General
prompts - Claude MCP Skill
Version and manage your agent's prompts with LangWatch Prompts CLI. Use for both onboarding (set up prompt versioning for an entire codebase) and targeted operations (version a specific prompt, create a new prompt version). Supports Python and TypeScript.
SEO Guide: Enhance your AI agent with the prompts tool. This Model Context Protocol (MCP) server allows Claude Desktop and other LLMs to version and manage your agent's prompts with langwatch prompts cli. use for both onboarding (set up ... Download and configure this skill to unlock new capabilities for your AI workflow.
Documentation
SKILL.md# Version Your Prompts with LangWatch Prompts CLI
## Determine Scope
If the user's request is **general** ("set up prompt versioning", "version my prompts"):
- Read the full codebase to find all hardcoded prompt strings
- Study git history to understand what changed and why — focus on agent behavior changes, prompt tweaks, bug fixes. Read commit messages for context.
- Set up the Prompts CLI and create managed prompts for each hardcoded prompt
- Update all application code to use `langwatch.prompts.get()`
If the user's request is **specific** ("version this prompt", "create a new prompt version"):
- Focus on the specific prompt
- Create or update the managed prompt
- Update the relevant code to use `langwatch.prompts.get()`
## Plan Limits
See [Plan Limits](_shared/plan-limits.md).
## Step 1: Read the Prompts CLI Docs
See [CLI Setup](_shared/cli-setup.md).
Then specifically read the Prompts CLI guide:
```bash
langwatch docs prompt-management/cli
```
CRITICAL: Do NOT guess how to use the Prompts CLI. Read the docs first.
## Step 2: Initialize Prompts in the Project
```bash
langwatch prompt init
```
Creates a `prompts.json` config and a `prompts/` directory in the project root.
## Step 3: Create a Managed Prompt for Each Hardcoded Prompt
Scan the codebase for hardcoded prompt strings (system messages, instructions). For each:
```bash
langwatch prompt create <name>
```
Edit the generated `.prompt.yaml` file to match the original prompt content.
## Step 4: Update Application Code
Replace every hardcoded prompt string with a call to `langwatch.prompts.get()`.
**Python (BAD → GOOD):**
```python
agent = Agent(instructions="You are a helpful assistant.")
```
```python
import langwatch
prompt = langwatch.prompts.get("my-agent")
agent = Agent(instructions=prompt.compile().messages[0]["content"])
```
**TypeScript (BAD → GOOD):**
```typescript
const systemPrompt = "You are a helpful assistant.";
```
```typescript
const langwatch = new LangWatch();
const prompt = await langwatch.prompts.get("my-agent");
```
CRITICAL: Do NOT wrap `langwatch.prompts.get()` in a try/catch with a hardcoded fallback string. The whole point of prompt versioning is that prompts are managed externally. A fallback defeats this by silently reverting to a stale hardcoded copy.
## Step 5: Sync to the Platform
```bash
langwatch prompt sync
```
## Step 6: Tag Versions for Deployment
Three built-in tags: `latest` (auto-assigned), `production`, `staging`. Update code to fetch by tag:
```python
prompt = langwatch.prompts.get("my-agent", tag="production")
```
```typescript
const prompt = await langwatch.prompts.get("my-agent", { tag: "production" });
```
Assign tags via the CLI (or the Deploy dialog in the LangWatch UI):
```bash
langwatch prompt tag assign my-agent production
```
For canary or blue/green deployments, create custom tags with `langwatch prompt tag create`.
## Step 7: Verify
Run `langwatch prompt list` to confirm everything synced, or open the Prompts section in the LangWatch app.
## Common Mistakes
- Do NOT hardcode prompts — always fetch via `langwatch.prompts.get()`
- Do NOT add a hardcoded fallback string in a try/catch — that silently defeats versioning
- Do NOT manually edit `prompts.json` — use the CLI
- Do NOT skip `langwatch prompt sync` after creating promptsSignals
Information
- Repository
- langwatch/langwatch
- Author
- langwatch
- Last Sync
- 4/24/2026
- Repo Updated
- 4/23/2026
- Created
- 3/17/2026
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