list_districts

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

No annotations are provided, so the description carries full behavioral burden. It discloses a critical behavioral trait: the names are korter's own, not standard administrative districts, and gives a concrete example of geographic scope. This is valuable but only covers naming/scope; it says nothing about read-only nature, rate limits, caching, or response format. For a zero-param list tool, the biggest behavioral risk — 'these aren't the districts you think they are' — is addressed, earning a 3.

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?

Two sentences, front-loaded with the core purpose (taxonomy + average price), followed by the naming caveat. No wasted words. The dash construction is slightly informal but information-dense and easy to parse.

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 zero-param list tool with no output schema, the description covers purpose and a key caveat about naming. However, with no output schema, it does not describe what the returned list looks like (district names + price fields? hierarchies?) nor does it indicate if this is a static reference or computed fresh. Adequate but incomplete for an agent needing to interpret results.

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?

Zero parameters, so baseline is 4. The description correctly adds no parameter semantics because there are none to describe, and it wisely uses the space for scope clarification instead.

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 (list) and resource (districts/microdistricts) and adds the crucial scope — it's the platform's own proprietary taxonomy plus average price per m². This distinguishes it clearly from the sibling 'secondary_trends' or 'search_secondary', which handle market data differently.

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 implies this is the canonical source for district-level price averages, and the caveat about 'Vake district' swallowing Bagebi etc. implicitly guides interpretation. However, it does not explicitly state when to use this tool vs. alternatives like price_history or secondary_trends — the agent must infer that this is for static taxonomy lookups.

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