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

Beyond the readOnly/openWorld/non-destructive annotations, the description discloses the live data source, the result categories, handling of missing data as no_data rather than estimation, output tags and timestamps, and the paid/trial credit behavior. The cost and trial-key details are especially valuable behavioral context that annotations do not cover.

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 dense but every sentence carries operational information: purpose, trigger definitions, missing-data policy, cost, and trial mechanics. It is reasonably front-loaded, though the first sentence is long and packs several result-format details together.

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 specialized paid scan tool with an output schema and safety annotations, the description covers what an agent needs: what is scanned, what the verdict states mean, how missing data is treated, and the payment/trial rules. No important invocation condition appears to be omitted.

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 parameters are already documented. The description still adds useful meaning around trial_key by naming the trial endpoint and the first-three-VERDICT-scans-free rule, and it clarifies that data comes from live Schwab rather than a generic source.

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 states a specific verb and resource: run one SML Triple-Trigger SPEC v2 scan of a ticker on live Schwab data. It also names the exact outcome categories (VERDICT, WATCH, NONE) and what they represent, so an agent can distinguish this tool from a generic quote or screening tool.

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 explicitly says to use the tool to check whether a ticker currently shows the three named trigger conditions, which gives clear intended-use context. There are no sibling tools to route between, but it also does not state exclusions or when not to use it, so it stops short of a 5.

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