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avivsinai

langfuse-mcp

create_chat_prompt

Create a new version of a chat prompt by defining role/content messages. Assign labels, config, tags, and commit message to manage prompt iterations.

Instructions

Create a new chat prompt version in Langfuse.

Chat prompts are arrays of role/content messages. Prompts are immutable; create a new version to update content. Labels are unique across versions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesThe name of the prompt to create
promptYesChat messages in the format [{role: 'system'|'user'|'assistant', content: '...'}]
labelsNoLabels to assign (e.g., ['production', 'staging'])
configNoOptional JSON config (e.g., {model: 'gpt-4', temperature: 0.7})
tagsNoOptional tags for organization (e.g., ['experimental', 'v2'])
commit_messageNoOptional commit message describing the changes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description discloses key behaviors: immutability and label uniqueness. However, it omits other relevant traits like idempotency, permissions, or rate limits, leaving some gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences long, front-loaded with the primary action, and contains no extraneous information. Every sentence serves a purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 6-parameter tool with output schema, the description covers the essential context (immutability, versioning, label behavior). It could mention optional parameters like config or tags, but the schema handles that.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% (baseline 3), but the description adds value by explaining the prompt format (arrays of role/content) and that labels are unique across versions, aiding understanding beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool creates a new chat prompt version in Langfuse. It specifies the resource type ('chat prompt') and distinguishes it from siblings like 'create_text_prompt' by noting the structure (arrays of role/content messages) and immutability.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains that prompts are immutable and a new version must be created to update content, which guides when to use this tool. It does not explicitly list alternatives but context suffices.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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