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avivsinai

langfuse-mcp

create_chat_prompt

Create and version chat prompts with labels and configuration for LLM applications in Langfuse.

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

Behavior4/5

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

With no annotations provided, the description carries full burden and does well by disclosing key behavioral traits: it explains that prompts are immutable (important constraint), that creating a new version is required for updates, and that labels have uniqueness constraints across versions. It doesn't cover permissions, rate limits, or error handling, but provides substantial operational context.

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 perfectly concise with three sentences that each earn their place: first establishes the core action, second explains the data format and immutability constraint, third provides crucial uniqueness rule for labels. No wasted words, front-loaded with the main 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?

Given the tool's complexity (6 parameters, mutation operation) and the presence of an output schema, the description provides good coverage of operational constraints (immutability, versioning, label uniqueness). However, as a mutation tool with no annotations, it could benefit from mentioning authentication requirements or potential side effects to be fully complete.

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

Parameters3/5

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

Schema description coverage is 100%, so the baseline is 3. The description adds minimal parameter semantics beyond the schema - it mentions that 'prompts are arrays of role/content messages' and 'labels are unique across versions', which provides some context but doesn't significantly enhance understanding of individual parameters beyond what the schema already documents.

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 specific action ('Create a new chat prompt version') and resource ('in Langfuse'), distinguishing it from sibling tools like create_text_prompt. It explicitly mentions that prompts are immutable and require new versions for updates, which clarifies the tool's unique purpose beyond basic creation.

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 provides clear context about when to use this tool ('create a new version to update content') and mentions that 'labels are unique across versions', which offers implicit guidance. However, it doesn't explicitly state when to use alternatives like update_prompt_labels or how this differs from create_text_prompt, missing explicit sibling differentiation.

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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