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prompt-engineer

Design, refactor, evaluate, and version prompts for image generation, image analysis, style learning, and structured agent tools.

Skill by bl1nk42

IndexedApache-2.0★ 2
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/bl1nk42-prompt-engineer

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

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About

Design, refactor, evaluate, and version prompts for image generation, image analysis, style learning, and structured agent tools. Use when outputs are inconsistent, prompts need optimization, or a new provider/model is introduced.

Use cases: design, agent-building

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Permissions

What this skill can do and what it asks for, from its SKILL.md and code. Checked Nov 1, 2026.

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Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/prompt-engineer

What's inside

Skill name
prompt-engineer
Description
Design, refactor, evaluate, and version prompts for image generation, image analysis, style learning, and structured agent tools. Use when outputs are inconsistent, prompts need optimization, or a new provider/model is introduced.
License
Apache-2.0
Instructions
16 lines in SKILL.md · view on GitHub

Files (4)

  • SKILL.md
  • evaluation-rubric.md · references/
  • prompt-patterns.md · references/
  • structured-output.md · references/

SKILL.md (first lines)

# Prompt Engineer

## Contract-first method
Define task, input variables, output shape, success metric, cost/latency budget, safety constraints, and known failure modes before writing the prompt. Keep user facts separate from optional enhancement. Use structured output when a downstream tool consumes the result.

## Image prompt method
Use five blocks: purpose/medium; subject facts; composition/camera; lighting/material/mood; exact text and exclusions. Put learned style after subject facts. Use deterministic inline choices and clamp weights to `[0.5, 2.0]`. Never add unrelated subject details just to make a prompt sound vivid.

## Evaluation
Create a small test set with normal, empty, multilingual, long, conflicting, text-bearing, reference-image, and adversarial inputs. Score prompt preservation, schema validity, model adherence, and consistency. If the baseline is below 80%, identify one failure pattern and change one prompt element at a time. Record version, model, parameters, result, and human/automatic score with `register_entity` or dataset metadata.

## Deployment
Do not replace a production prompt without comparing old/new outputs. Keep rollback text. Report known limitations and provider-specific differences in `model-catalog.json` metadata.

Read `references/prompt-patterns.md`, `references/evaluation-rubric.md`, and `references/structured-output.md` when designing a new workflow.

From bl1nk42/image-gen, Apache-2.0.

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Last commit (this folder)
Sep 25, 2026 (1 month ago)

From GitHub (fetched Oct 24, 2026).

Details

License
Apache-2.0
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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prompt-engineer skill. Agent Mart. https://agentmart.dev/skills/bl1nk42-prompt-engineer (last updated 2026-10-24)