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Prompt Documentation Templates for Teams

·10 min read·Par Hans Kuepper · Fondateur de PromptQuorum, outil de dispatch multi-modèle · PromptQuorum

Well-documented prompts are reusable; poorly documented ones get reinvented. As of April 2026, using standardized templates ensures consistent, discoverable prompt libraries.

Standard Prompt Template

Title: Clear, searchable name

Purpose: 1—2 sentences (what it solves)

Prompt Body: Full text with placeholders

Inputs: What the user provides

Output Format: Expected structure (JSON, bullets, etc.)

Model & Settings: Recommended model, temperature, etc.

Examples: 1—2 input→output examples

Tags: #category #use-case

Owner: Who maintains this

Version: Current version

Last Updated: Date

Known Limitations: Where it fails

Example: Classify Sentiment

Title: Sentiment Classification

Purpose: Classify customer feedback as positive, negative, or neutral

Prompt Body: "Classify the following feedback as positive, negative, or neutral. Respond with only one word.\n\nFeedback: {feedback}"

Inputs: feedback (string)

Output Format: "positive" | "negative" | "neutral"

Model: GPT-4o or Claude

Examples: "Great service!" → "positive", "Broke after 1 day" → "negative"

Version: v1.2 (fixed sarcasm detection)

Owner: Customer Success team

Where to Store Documentation

  • Git: Markdown files, version control
  • Spreadsheet: Searchable, non-technical
  • Wiki: Central knowledge base
  • Prompt tool: Built-in documentation

Make Prompts Searchable

  • Use consistent naming
  • Tag heavily (#classification, #sentiment)
  • Write clear descriptions
  • Organize by use case or domain

Sources

  • Markdown. Writing style guide
  • GitHub. README best practices
  • Notion. Template design

Common Mistakes

  • Documentation out of sync with actual prompt
  • No examples (confusing for new users)
  • Poor naming (unmemorable, unsearchable)
  • No metadata (can't find it later)
  • Overly detailed (people skip it)
  • No limitations section (hidden failures)

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