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therealsachin

Langfuse MCP Server

project_overview

Summarize project cost, token usage, and trace data within a specified time window to monitor analytics and track spending.

Instructions

Get a summary of total cost, tokens, and traces for a project over a time window.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fromYesStart timestamp (ISO 8601)
toYesEnd timestamp (ISO 8601)
environmentNoOptional environment filter (e.g., "production", "staging")
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves a summary but doesn't cover critical aspects like whether it's read-only (implied by 'Get'), potential rate limits, authentication needs, error handling, or the format of the returned data. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

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 a single, efficient sentence that front-loads the core purpose ('Get a summary') and specifies key metrics (cost, tokens, traces) and scope (project, time window). There is no wasted verbiage or redundancy, making it highly concise and well-structured for quick comprehension.

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

Completeness2/5

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

Given the complexity of summarizing project data with 3 parameters and no output schema or annotations, the description is incomplete. It doesn't explain the return format, potential limitations (e.g., data availability), or how it differs from sibling tools. For a tool without structured output information, more detail is needed to ensure the agent can use it effectively.

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?

The description mentions a 'time window', which aligns with the 'from' and 'to' parameters in the schema, but adds no additional meaning beyond what the schema provides (e.g., it doesn't explain the 'environment' parameter or provide examples like 'production'). With 100% schema description coverage, the baseline is 3, as the schema already documents parameters adequately without extra insights from the description.

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 with a specific verb ('Get') and resource ('summary of total cost, tokens, and traces for a project'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'get_cost_analysis' or 'get_daily_metrics', which might also provide cost or metric summaries, leaving some ambiguity about uniqueness.

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 mentions a 'time window' but doesn't specify scenarios, prerequisites, or exclusions, such as whether it's for high-level overviews or detailed breakdowns compared to siblings like 'get_metrics' or 'usage_by_model'. This lack of context makes it harder for an agent to choose appropriately.

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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