get_market_pulse

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

Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false. The description adds valuable behavioral context: 'collected weekly from property portals,' indicating the data freshness and source. It also enumerates the key metrics returned, providing full transparency beyond the annotations without contradiction.

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 two sentences long, front-loaded with the tool's purpose and key details. Every word adds value—no fluff, no redundancy. It efficiently conveys scope, data points, and use case.

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?

For a simple tool with one parameter, no output schema, and informative annotations, the description is comprehensive. It explains what data is returned (listing counts, median prices, time on market), the update frequency (weekly), geographic coverage (England & Wales), and the rationale for using this over completed-sales data. It fully equips an agent to understand the tool's purpose and behavior.

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 single parameter 'area' is well-described in the schema as a UK postcode district with example 'E17'. The description does not significantly add meaning beyond the schema, but the example is helpful. Given 100% schema coverage, a baseline of 3 is appropriate.

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 description clearly states the tool retrieves live asking-market state for a UK postcode district, listing specific data points (active listings, new listings, price reductions, median price, time on market). It answers key questions about market movement and seller pricing, and the name 'get_market_pulse' complements the description. It implicitly distinguishes from siblings like get_area_score and get_area_context which likely provide different scopes of 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?

The description explicitly contrasts with completed-sales data that lags by months, indicating this tool is for current negotiation-side insights. It notes the geographic scope (England & Wales, sale listings) and provides a clear use case ('is this area moving or stuck?'). However, it could be even stronger by naming specific sibling tools as alternatives or explicitly stating when not to use this tool.

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