Track City Changes Over Time

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

With no annotations, the description carries full burden and does meaningful work: it discloses the underlying data sources, the return structure (per-metric improving/declining/stable tags), and the analytical framing. It omits anything about auth requirements, rate limits, latency, or data freshness, which are the remaining gaps.

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 supporting sources, then output shape. Mostly earns its place, though 'Great for spotting momentum or emerging problems' is soft marketing filler that a stricter version would cut.

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 one-parameter read-only aggregate with no output schema and no annotations, the description gives enough: what it aggregates, what it returns, and the directional tagging scheme. Only the absence of any data-source caveats or freshness notes keeps it from 5.

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?

Single parameter with 100% schema description coverage, so the schema already documents 'city' fully with examples. The description adds nothing about city syntax (e.g., supported formats, whether metro areas count), so baseline 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+resource ('show how a city is changing') and immediately names the aggregation scope — BLS, FRED, FBI, permits, 311 — which distinguishes it from the single-domain siblings like query_employment or query_311_trends. The output shape ('directional dashboard') is also stated, so an agent can tell what it gets without opening a 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?

Gives clear context ('spotting momentum or emerging problems'), which tells the agent this is a trend/aggregate tool rather than a raw-data query. However, it never names an alternative or states a when-not condition (e.g., use query_city_data for raw values), so the exclusion guidance is absent.

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