Get top institutional holders of a stock from SEC 13F filings. Shows which hedge funds, mutual funds, and pension funds own the most shares, with quarter-over-quarter changes.
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | Page number | |
| limit | No | Results per page | |
| ticker | Yes | Stock ticker symbol (e.g. 'NVDA') |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the tool is a read operation (shows data) but does not disclose any behavioral traits like idempotency, authentication needs, rate limits, pagination behavior, or whether it returns only top N holders. This is adequate but lacks depth.
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 sentences, front-loads the purpose, and contains no unnecessary words. It efficiently conveys the core functionality.
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 without an output schema, the description gives a reasonable expectation of the response content (institutional holders with changes). However, it does not specify the response structure (e.g., list, fields like holder name, shares, change percentage). This is slightly incomplete but still informative.
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 coverage is 100% and the descriptions for page, limit, and ticker in the schema are clear and self-contained. The tool description does not add additional semantic information beyond the schema (e.g., example values or formatting). Baseline 3 applies.
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 retrieves top institutional holders from SEC 13F filings, specifying the data source and what it includes (hedge funds, mutual funds, pension funds with quarter-over-quarter changes). This distinguishes it from sibling tools like get_crypto_holders or get_institution_holdings.
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 provides clear context for when to use the tool (to get institutional holders) but does not explicitly state when not to use it or compare to alternatives. No exclusions or alternative tool mentions are given.
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 resource and action, and descriptions explicitly disambiguate similar pairs (e.g., get_congress_member vs get_congress_trades, get_crypto_holder vs get_crypto_holders). No two tools appear to do the same thing.
The dominant pattern is get_<noun>, with list_<noun> for enumerations. Minor deviations exist: a bare 'search' tool and the 'sec_' prefix on SEC filing tools break the uniform verb_noun style, but the pattern remains predictable.
At 24 tools, this is on the heavier side, but the server spans multiple financial data domains (SEC filings, stocks, insider trading, crypto, rates, economics), so each tool has a clear purpose. It is just below the 'too many' threshold.
The tool surface is remarkably complete for financial data retrieval: SEC filing lifecycle is covered (list -> index -> document), institutional ownership is available from both stock and institution perspectives, and insider/congress/crypto/economic data are all present. No obvious gaps or dead ends.