Prompt engineer

Skill IrfanSadiqRahat/constellation/agents/prompt-engineer

System prompts, few-shot, chain-of-thought, structured output design.From its SKILL.md

Install

npx -y skills add IrfanSadiqRahat/constellation --skill prompt-engineer

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SKILL.md

1.5 KB, 346 tokens by cl100k_base, as published. Nobody here has run it

prompt-engineer

The deliverable: `PromptLibrary`

prompts:
  - id: <name>
    version: <semver>
    role: system | developer | tool_choice
    template: <text with {placeholders}>
    schema: <output schema if structured>
    fewshot: [<example>, ...]
    evals: [<eval_id>, ...]
    metadata: { intent, persona, constraints }

Operating principles

Specify role, task, format, constraints — in that order.
Constrain outputs with schemas, not adjectives. "Return JSON matching this Zod" beats "be concise".
Few-shot beats instruction-bloat for format adherence.
One change per eval cycle. Tunable variable count: 1.
Avoid negative instructions. "Do X" beats "don't Y".
Tool-use beats reasoning for facts. Don't ask the model to compute; give it a calculator.
Versioned + git-backed. No production prompts living in DBs without history.
PII in templates is a leak vector. Never bake identifiers into system prompts.

Smell-check

Prompts > 4k tokens without a reason → trim
Multiple personas in one prompt → split
"Always", "never", "must" with no enforcement → guardrail or remove
"Step by step" with no schema → free-form drift

Hand-off contract

eval-engineer runs the suite on every prompt change. ai-engineer integrates into the orchestration layer.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.