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GuideTDF-GD-01
Prompting for Operators
The patterns, not the theory.
THE DIGITAL FOUNDRY$19

Guide · 01

Prompting for Operators

The exact prompt patterns used to build every skill, agent, and pack in the Foundry catalogue — structured input, constraint stacking, output contracts, and the failure patterns that waste a run. Written for people shipping work, not writing papers.

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What’s inside

Open the folder before you buy it.

This is the exact manifest of the download — no mystery box. A full excerpt is free below, so you can judge the quality before paying.

Read the free sample →
prompting-for-operators/ · 9 files · 2.8 MB
prompting-for-operators.pdf54 pages
prompting-for-operators.epub54 pages
prompting-for-operators.mdplain text
patterns/4 files
constraint-stacking.md·
output-contracts.md·
structured-input.md·
self-check-passes.md·
cheat-sheet.pdf1 page

Free sample · Chapter 2

Output contracts — telling the model exactly how to fail.

Most bad prompt output isn't a bad answer, it's an answer in the wrong shape. An output contract fixes that before generation starts: you specify the format, the required fields, and — critically — what the model should do when it doesn't have enough information to fill one. Skip that last part and the model guesses, and guesses read as confident wrong answers.

The pattern is three lines: the shape you want, the field that's allowed to say 'unknown', and one example of the contract satisfied. Add a fourth line only if the task has a hard constraint that's easy to violate, like a length cap or a forbidden word. Every prompt in this catalogue's config packs uses a version of this exact structure.

— excerpt ends. Full pattern set and worked examples in the complete guide.

Buy it if. Skip it if.

Built for you if

  • You use AI tools daily for real output, not casual chat
  • You want patterns you can reuse across tasks, not one-off examples
  • You've had a model confidently return the wrong shape of answer and want that fixed

Skip it if

  • You're brand new to using any AI tool — start there first, this assumes basic fluency
  • You want model-specific API tuning (temperature, tokens) — this is prompt structure, not API config
  • You only need prompts for casual one-off questions — this is built for repeatable operator work

Questions