llm

---

name: llm

description: "Build and evaluate LLM prompts. Use when crafting system prompts, comparing variants, estimating tokens, or managing prompt templates."

version: "3.4.0"

author: BytesAgain

homepage: https://bytesagain.com

source: https://github.com/bytesagain/ai-skills

tags:

- llm

- prompt-engineering

- tokens

- templates

- evaluation

---

# llm

LLM Prompt Engineering Toolkit. Build structured prompts from role/context/task components, compare prompt variations side by side, estimate token counts, manage reusable prompt templates, chain multi-step prompts, and evaluate prompt quality with a scored breakdown. All commands run locally in bash with no API keys or network access required.

Commands

`prompt` — Build a Structured Prompt

Assembles a prompt from modular components: role, context, task, constraints, and output format. The `--task` flag is required; all others are optional.

**Flags:**

bash scripts/script.sh prompt --role "senior developer" --context "Python Flask app" --task "write unit tests"
bash scripts/script.sh prompt --task "summarize this article" --constraints "max 3 sentences" --json

`compare` — Compare Prompt Variations

Compare two or more prompt files side by side. Shows each variant with word/line/char/token stats, then a `diff --side-by-side` of the first two variants, plus a summary table.

**Flags:**

bash scripts/script.sh compare --prompts prompt_a.txt prompt_b.txt
bash scripts/script.sh compare --prompts v1.txt v2.txt v3.txt

`tokenize` — Estimate Token Count

Estimate the token count for a given text using a cl100k_base-compatible heuristic. Reports characters, words, lines, and estimated tokens.

**Input methods:**

bash scripts/script.sh tokenize --input "Your prompt text here"
bash scripts/script.sh tokenize --file prompt.txt
echo "some text" | bash scripts/script.sh tokenize
bash scripts/script.sh tokenize --file prompt.txt --json

`template` — Manage Prompt Templates

Save, list, load, and delete reusable prompt templates. Templates are stored as `.txt` files in `~/.llm-skill/templates/`.

**Actions:**

bash scripts/script.sh template --save my_template --file prompt.txt
bash scripts/script.sh template --list
bash scripts/script.sh template --list --json
bash scripts/script.sh template --load my_template
bash scripts/script.sh template --delete my_template
echo "Write a haiku about {{topic}}" | bash scripts/script.sh template --save haiku

`chain` — Multi-Step Prompt Chains

Run a sequence of prompt steps where each step's output feeds into the next via the `{{previous_output}}` placeholder. Steps can be specified as individual files or loaded from a JSON config.

**Flags:**

bash scripts/script.sh chain --steps step1.txt step2.txt step3.txt
bash scripts/script.sh chain --from chain_config.json
bash scripts/script.sh chain --steps brainstorm.txt refine.txt format.txt --json

`evaluate` — Score Prompt Quality

Score a prompt on four dimensions (0–100 each): **Clarity**, **Specificity**, **Structure**, and **Completeness**. Returns an overall score (0–100) and letter grade (A–F) with actionable suggestions.

**Scoring heuristics:**

bash scripts/script.sh evaluate --input "Explain quantum computing"
bash scripts/script.sh evaluate --file my_prompt.txt
bash scripts/script.sh evaluate --file my_prompt.txt --json

`help` — Show Help

bash scripts/script.sh help

Global Flags

Data Storage

Requirements

When to Use

1. **Crafting system prompts** — Use `prompt` to build well-structured prompts from role/context/task components instead of writing them freehand.

2. **A/B testing prompt variants** — Use `compare` to see side-by-side diffs and token counts for two or more prompt versions before committing to one.

3. **Estimating API costs** — Use `tokenize` to get token estimates before sending prompts to paid LLM APIs, helping you stay within budget.

4. **Building reusable prompt libraries** — Use `template` to save, organize, and reuse your best prompts across projects.

5. **Quality-checking prompts before use** — Use `evaluate` to score your prompts on clarity, specificity, structure, and completeness, with actionable improvement suggestions.

Examples

# Build a structured prompt for code review
bash scripts/script.sh prompt \
  --role "senior code reviewer" \
  --context "React TypeScript project" \
  --task "review this pull request for bugs and performance issues" \
  --constraints "focus on security vulnerabilities" \
  --format "numbered list of findings"

# Estimate tokens for a long prompt
bash scripts/script.sh tokenize --file system_prompt.txt

# Save a template and reuse it
echo "You are a {{role}}. Your task: {{task}}" | bash scripts/script.sh template --save generic
bash scripts/script.sh template --load generic

# Evaluate prompt quality
bash scripts/script.sh evaluate --input "You are an expert Python developer. Write a function that sorts a list of dictionaries by a given key. Include type hints, docstring, and 3 unit tests."

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