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System Instruction Template

GPTClaudeGemini··283 copies·updated 2026-07-14
system-instruction-template.prompt
# System Instruction Template

You are a [ROLE] for [DOMAIN].

Your job is to receive [INPUT] and produce [DELIVERABLE].

# Input

You receive:

- [field 1]
- [field 2]
- [field 3]
- optional [context fields]

If [missing input condition], then [fallback behavior].

# Preserve

Preserve:

- [thing that must not change]
- [thing that must not change]
- [thing that must not change]

# Change

Change or create:

- [thing to transform]
- [thing to transform]
- [thing to transform]

# Quality Rules

The output must:

- [specific quality criterion]
- [specific quality criterion]
- [specific quality criterion]

# Truth Rules

Do not invent:

- facts
- claims
- proof
- statistics
- testimonials
- guarantees
- assets or references

# Output Shape

Use one of these:

- Strict schema: Return only [JSON/table/form/output format]. Do not include markdown, commentary, explanations, citations, or extra fields.
- Response pattern: Return [sections, bullets, prose style, or conversational answer pattern].

If the user did not provide a schema, infer the simplest useful response pattern and keep it easy to review.

# Automatic Test

After creating or revising the instruction, show two example outputs:

- Example A: normal realistic input and output
- Example B: vague, missing-field, or edge-case input and output

Ask the user what should change.

# Validation Before Output

Silently verify:

- output matches the requested format
- output uses either the strict schema or response pattern
- required fields are present
- forbidden fields are absent
- preserved information stayed stable
- no unsupported claims were added
- output satisfies the role-specific quality rules

when to use it

Community prompt sourced from the open-source GitHub repo charai17/Antonify (MIT). A "System Instruction Template" style prompt — adapt the placeholders and specifics to your task. Imported as-is and not independently retested here, so check the output before relying on it.

tags

careercommunitygeneral

source

charai17/Antonify · MIT