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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is clear. The description adds valuable behavioral context: it discloses that the tool returns a composite index, a regime label, per-component decomposition, a 'Tell', and data faults – effectively describing what the output includes without relying on the output schema. It also implies this is a point-in-time snapshot ('live'), which is relevant. No contradiction with annotations.

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 a single, front-loaded sentence that efficiently lays out the purpose and output components without extraneous words. Every clause adds information: 'live', '0-100 composite index', 'regime', 'per-component decomposition', 'Tell', 'data faults'. It is dense but well-structured and immediately communicates the tool's value.

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?

Given zero parameters and an existing output schema, the description fully covers what an agent needs to know: when to use it (explicit trigger), what it returns (index, regime, decomposition, tell, faults), and that it's a safe read operation (via annotations). It even hints at the tool's breadth by listing market areas. No gaps apparent for a tool of this complexity.

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 per rubric baseline is 4. The schema description coverage is 100% (trivially, no params). The description does not need to explain parameters, and it doesn't, which is appropriate. It explains what the tool returns, which is more useful than param detail here.

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 title and description clearly state it provides 'The live money-market funding-stress reading' – a specific, measurable output (index, regime, components, tell, faults). It distinguishes from siblings like 'money_market_context' and 'oil_funding_context' by focusing narrowly on funding stress. The verb is implicit but obvious ('read' or 'get'), and the resource is precisely 'money-market funding-stress'.

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?

Explicit usage trigger: 'Ask this whenever an analysis touches US dollar funding, repo, reserves, the Fed's balance sheet, or liquidity conditions.' This is clear and practical. However, it does not mention when NOT to use it or suggest alternatives (e.g., when a broader market context is needed), so it falls short of a 5.

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