SEC Form 4 insider transaction history — executive buy/sell filings in the last 90 days with filing dates and links. Returns insider activity signal. Source: SEC EDGAR. Cryptographically attested with a post-quantum signed settlement receipt. Verify at trust.stratalize.com/verify.
| Name | Required | Description | Default |
|---|---|---|---|
| ticker | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the tool read-only and non-destructive. The description adds valuable behavioral context about the data source (SEC EDGAR) and the cryptographic attestation/verification process, which goes beyond the annotation baseline. It does not describe return format or pagination, but the attestation detail is significant.
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 information-dense, front-loading the core definition of SEC Form 4 insider transactions and then adding source, payload, and verification details. Every sentence contributes unique value, with no redundant phrasing or excessive length.
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 single-parameter, read-only tool with no output schema, the description covers the data source, time window, and output type (filings with dates/links) reasonably well. However, 'returns insider activity signal' is somewhat vague, leaving the exact return structure unclear, which slightly detracts from completeness.
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 provides only the parameter name 'ticker' and basic string constraints with 0% description coverage. The description does not explain what ticker means, provide examples, or clarify format, so it fails to compensate for the schema's sparse documentation, leaving the parameter semantics mostly to inference from the name.
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 identifies the resource (SEC Form 4 insider transaction history) and the specific scope (executive buy/sell filings, last 90 days, filing dates/links), distinguishing it from siblings like get_sec_beneficial_ownership by highlighting the Form 4 focus and the 90-day window.
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 explicit when-to-use or alternative guidance is provided. The tool's purpose implies it is for insider trading data from SEC filings, but there is no mention of when not to use it or what to use instead for broader ownership data, leaving usage context merely 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.
Multiple tools have overlapping purposes, e.g., get_inflation_benchmark and get_bls_inflation_components, get_commodity_benchmark and get_agricultural_commodity_benchmark. Descriptions provide some differentiation, but many benchmark tools cover similar domains, leading to high potential for misselection.
All tools follow a consistent 'get_' prefix with snake_case nouns, e.g., get_inflation_benchmark, get_ma_multiples_benchmark. No mixing of conventions or irregular naming patterns.
46 tools is excessive for a server focused on financial benchmarks and intelligence. While the domain is broad, many tools could be consolidated. The high count may overwhelm agents and suggests insufficient scoping.
The toolset covers a wide range of financial data—benchmarks, regulatory filings, commodity prices—but lacks granular tools like individual stock prices or sector-specific indices. Some areas (e.g., credit unions) are well-covered, but other common financial operations (e.g., portfolio analytics) are absent.