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

Annotations already declare readOnly, idempotent, non-destructive and a closed world, so safety is covered. The description adds genuinely useful substance beyond them: the 0-100 scale, the four constituent factors with parenthetical definitions, and the fact that it concerns forward-guidance trustworthiness. It does not discuss data freshness or coverage limits, keeping it short of a 5.

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?

Front-loaded with the core purpose, then the scoring composition, then the usage context. The factor list is dense but each item earns its place by explaining what drives the score. Slightly long for a one-parameter read tool, but no filler sentences.

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 the description need not describe return values, and it still explains the score's scale and construction. Combined with full annotation coverage and a fully documented single parameter, an agent has almost everything needed; the only gap is disambiguation from the near-identical credibility sibling.

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?

There is a single parameter whose schema description coverage is 100%, so the schema already documents the ticker format and examples. The description adds no extra meaning about the ticker argument (e.g. whether non-NZX listings are rejected), so the baseline of 3 applies.

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 (get) and resource (management credibility score), and defines precisely what the score is: a composite 0-100 metric with four named factors. It is very clear on its own, but it never distinguishes itself from the close sibling get_credibility_momentum, so it falls short of full sibling differentiation.

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?

Explicitly gives the when-to-use context: evaluating management quality or deciding whether to trust forward estimates. That is a clear selection signal, but it offers no when-not-to-use guidance and does not point to any alternative tool for related questions.

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