Templates

Prompt Assembly Template

Use this after the intent note, model-fit note, and context pack. The goal is not to fill every field; it is to make each included field earn its place.

Source: templates/prompt-assembly.md

Prompt Assembly Template

Use this after the intent note, model-fit note, and context pack. The goal is not to fill every field; it is to make each included field earn its place.

If this same assembly pattern keeps recurring, promote the reusable procedure to a project skill and keep run-specific facts in the next context pack.

1. Intent and success criteria

User-visible outcome:

  • ...

What counts as correct:

  • ...

What failure would matter:

  • ...

Fixture set to run before trusting the prompt:

FixtureInputExpected behavior
Happy path
Missing context
Ambiguous input
Conflicting sources
Instruction inside data
Format edge case

2. Model fit

Language operation:

  • [ ] extract structure from supplied material
  • [ ] compare options against criteria
  • [ ] classify against explicit categories
  • [ ] rewrite for a known audience or voice
  • [ ] critique against a checklist
  • [ ] generate candidates inside constraints
  • [ ] translate between domains, vocabularies, or levels of detail
  • [ ] other:

Model or mode choice:

  • ...

Latency, cost, reasoning, tool, or structured-output tradeoff:

  • ...

3. Stable instructions

These should hold across runs of this prompt shape.

Instruction typeContent
Role or job
Task rules
Boundaries and refusals
Uncertainty behavior
Citation or evidence rules
Output contract summary

4. Dynamic context

Separate the material the model transforms from the material it uses as background.

Primary content

What is the model operating on?

LabelSource / provenanceAuthorityInclude becauseBudget decision

Supporting context

What helps interpret the primary content?

LabelSource / provenanceAuthorityInclude becauseBudget decision

Dynamic context boundaries:

  • Data is labeled and delimited: yes / no
  • User-supplied or retrieved instructions are treated as data: yes / no
  • Missing or conflicting evidence has an explicit handling rule: yes / no

5. Examples

Use examples when they regulate behavior. Keep them consistent and varied.

Example typeInputExpected output pattern
Normal case
Edge case
Counterexample / what not to do

6. Output contract

Format or schema:

  • ...

Required sections or fields:

  • ...

Evidence or citation requirement:

  • ...

Length, tone, or audience constraint:

  • ...

If the answer is missing from context:

  • ...

7. Final assembled request

Write the final request in prose. A reviewer should be able to see:

  • the stable instruction;
  • the dynamic context and its provenance;
  • the task boundary;
  • the output contract;
  • the evidence rule;
  • the missing-context behavior.

8. Reviewer checks

Reject the assembled prompt if:

  • [ ] success criteria are missing;
  • [ ] stable instructions and dynamic data are mixed together;
  • [ ] context lacks provenance or authority;
  • [ ] the model has to infer private facts;
  • [ ] examples are absent where consistent behavior matters;
  • [ ] missing or conflicting evidence has no safe response;
  • [ ] the output cannot be checked by fixture, reviewer, or eval;
  • [ ] the prompt worked once but no failure case was tested.