Ross ROSS = Recommend OSS · open-source software intelligence for agents

microsoft/prompty

Prompty makes it easy to create, manage, debug, and evaluate LLM prompts for your AI applications. Prompty is an asset class and format for LLM prompts designed to enhance observability, understandability, and portability for developers. observed · 2026-08-28

github.com/microsoft/prompty · homepage · Rust · MIT (permissive) observed · 2026-08-28

Health v2 · maintenance only

71/100

  • Activity 99
  • Release rhythm 40
  • Longevity 61
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.

  • gap_med: 0.0
  • age_days: 863
  • days_rel: 405
  • days_push: 8
  • n_releases_24m: 5

Full methodology

Adoption not part of the score

1252 stars · 126 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Prompty is a markdown-based file format (.prompty) for authoring LLM prompts with YAML frontmatter for model config, inputs, tools, and templates. It ships runtimes for Python, TypeScript, and Rust plus a VS Code extension to execute, trace, and debug prompts across providers like OpenAI, Anthropic, and Microsoft Foundry.

Use cases

  • manage llm prompts as versioned files
  • run a prompt from python or typescript without rewriting it
  • debug and trace llm prompt executions
  • evaluate and iterate on prompt templates
  • switch llm providers without changing prompt files
  • author prompts in vs code with syntax highlighting
  • render jinja2 or mustache prompt templates

When to choose

  • you want a portable, single-file prompt asset format across languages
  • you need built-in tracing and observability for prompt runs
  • your team authors prompts in VS Code and executes them in Python or TypeScript
  • you need to swap LLM providers or endpoints without editing prompt bodies

When to avoid

  • you need a full agent orchestration framework rather than prompt assets
  • you require a stable, frozen API - the v2 format and tooling are in alpha and may change
  • you only call LLMs with simple hardcoded strings and don't need templating or tracing

Facets

library · maturity experimental

prompt-engineering llm-inference templating tracing sdk large-language-models developer-tools artificial-intelligence python rust cross-platform editor-plugin prompt-format markdown-prompts vscode-extension llm-observability portable-prompts jinja2 mustache ai-agents nodejs

3 sources

Member repositories

RepositoryRoleHealth v2
microsoft/promptymain71

For agents

markdown · JSON · MCP: product_card(name="microsoft/prompty")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem