bloomberg_status

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

With no annotations, the description carries the full behavioral burden. It discloses the diagnostic nature and what it reports (live backend plus connection details), which is useful, but says nothing about permissions, latency, or whether it touches the live connection, and does not explicitly confirm it is a safe non-mutating read.

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?

Two short sentences with the core purpose front-loaded and the call condition immediately after. Zero filler; every clause adds either the what or the when.

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?

An output schema exists, so return values need not be explained, and for a zero-parameter diagnostic tool the purpose plus call conditions are essentially complete. Only the absence of any safety/read-only framing keeps it off the top score.

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 takes zero parameters, so there is no parameter surface for the description to document; the 100% coverage figure is trivially met. The baseline for a parameterless tool applies and nothing is misleading.

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?

States a specific verb ('Report') and resource ('which backend is live ... and its connection details'), with parenthetical detail distinguishing real BLPAPI from mock. This is unmistakably distinct from the sibling data-retrieval tools like get_reference_data and get_historical_data.

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?

Gives a clear triggering condition ('Call this first when data looks wrong') plus a second use case (confirming the server talks to a real Terminal/SAPI/B-PIPE endpoint). It stops short of naming an explicit alternative or when-not-to-use, so it falls just short of the top band.

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