Get a free company primer for any US-listed company. Returns business overview, financial snapshot, and recent catalysts. No payment required.
| Name | Required | Description | Default |
|---|---|---|---|
| ticker | Yes | Stock ticker symbol (e.g. AAPL, MSFT, NVDA) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the weight of behavioral disclosure. It explicitly states what the tool returns ('business overview, financial snapshot, and recent catalysts') and that no payment is required. This adds meaningful context about the operation and its accessibility, though it does not cover rate limits, data freshness, or any potential side effects. It is transparent enough for a read-oriented tool.
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 two concise sentences. It front-loads the purpose and then details the return content and a key differentiator ('No payment required'). Every word earns its place, with no redundancy or tangential information.
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?
The tool is simple (one parameter, no output schema), and the description provides adequate context by stating what the primer includes. It does not explain the exact format or structure of the return, but the three components listed (overview, financial snapshot, catalysts) give a clear sense of the output. It is complete enough for a straightforward read-only tool.
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?
The input schema provides complete coverage for the single parameter 'ticker', including a descriptive example ('AAPL, MSFT, NVDA'). The description does not add further parameter details, but given the high schema coverage, the baseline of 3 applies. The description adds no extra meaning beyond what the schema already conveys.
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 clearly states the tool's function: 'Get a free company primer for any US-listed company.' The verb 'Get' it is unambiguous and the resource is defined. The scope is specific ('US-listed company'), and it distinguishes itself from siblings like 'get_fundamental_analysis' and 'get_investment_memo' by focusing on a primer (overview) rather than deep analysis.
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?
The description implies usage—it is for obtaining a quick company primer with basic business and financial info. It does not explicitly state when to use this tool instead of siblings such as get_fundamental_analysis or get_investment_memo, nor does it mention any exclusions. The 'free' and 'primer' wording hints at a lightweight overview, but clear guidance is missing.
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.
The three research products (primer, fundamental analysis, memo) are clearly differentiated by depth and cost. list_coverage and search_research overlap somewhat, but the distinction between enumerating all covered tickers and querying by name/ticker is evident from their descriptions.
All tools follow a consistent verb_noun pattern with snake_case (get_*, list_*, request_*, search_*). The verbs accurately reflect their actions, making the set predictable.
With 6 tools, the server is well-scoped for an equity research service, covering discovery, free/paid research tiers, and coverage requests without unnecessary complexity.
The surface covers the full workflow: free primer for any US company, paid deep-dive analysis, coverage listing/search, and the ability to request new coverage. No obvious gaps for the stated purpose.
