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int2t05int2t05/engineering-skills/skills/03-design/prompt-engineering/SKILL.md

prompt-engineering

Skill3 starsChanged 29 days agoMITView on GitHub

Design and evaluate prompts or LLM workflows on representative tasks. Triggers on "prompt engineering", "提示词工程".

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The file

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    Common

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    Distinctive

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  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Run representative and adversarial cases.

    line 22

“Common” is measured: kept by at least 6 in 10 of the 75 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

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Files
SKILL.md

Prompt Engineering

When to use

  • Design and evaluate prompts or LLM workflows on representative tasks.

Not for: skill-authoring for skills; research for model comparisons.

Steps

  1. Define inputs, expected outcomes, trust boundaries, failure costs and representative cases.
  2. Establish the existing baseline; add minimal instructions addressing observed gaps and verify current provider behavior.
  3. Specify output validation and actual tool permissions, budgets and termination; prompt text alone is not a security boundary.
  4. Run representative and adversarial cases; compare quality, latency and cost and report limitations.

Output: Suggested paths, subject to human audit: docs/design/PROMPT.md for a maintained workflow.

Verify

  • Revisions have a stated baseline and rubric; invalid output and untrusted input are handled and unrun cases are explicit.

References

  • engineering-principles.md — shared decision boundaries, scope and verification.
  • human-audit.md — document consent, readability and human review.
  • references/prompt-architecture.md — prompt component breakdown, few-shot patterns, structured-output techniques, model selection matrix, eval-harness setup, guardrail catalog

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