langfuse_health

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

With no annotations, the description carries the full transparency burden. It discloses a required scope (integrations:observe:read), policy governance, and ProofLink receipt sealing, which provides meaningful context beyond the schema. It also states what it returns, though it does not detail error conditions or exact output formatting.

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

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

The description is two sentences that are front-loaded with the primary purpose, followed by necessary scope and policy context. Every word earns its place, with no redundancy or filler.

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

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

For a simple health-check tool, the description covers the main bases: purpose, return values, required scope, and policy context. It does not specify the exact structure of 'ok status' or how to interpret unhealthy responses, but given the tool's simplicity, this is a minor gap.

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

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

The tool has zero parameters, so the schema fully covers parameter semantics. The description adds no parameter detail, but with no parameters to explain, the baseline of 4 is appropriate.

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

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

The description clearly states the specific verb 'Check' and the exact resource 'Langfuse LLM observability platform health', distinguishing it from sibling health tools like ragflow_health or shuffle_health by naming the platform. It also specifies what is returned (ok status and org name), adding concrete scope.

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

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

Usage context is implied by the tool name and description: use this when you need Langfuse platform health. However, there are no explicit when-to-use instructions, exclusions, or references to alternative tools, leaving the agent to infer the appropriate situation.

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