Retrieve just the top analyst-debate insights for a company — the punchiest, decision-relevant claims that AskCyborg's analyst panel surfaced after stress-testing the company. Faster and more focused than get_company_report when you just need 'what should I know about this company in 60 seconds'.
| Name | Required | Description | Default |
|---|---|---|---|
| company | Yes | Company name, ticker, or slug. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that the tool returns top, punchy, decision-relevant claims and is faster than a full report, adding meaningful context. However, it does not describe return format, pagination, or other potential behaviors, leaving some gaps.
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?
Two sentences, front-loaded with the core action, then a concise comparison and use case. Every sentence earns its place with zero fluff or repetition.
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 simple one-parameter tool with no output schema, the description provides essential context: what it returns, the benefit, and when to use it. It could mention the output format or structure slightly more, but it is adequately complete for the tool's simplicity.
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 schema already fully describes the only parameter 'company' with a clear description. The tool description adds no extra meaning to the parameter itself, so it appropriately relies on the schema. Baseline of 3 is justified.
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 uses a specific verb 'Retrieve' and a specific resource 'top analyst-debate insights for a company'. It clearly distinguishes itself from sibling tool get_company_report by emphasizing speed and focus, making the tool's unique purpose unambiguous.
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?
Provides clear context for when to use this tool ('when you just need what should I know about this company in 60 seconds') and explicitly names the alternative (get_company_report) with a comparative advantage. Does not explicitly state when not to use it, but the guidance is sufficient.
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.
Each tool serves a distinct purpose: comparing companies, retrieving full reports, fetching a quick score, and searching. No overlap or ambiguity between them.
All tool names follow a consistent verb_noun pattern (compare_companies, get_company_report, get_cyborg_score, search_companies), making them predictable and easy to understand.
4 tools is well-scoped for a company research server. Each tool earns its place without being too few or too many.
The tool set covers search, detailed report retrieval, quick score lookup, and comparison. A minor gap is the lack of a tool to list or get recent reports for a company, but core workflows are supported.
