get_demo_compositeA single fixed demo ticker, callable without an API key, so the data shape can be inspected before signing up. Returns only the demo ticker regardless of input. For real tickers use get_composite, which requires a free key.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation already signals safety, but the description adds unique behavioral context: no API key required and output is always the demo ticker regardless of input. This goes beyond what annotations provide, though it doesn't detail rate limits or return format.
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?
Three concise sentences, each earning its place: purpose, behavior, and alternative. Information is front-loaded with the most important facts first, zero fluff.
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 tool with no parameters and no output schema, the description fully covers what the agent needs to know: what it returns (demo ticker), why (inspect data shape), auth constraints (no key), and how it differs from the real tool. No gaps.
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?
With zero parameters, the baseline is 4. The description adds value by explaining that input is irrelevant ('regardless of input'), which preempts any attempt to pass a ticker. Given the empty schema, this semantic clarification is helpful.
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?
Description clearly defines the tool as a fixed demo ticker for inspecting data shape, with the specific goal of pre-signup exploration. It explicitly distinguishes from get_composite for real tickers, satisfying the 'specific verb+resource+scope' criterion.
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?
Explicitly states when to use (before signing up) and when not (for real tickers), and names the alternative tool get_composite. This provides clear decision guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
get_composite and get_consensus both return per-ticker consensus with dimension breakdowns, creating ambiguity; agents might call the wrong one. Other tools are clearly distinct, but this overlap requires extra care.
All tools follow a verb_noun pattern: get_ for single entities, list_ for collections, and rank/search/screen as action verbs. The pattern is consistent and predictable across the entire set.
15 tools is well-scoped for a market intelligence server, covering single-ticker queries, lists, discovery, and market-level signals without unnecessary bloat.
The surface covers core workflows: ticker resolution, consensus, evidence, trades, positioning, screening, and market signals. Minor gaps exist (e.g., historical consensus or direct ticker comparison), but they are not critical.