Institutional ownership of a company — total holders, ownership percentage, how many increased vs decreased positions, and the largest holders. Quarterly 13F data: always at least one quarter behind.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Top holders to include. Defaults to 10. | |
| ticker | Yes | Stock ticker (e.g. AAPL). Individual companies only. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With annotations already indicating readOnly, idempotent, and non-destructive behavior, the description adds valuable context by disclosing the data's quarterly nature and latency ('always at least one quarter behind'). It also details the specific output fields (total holders, ownership percentage, etc.), which is especially important given the lack of an output schema.
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, information-dense sentence that front-loads the key concept ('Institutional ownership of a company') and efficiently lists the output contents and data freshness. No unnecessary words 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 read-only tool with two parameters and no output schema, the description is quite complete: it names the main output fields, specifies the data source (13F) and its delay, and works with the schema to cover the 'ticker' constraint. It misses minor details like geographic limitations, but those are not critical for typical use.
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 100% coverage, with clear descriptions for both 'ticker' and 'limit' (including default and range). The description does not add any parameter-specific meaning beyond what the schema already offers, so the baseline of 3 is appropriate.
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: it returns institutional ownership data including total holders, ownership percentage, position changes, and largest holders. This specific listing of output content distinguishes it from sibling tools like get_insider_transactions or get_fundamentals, making the 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?
The description implies usage by specifying the data type (institutional ownership) and adds the note 'Quarterly 13F data: always at least one quarter behind,' which suggests it is not for real-time data. However, it does not explicitly name alternatives or provide when-to-use vs. when-not-to-use guidance, so usage context is only implied.
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.
With 57 tools, most have distinct purposes (market data, journaling, watchlists). A few related tools (get_price_alignment vs get_crypto_price_alignment, get_market_pulse vs get_market_movers) could cause miselection, but descriptions clarify asset types and scope.
Tools predominantly use get_/list_/create_/update_/delete_ verbs with clear noun suffixes. Minor deviations like start_here, whoami, add_to_watchlist, and remove_from_watchlist break the pure verb_noun pattern, but the style is consistent and readable.
At 57 tools, the server is far beyond the well-scoped range. While the domain is broad, this many tools will overwhelm an agent's capability to select accurately, and many could be consolidated (e.g., separate financial statements).
The server covers watchlist CRUD, trading journaling, market data (fundamentals, statements, news, transcripts), analysis tools, and community features. No obvious dead ends; lifecycle coverage is thorough for the described domain.
