catalyst_for_company
Return verified catalyst events for one public company by ticker, each linked to its official source. Free preview; full data inline.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| ticker | Yes |
Return verified catalyst events for one public company by ticker, each linked to its official source. Free preview; full data inline.
| Name | Required | Description | Default |
|---|---|---|---|
| ticker | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses events are verified and linked to official sources, and mentions free preview with full data inline. However, with no annotations, it fails to clarify potential restrictions, auth needs, or response behavior on errors.
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 concise sentences front-load core action and add pricing context without redundancy.
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?
Adequately covers key points for a simple tool (what, for whom, source, pricing). Lacks explicit return format or edge-case handling, but sufficient given minimal parameters and no output schema.
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 has 0% description coverage; description merely repeats 'ticker' without adding format, examples, or domain restrictions, insufficient for a tool with zero schema documentation.
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 states the tool returns verified catalyst events for one public company by ticker, distinguishing it from siblings by specifying 'public company' vs drug or upcoming events.
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?
Implies usage when needing catalyst events for a specific ticker, but lacks explicit when-to-use or not-use guidance relative to sibling tools catalyst_for_drug and upcoming_catalysts.
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 targets a distinct query type: by company ticker, by drug name, or upcoming catalysts. Descriptions clearly differentiate them, leaving no ambiguity.
Tool names follow a similar pattern using 'catalyst' as a prefix, with 'for_company', 'for_drug', and 'upcoming_' modifiers. While not strictly verb_noun, they are consistent and predictable.
With 3 tools, the server is focused and efficient for its domain of biotech catalysts. It covers the core query types without being overly sparse or bloated.
The set covers catalysts by company, by drug, and upcoming events. Minor gaps like historical or date-range queries exist but are acceptable given the server's scope and the detailed data returned.