list_live_statesWhere we are live right now — the state codes, read from production, never a cached page.
Call it before promising a buyer a state: a state not in this list is not
live yet. Returns `[{"state": "CO"}, ...]` — codes only, no counts. For how
many records a state holds, `quote_list` (or `browse_leads(summary=True)`)
on that state returns the live graded counts.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds meaningful behavioral detail: data is read live from production, never cached, and the result is codes only with no counts. This goes beyond what annotations provide.
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?
Every sentence earns its place: what it returns, when to call it, the exact output shape, and what to use instead for counts. The core message is front-loaded and there is no 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?
Despite having no output schema, the description gives the exact return format. It also tells the agent how to interpret the list and how to get count data elsewhere. Nothing needed for correct invocation is missing.
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 there is no parameter semantics to elaborate. The description compensates by documenting the return shape exactly, which is the only operational detail an agent needs.
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 exactly what the tool does: returns live state codes from production, never from cache. Differentiates from siblings by emphasizing it is the authoritative source for currently-live states and pointing to quote_list/browse_leads for counts.
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 tells the agent when to call it — before promising a buyer a state — and gives a clear decision rule: a state not in the list is not live yet. It also names alternatives for count-related needs, so usage context is fully specified.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.