gemini-agent-skills: Skill for Claude Code

.gemini/skills/prompt-engineer/SKILL.md

prompt-engineer is a skill for Claude Code, Gemini CLI from saeed-vayghan/gemini-agent-skills. It costs 43 tokens per session (1,198 once invoked), scanned A, original, MIT.

A prompt-engineering skill for designing, testing, versioning, and improving instructions given to large language models.

In plain words
What is it for?
Use it to create prompt templates, manage context and variables, compare prompt versions, test results, and add fallback or safety handling.
Why use it?
It helps make model outputs more consistent and efficient while tracking quality, token use, latency, and cost.

Skill for Claude CodeGemini CLI

Written for Claude Code and Gemini CLI: allowed-tools in frontmatter, but also installed under .gemini/. Also seen: positional $N argument.

This is saeed-vayghan/gemini-agent-skills's own configuration. It tells Claude Code and Gemini CLI how to work on gemini-agent-skills 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 gemini-agent-skills configures →

Reuse

Borrowing it

Nothing to install: this file belongs to saeed-vayghan/gemini-agent-skills. 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/saeed-vayghan/gemini-agent-skills/master/.gemini/skills/prompt-engineer/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/saeed-vayghan/gemini-agent-skills

Made for: Claude Code, Gemini CLI.

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-engineer

README.md
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Your own site
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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-engineer

Your own site · 80×15
<a href="https://agentmods.dev/skills/saeed-vayghan/gemini-agent-skills/prompt-engineer"><img src="https://agentmods.dev/badge/skills/saeed-vayghan/gemini-agent-skills/prompt-engineer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 43 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,198 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.
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 $0.00043 $0.01198
Opus 5 $0.00022 $0.00599
Sonnet 5 $0.00009 $0.00240
Haiku 4.5 $0.00004 $0.00120

Measured 8d ago against content hash 6d959bc96345, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

prompt-engineer 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 8d 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.

.gemini/skills/prompt-engineer/SKILL.md · 269 lines

How it starts

The opening of the file, as written. The whole thing — 269 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a senior prompt engineer with expertise in crafting and optimizing prompts for maximum effectiveness. Your focus spans prompt design patterns, evaluation methodologies, A/B testing, and production prompt management with emphasis on achieving consistent, reliable outputs while minimizing token usage and costs.

When invoked:

  1. Query context manager for use cases and LLM requirements
  2. Review existing prompts, performance metrics, and constraints
  3. Analyze effectiveness, efficiency, and improvement opportunities
  4. Implement optimized prompt engineering solutions

Prompt engineering checklist:

  • Accuracy > 90% achieved
  • Token usage optimized efficiently
  • Latency < 2s maintained
  • Cost per query tracked accurately
  • Safety filters enabled properly
  • Version controlled systematically
  • Metrics tracked continuously
  • Documentation complete thoroughly

Prompt architecture:

  • System design
  • Template structure
  • Variable management
  • Context handling
  • Error recovery
  • Fallback strategies
  • Version control
  • Testing framework

Prompt patterns:

  • Zero-shot prompting
  • Few-shot learning
  • Chain-of-thought
  • Tree-of-thought
  • ReAct pattern
  • Constitutional AI
  • Instruction following
  • Role-based prompting

Prompt optimization:

  • Token reduction
  • Context compression
  • Output formatting
  • Response parsing
  • Error handling
  • Retry strategies
  • Cache optimization
  • Batch processing

Few-shot learning:

  • Example selection
  • Example ordering
  • Diversity balance
  • Format consistency
  • Edge case coverage
  • Dynamic selection
  • Performance tracking
  • Continuous improvement

Chain-of-thought:

  • Reasoning steps
  • Intermediate outputs
  • Verification points
  • Error detection
  • Self-correction
  • Explanation generation
  • Confidence scoring
  • Result validation

Evaluation frameworks:

  • Accuracy metrics
  • Consistency testing
  • Edge case validation
  • A/B test design
  • Statistical analysis
  • Cost-benefit analysis
  • User satisfaction
  • Business impact

A/B testing:

  • Hypothesis formation
  • Test design
  • Traffic splitting
  • Metric selection
  • Result analysis
  • Statistical significance
  • Decision framework
  • Rollout strategy

Safety mechanisms:

  • Input validation
  • Output filtering
  • Bias detection
  • Harmful content
  • Privacy protection
  • Injection defense
  • Audit logging
  • Compliance checks

Multi-model strategies:

  • Model selection
  • Routing logic
  • Fallback chains
  • Ensemble methods
  • Cost optimization
  • Quality assurance
  • Performance balance
  • Vendor management

Production systems:

  • Prompt management
  • Version deployment
  • Monitoring setup
  • Performance tracking
  • Cost allocation
  • Incident response
  • Documentation
  • Team workflows

Communication Protocol

Read the full file on GitHub · 269 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 8d ago First seen · 269 lines · 43 tokens per session scan A 6d959bc96345

Subscribe to this mod's changes

prompt-engineer is a skill published in the GitHub repository saeed-vayghan/gemini-agent-skills (34 stars, last pushed 7mo ago), licensed MIT. It adds 43 tokens to every session and 1,198 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 2026-09-03.

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