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avivsinai

langfuse-mcp

list_prompts

Retrieve and filter prompts from a Langfuse project to manage versions, labels, tags, and metadata with pagination support.

Instructions

List and filter prompts in the project.

Returns metadata about prompts including versions, labels, tags, and last updated time.

Args:
    ctx: Context object containing lifespan context with Langfuse client
    name: Optional filter by exact prompt name
    label: Optional filter by label on any version
    tag: Optional filter by tag
    page: Page number for pagination (starts at 1)
    limit: Maximum items per page (max 100)

Returns:
    A dictionary containing:
    - data: List of prompt metadata objects
    - metadata: Pagination info (page, limit, total)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoFilter by exact prompt name
labelNoFilter by label (e.g., 'production', 'staging')
tagNoFilter by tag
pageNoPage number for pagination (starts at 1)
limitNoItems per page (max 100)

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 provided, the description carries the full burden. It discloses that the tool returns metadata with pagination, which is helpful. However, it doesn't mention behavioral aspects like rate limits, authentication requirements, or whether it's read-only (implied but not stated). The description adds some context but lacks comprehensive behavioral disclosure.

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

Conciseness4/5

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

The description is well-structured with clear sections (purpose, returns, args) and uses efficient language. However, the Args section duplicates schema information unnecessarily, and the opening sentence could be more front-loaded with key differentiators.

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 moderate complexity (5 parameters, filtering functionality) and the presence of an output schema (implied by the Returns section), the description provides adequate context. It explains what the tool does, what parameters control, and what it returns. The main gap is lack of usage guidance relative to sibling tools.

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 schema already fully documents all 5 parameters. The description repeats parameter information in the Args section but adds no additional semantic context beyond what's in the schema. This meets the baseline of 3 when schema coverage is complete.

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

Purpose4/5

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

The description clearly states the tool's purpose: 'List and filter prompts in the project.' It specifies the verb ('list and filter') and resource ('prompts'), but doesn't explicitly differentiate from sibling tools like 'get_prompt' or 'get_prompt_unresolved' beyond the listing/filtering aspect.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_prompt' (for single prompt retrieval) or 'list_datasets' (for similar listing of different resources), leaving the agent without context for tool selection.

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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