
2,380
on trigger
The instruction body, read only when the skill fires.
1.3%
of a 200k window
Ten skills this size would take about 13% of the window before you open a file.
050k100k150k200k context window

2.5k tokens, estimated from the bundle at four bytes to the token, held for the rest of the session once it triggers. Middling. Fine to keep on in a project where you use it weekly, worth unloading in one where you never do.

Servers bill, skills cost

A server charges by the month. A skill charges once per session, in context, and then keeps charging it for as long as the session lives.

Before and after

The same question, put to the same model twice: once as it comes, and once with these instructions loaded.

No worked example has been published for this skill yet.

The procedure it runs

The procedure has not been set out here step by step. It is in the body of its SKILL.md: the start of it is shown above, and the whole file comes with the install.

Prose, not code

These steps are written for a model to follow, not executed by a runtime. It can still be told to skip one, and it will say so when it does.

Servers it uses

None. This skill calls no MCP servers at all.

Everything it needs is in the instructions, so it works in a project with nothing connected — the model reads the file and changes how it works with what it can already reach.

Its SKILL.md does not declare which tools it asks the agent for, so what it touches is whatever the instructions themselves ask for — read them before you install it.

What it asks for
Writes filesnot declared
Network accessnot declared

This SKILL.md carries no allowed-tools line, so neither is declared. A skill grants no permissions of its own — it can only ask for tools your client already has.

What it will not do

Every skill is narrow, and the useful ones say where they stop. These are the jobs this one is the wrong tool for.

What this skill is not for has not been published here. Nothing is implied by that: it is a section the author has not filled in.

What is in the bundle

1 file, 10.0 kB on disk. A bundle is text throughout: the instructions the model reads, plus the templates it fills in.

  • SKILL.md10.0 kB
What is not in it

No dependencies and nothing executable: a skill is text the agent reads, so the bundle is 1 file you can review in full before installing. The MIT licence covers the templates and examples as well as the instructions.

Install

Installing copies the bundle into your project. Nothing runs at install time — the files sit on disk until the model reads them.

# Senior Prompt Engineer · 2.5k tokens when loaded · macOS, Linux mkdir -p .claude/skills && t=$(mktemp -d) && curl -fsSL -o "$t/bundle.tar.gz" https://mcprush.com/api/skills/senior-prompt-engineer/bundle.tar.gz && tar -xzf "$t/bundle.tar.gz" -C "$t" && [ -d "$t/senior-prompt-engineer" ] && { [ ! -e .claude/skills/senior-prompt-engineer ] || { mv .claude/skills/senior-prompt-engineer "$t/.previous" && echo "Previous copy moved to $t/.previous"; }; } && mv "$t/senior-prompt-engineer" .claude/skills/ && echo "Installed .claude/skills/senior-prompt-engineer"
On Windows, or any OS with Node 20+
npx mcprush@latest skill add alirezarezvani/senior-prompt-engineer

Windows PowerShell says 'running scripts is disabled on this system'? Run Set-ExecutionPolicy -Scope CurrentUser RemoteSigned once, or type npx.cmd instead of npx (codex.cmd, gemini.cmd, grok.cmd likewise). PowerShell 7 needs neither. Writes to .claude/skills/senior-prompt-engineer/ in the current project. For every project instead, run mkdir -p ~/.claude/skills && t=$(mktemp -d) && curl -fsSL -o "$t/bundle.tar.gz" https://mcprush.com/api/skills/senior-prompt-engineer/bundle.tar.gz && tar -xzf "$t/bundle.tar.gz" -C "$t" && [ -d "$t/senior-prompt-engineer" ] && { [ ! -e ~/.claude/skills/senior-prompt-engineer ] || { mv ~/.claude/skills/senior-prompt-engineer "$t/.previous" && echo "Previous copy moved to $t/.previous"; }; } && mv "$t/senior-prompt-engineer" ~/.claude/skills/ && echo "Installed ~/.claude/skills/senior-prompt-engineer" (macOS, Linux) — or add --global to the npx line. The curl line replaces .claude/skills/senior-prompt-engineer/ only after the download succeeds, so files left there by another skill of the same name, or by an older release, do not mix in. A copy already there is moved aside, not deleted, and the line prints where.

Which clients pick it up on their own

A skill is a folder of text. Most of these read a skills folder and pick it up without being told; the rest take the same folder another way — an upload in the app, a parameter on an API call — and then choose it by its description just the same.

Claude Code.claude/skills/
Claude DesktopCustomize › Skills
ChatGPTSkills › Create › Upload
Cursor.cursor/skills/
VS Code.github/skills/
Codex CLI.agents/skills/
Gemini CLI.gemini/skills/
Grok Build.grok/skills/
Microsoft CopilotSkills › Upload a skill
PerplexityComputer › Skills › Upload a skill
DeepSeek Harness.dsh/skills/
Zed.agents/skills/
Devin Desktop.devin/skills/
Windsurf (legacy).windsurf/skills/
OpenAI Agents SDKInstructions or sandbox Skills
HTTP / APIa request parameter
This release
Versionnot versioned
Publishedno release date on file
PriceFree
Referencealirezarezvani/senior-prompt-engineer

Versions

Its author publishes no version number, so there is nothing here to pin to: what you install is the folder as it stands today. Instructions change more often than APIs do — a skill can be rewritten entirely without anything it depends on moving.

Pinning

Nothing to pin to: this skill carries no version number of its own. What you install is what the folder holds on the day you install it.

Reviews

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