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

With no annotations, the description carries the full burden. It does disclose meaningful traits: the fusion of three signal sources, the per-lead credit cost, and the live-state whitelist. It omits any return-shape, pagination, or failure behavior, which leaves a gap for a tool with no annotation coverage.

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 action and ranking metric, then supporting facts. It is dense but every clause (scoring, signals, live states, credit cost) informs a decision; only the state list is mildly redundant with the schema.

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?

No output schema exists, so the description compensates by describing what a lead contains (signal_types, opening_score) and the coverage/cost model. It is nearly complete for an agent to call it correctly, though return shape and result-count behavior are unstated.

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?

Schema coverage is 100%, so the baseline is 3, but the description adds real interpretability: it explains what opening_score means by tying signal_types ('liquor', 'food_permit', 'business') to fused lead quality, giving context the schema alone implies only partially.

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 ('Find restaurants/bars about to open in a state'), names the ranking metric, and the data-fusion scope. It is clearly distinguishable from siblings like venue_signals and watch_area, which are not about pre-opening leads.

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?

It routes the agent to `coverage` for the live-state list and states the cost (1 credit per returned lead), which are useful invocation conditions. However, it never says when to prefer this tool over venue_signals or watch_area, so the alternative-selection guidance is only implied.

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