List industries

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

The 'Read-only' opener merely restates readOnlyHint=true, earning no credit, but the description adds genuinely new behavioral context: it takes no input, returns both ids and display names, and flags that starred ids have published multiples in the open dataset. It does not discuss ordering or dataset size, 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?

Three short sentences, all front-loaded: read-only status, then what is returned, then the routing advice. No filler and nothing buried at the end.

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, yet the description still tells the agent what the payload means (ids, display names, starred ids with multiples) and how to use the result downstream. For a no-argument discovery tool this is fully sufficient.

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 are zero parameters, which is the baseline 4 case, and the description correctly confirms 'Takes no input' so the agent will not hunt for optional filters. No further parameter semantics are needed.

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 and resource: 'Lists every industry and sub-vertical ExitValue.ai tracks, with ids and display names.' It also scopes the content (which taxonomy, what fields, and the * marker for published multiples), so an agent can distinguish it from get_valuation_multiples and compare_industries without reading either schema.

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 says 'Use it first when you are unsure of an id' and notes that 'the other tools accept these ids or plain-English names' — it names the alternative path and the condition that selects this tool. That is both when-to-use and when-you-might-skip guidance.

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