US equity divergence read

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

Unusually strong: it discloses cost ($0.09 USDC per call, x402 on Base), billing behavior (settles only on success), latency bounds (10–180 s), and a security instruction to treat the response as untrusted data rather than instructions. These are behaviors the annotations (readOnly, openWorld, idempotent=false) cannot convey on their own.

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-loads the core verb+resource, then packs pricing, latency, and the untrusted-data caveat into tight clauses with no filler. Every sentence carries operational information an agent needs before calling.

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?

With no output schema, the description does name the response components (social sentiment, narrative, prediction-market context), which is the key missing piece elsewhere. It is nearly complete for a paid, high-latency research call; only a hint about response shape/size or failure modes is absent.

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% and only one parameter exists, so the baseline is already high. The description still adds value by framing the asset as a 'US stock ticker' with NVDA/TSLA examples, clarifying scope against the schema's own crypto-flavored 'BTC' example, though it stops short of stating validation rules or single-ticker constraints beyond the schema's maxLength.

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 operation — a sentiment-vs-price divergence read — on a clearly bounded resource (a single US stock ticker), and enumerates what the read covers: social sentiment, narrative, prediction-market context. It implicitly differentiates from siblings like vedetta_social and vedetta_narrative by bundling them into a divergence framing, but it never names those siblings directly.

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?

Usage is implied by the divergence framing and the 'Descriptive research, not financial advice' scope note, so an agent can infer this is for interpretive research rather than raw data pulls. However, no explicit when-to-use/when-not guidance is given, and with 19 siblings (vedetta_social, vedetta_trend, vedetta_snapshot) the agent gets no routing rule for choosing this over them.

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