get_large_holdings_events
Get large-holdings disclosure events (JP 350/360 reports).
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| ticker | Yes |
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Get large-holdings disclosure events (JP 350/360 reports).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| ticker | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It only restates the tool's purpose without mentioning whether it is read-only, any rate limits, pagination behavior, or what happens on missing data. The output schema exists but is not referenced.
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 a single short sentence that efficiently communicates the core purpose. It could be expanded without harming conciseness, but as-is it is not verbose.
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?
Given the existence of an output schema and two parameters, the description is too brief. It lacks essential details about parameter behavior and return value structure, leaving significant gaps for the agent.
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 has 2 parameters with 0% description coverage. The description adds no meaning about 'ticker' (presumably a stock ticker) or 'limit' (how results are limited, possibly pagination). The agent must infer from parameter names alone.
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 'Get large-holdings disclosure events (JP 350/360 reports)', specifying the verb and resource with additional context about the report type. However, it does not distinguish from sibling tools like get_institutional_holdings or get_major_shareholders.
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?
No guidance is provided on when to use this tool versus alternatives such as get_director_holdings or get_institutional_holdings. There is no mention of prerequisites, typical scenarios, or exclusion criteria.
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 financial data aspect (e.g., balance sheet vs income statement vs cash flow; different holding types; metrics vs history). No overlapping purposes.
All tools follow verb_noun pattern with snake_case (e.g., get_balance_sheet, compare_metrics). Consistent and predictable.
19 tools is slightly above the typical 3-15 range but covers a broad domain (statements, metrics, holdings, screening). Still reasonable and well-scoped.
Covers most key financial data needs: statements, metrics, insider trades, institutional holdings, screen/search. Minor gaps like earnings estimates or dividend history are absent but core workflows are complete.